vvEPA
United States Office of Research and EPA/600/R-22/049
Environmental Protection Development October 2022
Agency Washington, D.C. 20460 www.epa.gov/nlisrc
THE WIDE-AREA
DECONTAMINATION TOOL
by
Kevin Wegman1, Emily Peraza1, Eli Detmers1, Timothy Boe2, M. Worth Calfee2, Sang Don Lee2, Joseph
Wood2, Paul Lemieux2, Leroy Mickelsen3
1 Battelle Memorial Institute
505 King Avenue
Columbus, Ohio 43201
2US EPA Office of Research and Development (ORD)
Center for Environmental Solutions and Emergency Response (CESER)
Homeland Security and Materials Management Division (HSMMD)
Durham, NC 27709
3US EPA Office of Land and Emergency Management (OLEM)
Office of Emergency Management (OEM)
Consequence Management Advisory Division (CMAD)
Contract EP-C-16-014 to Battelle Memorial Institute
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Acknowledgments
Contributions of the following individuals and organizations to this report are gratefully
acknowledged:
US Environmental Protection Agency (EPA) Project Team
Timothy Boe (Principal Investigator, EPA/ORD/CESER)
M. Worth Calfee, Ph.D. (EPA/ORD/ CESER)
Sang Don Lee, Ph.D. (EPA/ORD/ CESER)
Joseph Wood (EPA/ORD/ CESER)
Paul Lemieux, Ph.D. (EPA/ORD/ CESER)
Leroy Mickelsen (EPA/OLEM/CMAD)
US EPA Technical Reviewers of Report
Lukas Oudejans (EPA/ORD/ CESER)
Shannon Serre (EPA/OLEM/CMAD)
US EPA Quality Assurance
Ramona Sherman (EPA/ORD/CESER)
Battelle Memorial Institute
Kevin Wegman
Emily Peraza
Eli Detmers
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DISCLAIMER
The U.S. Environmental Protection Agency, through its Office of Research and Development,
funded and managed the research described here under Contract EP-C-16-014 to Battelle
Memorial Institute It has been subjected to the Agency's review and has been approved for
publication. Note that approval does not signify that the contents necessarily reflect the views of
the Agency. Mention of trade names, products, or services does not convey official EPA
approval, endorsement, or recommendation.
Questions concerning this document, or its application should be addressed to:
Timothy Boe
U.S. Environmental Protection Agency
Office of Research and Development
National Homeland Security Research Center
109 T.W. Alexander Dr. (MD-E-343-06)
Research Triangle Park, NC 27711
Phone 919.541.2617
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FOREWORD
The U.S. Environmental Protection Agency (EPA) is charged by Congress with protecting the
Nation's land, air, and water resources. Under a mandate of national environmental laws, the
Agency strives to formulate and implement actions leading to a compatible balance between
human activities and the ability of natural systems to support and nurture life. To meet this
mandate, EPA's research program is providing data and technical support for solving
environmental problems today and building a science knowledge base necessary to manage our
ecological resources wisely, understand how pollutants affect our health, and prevent or reduce
environmental risks in the future.
The Center for Environmental Solutions and Emergency Response (CESER) within the Office of
Research and Development (ORD) conducts applied, stakeholder-driven research and provides
responsive technical support to help solve the Nation's environmental challenges. The Center's
research focuses on innovative approaches to address environmental challenges associated with
the built environment. We develop technologies and decision-support tools to help safeguard
public water systems and groundwater, guide sustainable materials management, remediate sites
from traditional contamination sources and emerging environmental stressors, and address
potential threats from terrorism and natural disasters. CESER collaborates with both public and
private sector partners to foster technologies that improve the effectiveness and reduce the cost
of compliance, while anticipating emerging problems. We provide technical support to EPA
regions and programs, states, tribal nations, and federal partners, and serve as the interagency
liaison for EPA in homeland security research and technology. The Center is a leader in
providing scientific solutions to protect human health and the environment.
This report describes the methodology developed for the Wide-Area Decontamination Tool, a
tool developed to characterize the cost and time associated with a remediation effort following a
biological incident impacting indoor, outdoor, and underground areas. This report details the
development of this tool, which began with a detailed review of existing remediation tools, a
literature review, and an in-depth statistical analysis of data on different decontamination
methods. It also includes detailed calculations which are performed within the tool, as well as a
proposed model improvement plan for future work on the tool.
Gregory Sayles, Director
Center for Environmental Solutions and Emergency Response
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The Wide-Area Decontamination Tool
for
THE WIDE-AREA DECONTAMINATION TOOL
Prepared under Contract Number EP-C-16-014 Task Order 68HERC19F0117
Prepared for
Timothy Boe
EPA Task Order Contracting Officer
Prepared by
Battelle Memorial Institute
Columbus, OH 43201
September 29th, 2021
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TABLE OF CONTENTS
Disclaimer ii
Foreword iii
List of TABLES ix
List of Figures xi
Acronyms and Abbreviations xiii
Executive Summary 1
1 Introduction 2
1.1 Goals of Preliminary Modeling Efforts 2
1.2 Desirable Model Criteria 3
2 Literature Review 3
2.1 Existing Models 3
2.1.1 WADE Model Analysis 4
2.1.2 WEST Application Model Analysis 7
2.1.3 TOTS Model Analysis 8
2.1.4 Decontamination Spreadsheet Model Analysis 9
2.2 Field Studies 10
2.2.1 BOTEReport 10
2.2.2 UTR OTD Report 12
2.3 The BioDecontamination Compendium 13
2.4 Conclusion 15
3 Methodology 15
3.1 Model Methodology Overview 15
3.2 Incident Command 18
3.2.1 Incident Command Parameters 18
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3.2.2 Incident Command Model 18
3.3 Characterization Sampling 20
3.3.1 Characterization Sampling Parameters 20
3.3.2 Characterization Sampling Model 21
3.4 Source Reduction 28
3.4.1 Source Reduction Parameters 29
3.4.2 S ource Reducti on Model 30
3.5 Efficacy 32
3.5.1 BioDecontamination Compendium Review 33
3.5.2 Application Method Review 42
3.5.3 Application Method and Surface Type Combinations Review 43
3.5.4 Bivariate Relationship Analysis 43
3.5.5 Single Dimensional Uncertainty Analysis 49
3.5.6 Creating a Single Model 57
3.5.7 Efficacy Model Parameters 58
3.5.8 Efficacy Model 58
3.6 Decontamination 59
3.6.1 Decontamination Parameters 59
3.6.2 Decontamination Model 61
3.7 Clearance Sampling 63
3.7.1 Clearance Sampling Parameters 63
3.7.2 Clearance Sampling Model 64
3.8 Waste Sampling 65
3.8.1 Waste Sampling Parameters 65
3.8.2 Waste Sampling Model 66
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3.9 Travel 70
3.9.1 Travel Parameters 70
3.9.2 Travel Model 71
3.10 Model Assumptions 74
3.10.1 Fixed Team Sizes 74
3.10.2 Application of Multiple Decontamination Methods to the Same Area 75
3.10.3 Multiple Sample Analysis Labs 76
4 Future Improvements 76
5 Case Studies 77
5.1 Case 1 78
5.1.1 Approach 78
5.1.2 Model Changes 79
5.1.3 Results 80
5.1.4 Additi onal Analy si s 83
5.2 Case 2 84
5.2.1 Approach 84
5.2.2 Model Changes 86
5.2.3 Results 87
5.2.4 Additional Analysis 90
6 Quality Assurance 91
6.1 Case Studies 91
6.2 Hand Calculations 91
6.3 SME Discussions 91
6.4 Data Quality 91
7 Conclusion 91
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8 Literature Cited References 92
Appendix A: Representative Surface Names A-l
Appendix B: Baseline Parameters B-l
Appendix C: User Guide C-l
Appendix D: Redundant BioDecontamination Compendium Columns D-l
Appendix E: Unrelated BioDecontamination Compendium Columns E-l
Appendix F: Surface Type Lookup Tables For Interior Surfaces F-l
Appendix G: Surface Type Lookup Tables For Exterior Surfaces G-l
Appendix H: Surface Type Lookup Tables For Underground Surfaces H-l
Appendix I: Highly Correlated Scatter Plots 1-1
Appendix J: Verification Case 1 Input Data J-l
Appendix K: Verification Case 2 Input Data K-l
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LIST OF TABLES
Table 1: Relevant Data Found in the WADE Tool3 6
Table 2: Relevant Data found in the BOTE report7 11
Table 3: Relevant Data Found in the UTR OTD Report8 13
Table 4: Application Methods Found in the BioDecontamination Compendium9 14
Table 5: IC Model Parameters 18
Table 6: CS Model Parameters 20
Table 7: SR Model Parameters 30
Table 8: Compendium Columns Deemed Relevant to the Efficacy Model 34
Table 9: Converted Coupon Area Units 37
Table 10: Converted Volume of Agent Applied Units 37
Table 11: Converted Loading Units 38
Table 12: Converted Concentration Dose Units 38
Table 13: Unique Concentration Dose Units 39
Table 14: Columns Added to the BioDecontamination Compendium 40
Table 15: Nt Calculations Based on EffMeas 42
Table 16: Numerical Columns Included in the Bivariate Relationship Analysis 44
Table 17: Relationship Strength of Correlation Coefficients 44
Table 18: Compendium Datasets and Subsets Which Met r and p-value Thresholds 45
Table 19: Subsets with Strong Correlations with Loading 46
Table 20: Subsets with Strong Correlations with ConcDose 46
Table 21: Subsets with Strong Correlations with H202 46
Table 22: Subsets with Strong Correlations with Temp 47
Table 23: Subsets with Strong Correlations with RH 47
Table 24: Subsets with Strong Correlations with ContTime 47
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Table 25: Efficacy Model Parameters 58
Table 26: DC Model Parameters 60
Table 27: CL Model Parameters 63
Table 28: WS Model Parameters 65
Table 29: Transportation and Miscellaneous Considerations Parameters 71
Table 30: BOTE Cost Results 78
Table 31: BOTE Time Results 78
Table 32: Wide-Area Decontamination Tool Cost Results: BOTE 80
Table 33: Wide-Area Decontamination Tool Time Results: BOTE 81
Table 34: BOTE Cost Percentages 84
Table 35: BOTE Time Percentages 84
Table 36: UTR OTD Cost Results 85
Table 37: UTR OTD Time Results 85
Table 38: Wide-Area Decontamination Tool Cost Results: UTR OTD 87
Table 39: Wide-Area Decontamination Tool Time Results: UTR OTD 88
Table 40: UTR OTD Cost Percentages 90
Table 41: UTR OTD Time Percentages 90
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LIST OF FIGURES
Figure 1: TOTS Spreadsheet Tool Screenshot
Figure 2: Decontamination Spreadsheet Tool Screenshot
Figure 3: Wide Area Decontamination Model Flow
Figure 4: ModifyParameters.xlsx Screenshot
Figure 5: DefineScenario.xlsx Screenshot
Figure 6: Flowchart of Resources into the Wide-Area Decontamination Tool
Figure 7: Reviewed Application Method and Surface Type Combinations
Figure 8: Uniform X-Dependent Distribution for ConcDose and Efficacy for Foam Spray.
Figure 9: Drawn a and b Values for Each X-Value
Figure 10: Histogram of Efficacy for Physical
Figure 11: Bimodal Fumigation Efficacy Histogram
Figure 12: Histogram of Efficacy for Fumigation and IndoorCarpet
Figure 13: Histogram of Efficacy for Fumigation and IndoorCeilings
Figure 14: Histogram of Efficacy for Fumigation and IndoorMisc
Figure 15: Histogram of Efficacy for Fumigation and UndergroundCarpet
Figure 16: Histogram of Efficacy for Fumigation and UndergroundCeilings
Figure 17: Histogram of Efficacy for Fumigation
Figure 18: Bimodal Liquid Spray Efficacy Histogram
Figure 19: Histogram of Efficacy for Liquid Spray and Roofing
Figure 20: Histogram of Efficacy for Liquid Spray
Figure 21: Histogram of Efficacy for Liquid Immersion
Figure 22: Histogram of Efficacy for Gel
Figure 23: Histogram of Efficacy for Aerosol
Figure 24: Histogram of Efficacy for Fogging
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Figure 25: Efficacy Model Categorizations Grid 58
Figure 26: Team Makeup and Number of Teams for Each Element7 75
Figure 27: Team Makeup and Number of Teams for Each Element8 75
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ACRONYMS AND ABBREVIATIONS
AIC
Akaike Information Criterion
BOTE
Bio-response Operational Testing and Evaluation
CBR
Chemical, Biological, and Radiological
CBRN
Chemical, Biological, Radiological and Nuclear
CDC
Centers for Disease Control and Prevention
CFU
Colony Forming Units
CS
Characterization Sampling
DC
Decontamination
DHS
(US) Department of Homeland Security
EPA
(US) Environmental Protection Agency
GIS
Geographic Information System
HSRP
Homeland Security Research Program (EPA)
IC
Incident Command
LR
Log Reduction
MLE
Maximum Likelihood Estimation
NEIC
National Enforcement Investigations Center
OTD
Operational Technology Demonstration
PPE
Personal Protective Equipment
RTP
Research Triangle Park, NC
S&T
Science and Technology Directorate (DHS)
SR
Source Reduction
TOTS
Trade Off Tool for Sampling
UTR
Underground Transport Restoration
WADE
Wide-Area CBR Decontamination Incident Estimator
WADT
Wide-Area Decontamination Tool
WEST
Waste Estimation Support Tool
WS
Waste Sampling
Xlll
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EXECUTIVE SUMMARY
Large-scale biological incidents throughout indoor, outdoor, and underground areas have the
potential to extensively contaminate these sites, presenting risks to human health and requiring
extensive time, money, and resources to successfully decontaminate and allow these areas to be
utilized again. Contaminated sites must be sampled to characterize the level of contaminant
initially present; waste materials may be removed from the site to reduce the cost associated with
decontamination of materials that are not worth decontaminating; the site may need to be treated
with a decontamination agent; finally, after decontamination, surfaces may need to be sampled
again to ensure the level of contaminant has been adequately reduced or completely eliminated.
The ability to estimate the cost of decontaminating affected areas following such an incident, as
well as the time and resources required to do so, is critical to planning and preparedness for a
wide-area decontamination effort.
This report details the development of a probabilistic model, the Wide-Area Decontamination
Tool (WADT), which simulates the overall cost, time, and resource demand associated with the
decontamination of a wide-area indoor, outdoor, and underground biological incident. This effort
included three elements: 1) a review of existing models to identify important aspects of the
decontamination process and calculations that should be considered during the development of
the tool, 2) a review of studies on the mock decontamination of indoor and underground
transportation sites to determine how similar the three decontamination area types (i.e., indoor,
outdoor, and underground) were and to identify relevant data that could be used to facilitate the
probabilistic nature of the tool (note that no such outdoor study existed at the time of
development), and 3) an analysis of EPA's biodecon compendium to develop models for the
effectiveness of decontamination treatment types on various surface materials utilized in the tool.
A desktop application was developed to run the probabilistic model estimating cost, time, and
resource demands for a wide-area biological incident. Excel workbooks containing the baseline
parameters for these models were also developed, allowing users to easily modify any data
within the application. A series of equations was defined to characterize each step of the
decontamination process, including the sampling of surfaces to define initial contaminant levels,
removal of waste from the site area, and the decontamination of surfaces. Driving the
decontamination of surfaces is a series of equations and distributions developed to estimate the
effectiveness, or efficacy, of a particular decontamination treatment method on a given surface
material. This analysis provided a method for estimating efficacy although it should be noted that
a more rigorous multivariate analysis may be beneficial to constructing the best possible efficacy
model from the available data for future versions of the tool. While the developed application
includes most of the desired functionality decided upon at the start of the effort, a model
improvement plan was also included to suggest enhancements for future iterations of the tool.
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1 INTRODUCTION
1.1 Goals of Preliminary Modeling Efforts
There are many types of emergencies and disasters that threaten the stability of society. Among
the most serious are incidents involving a persistent biological agent (e.g., Bacillus anthracis, the
causative agent for anthrax), for which government agencies have a specific interest in
developing mitigation strategies. For example, the 2001 Amerithrax incident, where letters laced
with Bacillus anthracis were mailed via the U.S. Postal Service, killed five Americans and
injured 17 others and was considered the worst biological attack in U.S. history1. The first
incident of its kind, this event highlighted the importance of recovery planning in reducing the
disruption caused by the accidental or intentional release of a persistent biological agent.
Following a biological incident, it is critical that contamination within affected site areas is
contained and the impacted areas decontaminated to ensure the biological agent does not spread
and that the risk of exposure is reduced. However, remediation efforts for such an incident are
costly. In fact, the cost of decontamination after the Amerithrax incident was estimated to be
between $290 and $350 million2. Additionally, these large-scale efforts are time consuming and
place a high demand on several specific resources, requiring months to years to fully resolve in
the case of the Amerithrax incident. Thus, it is important for government agencies to estimate the
demands associated with a wide-area biological incident in order to better prepare for future
incidents.
Preliminary research efforts into the issue of wide-area decontamination defined the context and
scope of modeling such an event as 1) conducting a meticulous analysis of various existing
models, literature, and datasets, 2) identifying the decontamination steps that will be considered
in modeling efforts, 3) identifying potential models that are capable of estimating the many costs
and resource demands associated with a wide-area incident, and 4) developing and implementing
a final model. The initial review of the existing decontamination models identified the need for a
modeling tool that could characterize wide-area indoor, outdoor, and underground biological
incidents and estimate the cost, time, and resources associated with the decontamination of these
areas while implementing a methodology for estimating efficacy, or the effectiveness of a given
decontamination treatment at reducing the contaminant present on a surface. This efficacy
model, which no existing tool currently implements, would simulate decontamination in a more
realistic way: surfaces possibly requiring multiple treatments to be fully decontaminated.
The final developed model estimates the cost of each step of the decontamination process as well
as the overall cost of the remediation effort for the incident. It also estimates the overall time
spent decontaminating and the various resources needed for the process, such as personal
protective equipment (PPE), decontamination agent, and associated delivery systems. This
application includes highly detailed cost and resource parameters that have not yet been fully
implemented in other existing tools, as well as a model for estimating efficacy which is unique to
this tool.
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1.2 Desirable Model Criteria
In order to model wide-area decontamination following a biological incident, it was important to
consider the aspects of the model being selected. The following set of criteria was established to
describe the optimal model:
• The modeling tool should quantify the resource demands (e.g., cost, time, and materials)
of decontaminating a wide-area indoor, outdoor, and underground area following a
biological incident.
• The modeling tool should determine the resource demands of such an incident, including,
but not limited to, personnel requirements, PPE usage, decontaminants, equipment
acquisition and/or rentals, and sampling materials, as well as the costs associated with
sample collection, processing, analysis, and waste.
• The modeling tool should include traditional sampling types, such as sponge sticks and
37 mm vacuum filter surface sampling types, for the characterization of the amount of
contaminant present in the site area.
• The modeling tool should characterize a decontamination treatment by its efficacy, or its
effectiveness at reducing contaminant levels present on a given surface.
• The modeling tool should include methodology to estimate the efficacy of
decontamination treatment methods based on any environmental or surface composition
factors which have been identified as relevant to the estimation of efficacy.
• The modeling tool should calculate waste quantities generated as a result of the
remediation effort but should not include any cost estimates based on these quantities.
These cost estimates will be calculated by an outside tool, e.g., the Waste Estimation
Support Tool (WEST) application. The modeling tool should generate waste quantities in
a format that can be accepted by this outside tool. This outside tool will then calculate
costs associated with these quantities.
2 LITERATURE REVIEW
The development of the Wide-Area Decontamination Tool began with an in-depth review of
various existing models, literature, and data. These resources facilitated the effort by providing
valuable information and calculations that were used to fully define a wide-area decontamination
scenario. The following sections summarize the reviewed resources and detail the information
identified as relevant to the effort.
2.1 Existing Models
At the start of this effort, four existing models were reviewed, each of which were related to the
decontamination process in some way: 1) The Wide-Area Chemical, Biological, and
Radiological (CBR) Decontamination Incident Estimator (WADE)3, 2) The WEST application5,
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3) the Trade Off Tool for Sampling (TOTS)6, and 4) the Decontamination Spreadsheet. Each of
these tools were reviewed and analyzed to identify methodologies which were crucial to
modeling a decontamination event, as well as the parameters which were important to consider
as they applied to those methodologies. This analysis also helped identify areas where these tools
may have been missing key functionality or processes that were important to include in the
Wide-Area Decontamination Tool. The following sections summarize these models, detail the
relevant information identified within each, and highlight any areas in which gaps were found
within each model.
2.1.1 WADE Model Analysis
EPA's WADE tool was designed to help on-scene coordinators determine the cost associated
with the decontamination of indoor scenarios. The Microsoft Excel-based tool estimates the total
cost of decontamination by considering individual costs associated with each step, or element, of
the remediation process3. The elements considered in the WADE tool are each listed and defined
below:
• Incident Command: The oversight and management of all personnel and all
decontamination processes. This process is ongoing throughout the entire
decontamination event.
• Characterization Sampling: The sampling of all surfaces to define the level of
contaminant initially present at the site area.
• Site Containment: The process of containing site contamination to ensure that CBR
hazards do not spread to uncontaminated areas and to prevent potential recontamination
from other sites after decontamination.
• Source Reduction: The removal of contaminated waste materials from a site area before
any decontamination has begun.
• Decontamination: The treatment of contaminated surfaces with any agent which may
reduce the level of contaminant present on those surfaces.
• Waste Sampling: The sampling of waste materials removed from the site area to define
the level of contaminant present and determine how hazardous the waste is.
• Waste Management: The treatment/disposal of waste removed from a contamination
site area.
• Clearance Sampling: The sampling of surfaces after decontamination has been
performed to determine if the level of contaminant meets clearance standards and the site
can be deemed safe.
The WADE tool also included historical data gathered from several references which influenced
cost estimates. These data ranged from hourly wages for various personnel types which may be
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present onsite during a decontamination event to the numerous costs associated with a specific
decontamination treatment, such as fumigation3.
Analysis of the WADE tool and the historical data included within it helped identify the key
components necessary to fully define a decontamination scenario. Six primary elements of the
decontamination process were identified within this tool as relevant to the current effort: 1)
Incident Command (IC), 2) Characterization Sampling (CS), 3) Source Reduction (SR), 4)
Decontamination (DC), 5) Clearance Sampling (CL), and 6) Waste Sampling (WS).
Although WADE was developed for indoor scenarios only, many of the cost equations for the
four primary elements were deemed relevant for indoor and underground scenarios and were
utilized in the model development. Additionally, the historical data informing these elements
within WADE were included in the development of the initial workbook driving the model,
Individual Data for Parameters.xlsx. Each data point identified as relevant can be found in Table
1.
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Table 1: Relevant Data Found in the WADE Tool3
Relevant Data
Description
Personnel Required
Breakdown of personnel required for each team (includes
different personnel types)
Number of Teams Required
Number of teams required for each element of remediation;
teams nominally consist of three people.
Number of Entries
Number of times teams enter the site area
Respirator Quantity
Number of respirators for each person (either zero or one)
Surface Area per Sponge Stick
Surface area that can be sampled with one sponge stick
Surface Area per 37 mm Cassette
Surface area that can be sampled with one 37 mm cassette
Sponge Sticks Used
Number of sampling sponge sticks used per hour per
sampling team
37 mm Cassettes Used
Number of 37 mm cassettes used per hour per sampling
team
Waste Mass Removed per Hour per Team
Mass of waste removed from the site area per hour per team
before decontamination
Personnel Hourly Rates
Hourly wages for each personnel type
Per Diem
Daily allowance for personnel expenses
Respirator Cost
Cost per one respirator
Cost of Decontamination Agent
Cost of decontamination agent by volume
Cost per Sample Shipped
Cost to ship each sample to an external lab
Cost of Analysis per Sample
Cost associated with the analysis of one sample at an
external laboratory
Cost per Sponge Stick
Cost to purchase one sampling sponge stick
Cost per 37 mm Cassette
Cost to purchase on sampling 37 mm cassette
Vacuum for 37 mm Cassette Rental Cost
Rental cost per day for one 37 mm vacuum
IC Rentals per Day
Cost of any rentals required for Incident Command per day
Plane Ticket Cost
Cost of one roundtrip ticket
Values for each of these data points were included in the initial workbook. Values from other
sources were also added, as described in Section 2.2.1 and Section 2.2.2. Due to the high amount
of uncertainty associated with decontamination events given the plethora of potentially
contaminated surfaces, the number of decontamination methodologies and options, the various
other influencing factors that may change for decontamination scenarios (e.g., environmental
factors influencing efficacy, overall extent of contamination), and the sparsity of available data
covering these wide-ranging scenarios, distributions were fit to the final set of data points using a
Python script. These statistical models best quantified the vast number of parameters for any
potential scenario with the uncertainty associated with the available data captured by the
statistical bounds.
Each parameter which had only one data point reported was fit with a constant distribution. Each
parameter which had between 2 and 5 data points was fit with a uniform distribution. All other
parameters which had 6 or more data points were fit with the following distributions:
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• Beta PERT
• Truncated Exponential
• Lognormal
• Truncated Normal
• Uniform
• Weibull Minimum
• Weibull Maximum
Each distribution was fit to the data using the built-in SciPy stats .fit method in Python. The .fit
method estimates the parameters of a given distribution by using Maximum Likelihood
Estimation (MLE) or maximizing a log-likelihood function4.
An Akaike Information Criterion (AIC) estimator was then calculated using the formula in
Equation 1 in order to determine which distribution was the best fit using the log-likelihood (LL)
and the number of distribution parameters (K).
AIC = -2 LL + 2 K (1)
The distribution corresponding to the lowest AIC was subsequently fit to the data. Once
distributions had been fit to each parameter, a second worksheet, ModifyParameters.xlsx, was
generated as the baseline workbook driving the distributions from which values would be drawn
in the model. Additional information on these baseline values is provided in Section 2.4.
While WADE was found to be a valuable resource in informing the IC, CS, SR, DC, and WS
elements, the tool did not include any efficacy or probabilistic information, nor was it found
relevant to outdoor scenarios. The lack of efficacy modeling capabilities was noted as a
particular disadvantage of the tool as a number of parameters influence efficacy and the accurate
estimation of efficacy based on surface composition and decontamination treatment methods can
have a large impact on the cost resulting from remediation efforts. As such, the efficacy
modeling capabilities desired for the Wide-Area Decontamination Tool were considered a
crucial piece of the tool.
2.1.2 WEST Application Model Analysis
EPA's WEST application was designed to estimate waste quantities based on contamination,
decontamination, and geographic information system (GIS) datasets. WEST is a Microsoft
Access planning tool which aids decision making by generating and characterizing a first order
estimate of waste quantities following a radiological incident. It allows users to investigate
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different decontamination and demolition approaches and assess how these different approaches
affect waste generation. Included in the tool are three elements which were previously defined in
WADE: 1) Waste Sampling, 2) Waste Management, and 3) Clearance Sampling5.
Although Waste Management functionality was not a desired component of the wide-area
decontamination model, this application helped identify a structure for the model outputs to serve
as inputs to the WEST application. For instance, the WEST application accepts waste quantities
as model inputs to simulate waste sampling and management. As such, it was determined that
these quantities would be calculated within the wide-area model and the resulting outputs would
be compatible with the WEST application to facilitate further analysis.
As the WEST application focuses on the estimation of costs associated with waste sampling and
waste management, the tool did not include modeling which simulated the actual
decontamination of surfaces following a contamination incident or the estimation of the resource
demand associated with the remediation efforts of such an incident. However, such functionality
was considered the keystone of the Wide-Area Decontamination Tool.
2.1.3 TOTS Model Analysis
TOTS is a GIS-based Excel tool designed to estimate the resource demand associated with large-
scale sampling efforts. Following a CBRN incident, surfaces must be sampled to determine the
level of contaminant present in the affected area. EPA's Homeland Security Research Program
(HSRP) developed this tool to leverage geospatial data to estimate how sampling decisions affect
cost and resource demands6.
TOTS provided a useful framework for the scenario definition data required. For instance, the
TOTS tool allows users to define a breakdown of surface types and their overall percentage
contribution to the site area to inform the sampling scenario. This can be seen in a screenshot of
the tool in Figure 1. This same surface breakdown was utilized in the Wide-Area
Decontamination Tool.
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Sample Type Assignment
This will be filled in with surface information from BOTE
Surface Type
Surface Distribution
Sample Type
Surface 1
100%
Aggressive Air
Surface 2
0%
Micro-Vacuum
Surface 3
0%
Micro-Vacuum
Surface 4
0%
Robotic Floor Cleaner
Surface 5
0%
Swab
Surface 6
0%
Swab
Surface 7
0%
Swab
Surface 8
0%
Swab
Surface 9
0%
Swab
Surface 10
0%
Swab
Total
100%
Surface Type
Swab
0%
Sponge Wipe
0%
Micro-Vacuum
0%
Sponge-Wipe Composite
0%
Micro-Vacuum Composite
0%
Robotic Floor Cleaner
0%
Grab/Bulk
0%
Aggressive Air
100%
Wet Vacuum
0%
Total
100%
Main Sample Strategy
Sample Type Assignment
|| CalcTable | Sampling Toolbox Info | Chart Data | SA-Cost-Time | Time, SA=50 | Time, SA=500 | Time, SA=1000 ... 0 :
Figure 1: TOTS Spreadsheet Tool Screenshot
The cost and time estimates provided within TOTS for various sampling techniques on different
surfaces were used to inform the traditional sampling types of interest (e.g., sponge sticks and 37
mm vacuums) as well as nontraditional sampling types (e.g., robotic household vacuum cleaner-
type sampling and wet vac).
TOTS also provided a blueprint for the type of geospatial data required for defining an outdoor
incident. While geospatial data were not included in the first iteration of the Wide-Area
Decontamination Tool, these data will be useful for future iterations and improvements.
The TOTS spreadsheet focuses only on costs associated with sampling. As such, this tool did not
consider other elements of the decontamination process from which additional costs are
generated. Similar to the WEST application, this tool alone did not provide a detailed estimation
of the cost and resource demand associated with the remediation of a wide-area incident. It also
did not include any efficacy modeling capabilities, all of which was desired functionality of the
Wide-Area Decontamination Tool.
2.1.4 Decontamination Spreadsheet Model Analysis
The Decontamination Spreadsheet, an internal research effort at the EPA, simulates a
contamination incident in the Manhattan borough in New York City, New York. The spreadsheet
includes a breakdown of indoor, outdoor, and underground surfaces within the affected area as
well as detailed population, square footage, vegetation, and vehicle data for the affected area. A
screenshot of the tool is shown in Figure 2.
9
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Figure 2: Decontamination Spreadsheet Tool Screenshot
The breakdown of surfaces for indoor, outdoor, and underground spaces found in the tool was
used similarly in the Wide-Area Decontamination Tool. Additionally, the building types listed on
the "Occupancy" tab of the tool helped identify important building types to include within the
definition of indoor scenarios.
The Decontamination Spreadsheet did not include any estimation of costs or resources resulting
in the decontamination of a wide-area incident. Similar to the other tools analyzed, this
spreadsheet also did not include any efficacy modeling capabilities. Again, this tool alone is not
able to provide enough detail for use as an adequate recovery planning tool and does not include
key functionality that was desired for the Wide-Area Decontamination Tool.
2.2 Field Studies
In addition to the three existing models that were reviewed, two primary references were used as
a source of data to fill in the model and to inform model assumptions: the Bio-response
Operational Testing and Evaluation (BOTE) Project report7 and the Underground Transport
Restoration (UTR) Operational Technology Demonstration (OTD) report8. Each report
summarizes an in-depth investigation into the decontamination of different facilities and
provides a detailed cost analysis for the study. The following sections summarize both reports
and detail the relevant information identified within them.
2.2.1 BOTE Report
The BOTE Project report details a comprehensive investigation into the decontamination of a
biological agent in an indoor scenario, a joint effort between EPA, the Department of Homeland
Security Science and Technology Directorate (DHS S&T), and the Centers for Disease Control
and Prevention (CDC). In this mock decontamination scenario, a surrogate (Bacillus atrophaeus,
subspecies globigii) for the biological agent Bacillus anthracis was disseminated in a facility
modified to replicate an office and residential building. Surfaces were sampled with cellulose
10
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sponge-stick wipes, swabs, and vacuum socks to determine the initial level of contaminant
present. Waste material was subsequently removed from the site area and disposed of. The
building was then decontaminated using three different treatment methods: 1) fumigation with
hydrogen peroxide vapor, 2) surface decontamination using pH-adjusted bleach, and 3)
fumigation with chlorine dioxide gas7.
The objectives of the BOTE project were to employ three different decontamination methods in a
large building scenario to assess the efficacy of each and to characterize and analyze the costs
associated with the remediation process. Costs were broken down for each decontamination
method and included personnel entering and exiting the site area, materials, supplies, and rentals,
and waste management costs, as well as general costs which remained fixed between
decontamination methods, such as sampling costs and safety management oversight costs7.
The BOTE report included a myriad of data which was found to be relevant to both indoor and
underground scenarios. Each data point identified as relevant can be found in Table 2.
Table 2: Relevant Data found in the BOTE report7
Relevant Data
Description
Personnel Required
Breakdown of personnel required for each team (includes
different personnel types)
Hours per Entry
Amount of time needed to for teams to enter the site area
Number of Entries
Number of times teams enter the contaminated area
Respirator Quantity
Number of respirators for each person (either zero or one)
Personnel Overhead Days
Number of setup and teardown days at the start and end of
each element
Waste Mass per Surface Area
Mass of waste present at the site area per surface area
Sponge Sticks Used
Number of sampling sponge sticks used per hour per
sampling team
37 mm Cassettes Used
Number of sampling 37 mm cassettes used per hour per
sampling team
Solid Waste Mass Generated per Surface
Mass of solid waste generated after decontamination per
Area
surface area
Aqueous Waste Mass Generated per
Surface Area
Mass of aqueous waste generated after decontamination
per surface area
Personnel Hourly Rates
Hourly wages for each personnel type
Per Diem
Daily allowance for personnel expenses
Rental Car Cost
Cost of the rental car per day
Cost of Analysis per Sample
Cost associated with the analysis of one sample at an
external laboratory
Decontamination Materials Cost
Total cost of decontamination materials based on the
decontamination treatment method
These data were included in the initial workbook developed for the Wide-Area Decontamination
Tool and used to develop distributions for the baseline parameters found in
11
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ModifyParameters.xlsx. For more detail regarding the generation of this baseline workbook,
refer back to Section 2.1.1.
2.2.2 UTR OTD Report
The Underground Transport Restoration (UTR) Operational Technology Demonstration (OTD)
report by EPA summarizes the decontamination of a mock subway system contaminated with a
surrogate (Bacillus atrophaeus, subspecies globigii) for the biological agent Bacillus anthracis.
The UTR OTD project was similar to the BOTE project in that the Bacillus anthracis surrogate
was disseminated in a mock facility and surfaces were sampled using sponge sticks, vacuum
cassettes, and a wash/extract method to assess the present contaminant level in ballast. However,
this scenario did not include the removal of all waste materials prior to decontamination as some
were decontaminated with the surrounding site area. Additionally, only two methods of
decontamination were utilized in this study: 1) fogging with diluted bleach, and 2) liquid
spraying of pH-adjusted bleach8.
A cost analysis similar to that found in the BOTE report was also included in the UTR OTD
report. Data from this analysis were used to inform both the indoor and underground scenarios
and was included in the initial workbook developed for the Wide-Area Decontamination Tool to
develop distributions for the baseline parameters needed in the model calculations. Each data
point identified as relevant can be found in Table 3.
12
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Table 3: Relevant Data Found in the UTR OTD Report8
Relevant Data
Description
Personnel Required
Breakdown of personnel required for each team
(includes different personnel types)
Personnel Overhead Days
Number of setup and teardown days at the start and
end of each element
Number of External Labs
Number of external labs to which samples are sent for
analysis
Lab Distance from Site Area
Distance from the contamination site to each external
lab
Surface Area to be Sampled
Surface area which will be sampled for spore loading
Days Required for Decontamination
Days required to fully apply a decontamination
treatment method
Number of Teams Required
Number of teams required for each element of
decontamination
Hours per Entry
Amount of time needed to for teams to enter the site
area
Number of Entries
Number of times teams enter the site area
Solid Waste Mass Generated per Surface
Area
Mass of solid waste generated after decontamination
per surface area
Liquid Waste Mass Generated per Surface
Area
Mass of liquid waste generated after decontamination
per surface area
Volume of Decontamination Agent Applied
Volume of decontamination agent needed for
treatment
Personnel per Rental Car
Number of people using one rental car
Personnel Hourly Rates
Hourly wages for each personnel type
Per Diem
Daily allowance for personnel expenses
Decontamination Materials Cost
Total cost of decontamination materials based on the
decontamination treatment method
PPE Unit Costs
Cost per one unit of PPE for each PPE level
Cost of Decontamination Agent
Cost of decontamination agent by volume
IC Supplies Cost
Cost of supplies for the Incident Command element
These data were included in the initial workbook developed for the Wide-Area Decontamination
Tool and was used to develop distributions for the baseline parameters found in
ModifyParameters.xlsx. For more detail regarding the generation of this baseline workbook,
refer to Section 2.1.1.
2.3 The BioDecontamination Compendium
In addition to the existing models and literature used to inform this effort, an extensive dataset
consisting of information obtained from a vast literature search regarding the efficacy of various
decontamination methods on a variety of surface materials was also reviewed. This dataset, the
BioDecontamination Compendium, was found to provide relevant data for all three scenario
types (i.e., indoor, outdoor, and underground).
13
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The BioDecontamination Compendium combines data from over 150 peer-reviewed sources
investigating various methods of decontaminating Bacillus anthracis, from aerosolized sporicidal
solutions to UV irradiation. The processed compendium is made up of 8,555 records and
includes 71 columns of both numerical and nonnumerical data, all pertaining to the efficacy of a
specific decontamination application method on a specific surface10.
The BioDecontamination Compendium provided useful categorizations for which efficacy could
be investigated. For instance, the compendium included an extensive list of decontamination
treatment application methods which varied in their effectiveness. These methods are listed in
Table 4.
Table 4: Application Methods Found in the BioDecontamination Compendium9
Application Methods
Description
Aerosol
Aerosolized sporicidal agent sprayed onto a surface
Aqueous Suspension
Mixture of sporicidal solution with spore-laden suspension
Foam Ambiguous
Surface decontamination foam applied ambiguously to a surface
Foam Spray
Surface decontamination foam applied using a liquid sprayer
Fogging
Fogging device used to disperse an aerosol
Fumigation
Release of a gas or vapor in an enclosed environment
Fumigation/Liquid
Both fumigation and liquid application methods
Gel
Sporicidal gel applied to a surface
Immersion
Spore-laden surface immersed on a liquid solution containing
decon agent
Liquid
Sporicidal liquid applied to a surface in various ways
Liquid Dropper
Small amount of sporicidal liquid applied to a surface using a
dropper
Liquid Immersion
Spore-laden surface immersed in a liquid solution containing
decontamination agent
Liquid-Soaked Gauze Covering
Surface is covered in gauze soaked in sporicidal solution
Liquid-Soaked Gauze Wipe
Surface is covered in gauze wipe soaked in sporicidal solution
Liquid Spray
Liquid solution is applied to a surface by spraying
Liquid Suspension
Contaminated liquid suspended in sporicidal solution
Liquid Wipe
Cleaning wipes wetted with decontaminant solution
Decontamination of surfaces using methods such as ultraviolet
Physical
treatment, UV-excimer laser irradiation, microwave, infrared,
filtration, pasteurization
Solid Powder
Sporicidal powder applied to a surface
Suspension
Spore-containing liquid media is added to or spiked with a
solution of liquid decontamination agent to produce a treated
media
Note that some of these application methods have vague or similar descriptions. This list of
methods was reviewed, and some methods were found to be surrogates for others or irrelevant
entirely. The methods that were maintained for use in the tool are listed in Section 3.5.2.
14
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The compendium also included an extensive list of surface materials which these methods were
applied9. These materials can be found in Appendix A. The application methods and surface
materials combined created a classification system for efficacy and allowed estimates of efficacy
to be assigned to each combination. This classification was used extensively throughout the
Wide-Area Decontamination Tool. Other numerical data was also investigated to determine
which environmental factors (e.g., temperature and relative humidity), agent factors (e.g.,
sporicidal agent used, concentration of agent used), or application factors (e.g., contact time)
were relevant to efficacy and could be used to estimate a value for each of these classifications.
A rigorous analysis of these factors and their influence on efficacy was performed for each
classification and used to develop an Efficacy Model to determine the effectiveness of the
decontamination treatments performed within the tool. For a more detailed explanation of this
analysis, refer to Section 3.5.
2.4 Conclusion
Generally, the existing tools reviewed informed the methodologies within the Wide-Area
Decontamination Tool and identified the key modeling aspects desired in one standalone tool in
order to accurately and fully estimate the cost and resource demand associated with
decontamination. The field studies that were reviewed helped identify relevant operational data
that could be used as the underlying data within the tool to drive the calculations. Finally, the
BioDecontamination Compendium provided valuable efficacy modeling data which was
identified as unique to the Wide-Area Decontamination Tool. For a full list of data collected
from these sources, refer to Appendix B.
3 METHODOLOGY
3.1 Model Methodology Overview
The Wide-Area Decontamination Tool is a probabilistic model that estimates the efficacy of
decontamination treatments applied to various surfaces in realistic indoor, outdoor, and
underground scenarios in order to identify the cost and resource demand of a remediation effort
following a biological incident. The user defines the scenario type (i.e., indoor, outdoor, and
underground) and the necessary parameters. The scenario is then run, and the results are
calculated and output to the user. This flow is illustrated in Figure 3.
15
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Define Scenario
and Parameters
Underground
Decontamination
Indoor
Decontamination
Outdoor
Decontamination
Figure 3: Wide Area Decontamination Model Flow
The tool is an ASP.NET Core application with a VueJS frontend and is compatible with any
Windows system without additional dependencies. The ModifyParameters.xlsx Excel worksheet
drives the baseline parameters in the tool, allowing users to easily change underlying data to fit
their needs. A screenshot of this worksheet is shown in Figure 4.
A\
A
B
C
D
E
j
1 Phase
Q Category QName
Q Description
Q Units
Q Distribute
Teams Required
Number of teams required
II
Personnel Required (OSC)
Number of OSC personnel required per team
person / tearr
Personnel Required (PL-4)
Number of PL-4 personnel required per team
person / team
Personnel Required (PL-3)
Number of PL-3 personnel required per team
person / tearr
Personnel Required (PL-2)
Number of PL-2 personnel required per team
person / team
Personnel Required (PL-1)
Number of PL-1 personnel required per team
person / team
Number of Respirators per Person
Number of respirators required per each person
respirator / person
Surface Area per Wipe
Surface area that can be sampled per one wipe
iA2 / sample
Surface Area per Vacuum Sample
Surface area that can be sampled per one vacuum sample
mA2/ sample
Wipes per Hour per Team
Number of wipes used per hour per team
sample / (hour * team)
Vacuum Samples per Hour per Team
Number of vacuum samples used per hour per team
sample / (hour * team)
Entry Duration Based on PPE Level (A)
Duration of each entry for one personnel donning PPE Level A
hours / entry
Entry Duration Based on PPE Level (B)
Duration of each entry for one personnel donning PPE Level B
hours / entry
Entry Duration Based on PPE Level (C)
Duration of each entry for one personnel donning PPE Level C
hours / entry
Entry Duration Based on PPE Level (D)
Duration of each entry for one personnel donning PPE Level D
hours / entry
Number of Labs
Number of labs to which samples will be sent
labs
Lab Uptime Hours per Day
Number of hours lab is operational per day
hours / day
Lab Throughput Samples per Day
Number of samples analyzed per day
nples / day
Roundtrip Days
Travel days to and from the site area
days
Personnel Overhead Days
Number of setup and teardown days at the start and end of the phase
days
Packaging Time per Sample
Time required to package one sample
minutes / sample
Source Reduction Decontamination Clearance Sampling | Waste Sampling j ... (+)
Figure 4: ModifyParameters.xlsx Screenshot
A separate Excel worksheet, the DefineScenario.xlsx worksheet, lists all of the user-inputs that
can be defined and edited directly in the tool. A screenshot of this worksheet is shown in Figure
5.
16
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Area Contaminated
D
E
|; . F j
Q Description
Q Units
Q Distribution Ty|Q Parameter 1 Q Parai
The total outdoor surface area contaminated
.oading
The severity of contamination on outdoor surfaces
log(cfu / mA2)
Area Contaminated
The total indoor surface area contaminated
.oading
The severity of contamination on indoor surfaces
log(cfu / mA2)
Underground
Underground
Area Contaminated
The total underground surface area contaminated
Underground
Underground
.oading
The severity of contamination on underground surfac
log(cfu / mA2)
ndoor Contamination Breakout
The fraction of interio
contaminated surface area wh
ndoor Contamination Breakout
The fraction of interio
aminated surface area wh
ndoor Contamina
The fraction of
nated surface area wh
ndoor Contamina
The fraction of
nated surface area wh
Religious
ndoor Contamina
The fraction of
nated surface area wh
Government
ndoor Contamination Breakout
The fraction of interio
contaminated surface area wh
ndoor Contamination Breakout
The fraction of interio
contaminated surface a
Outdoor Exterior
Outdoor Surface Type Breakout
The fraction of surface outdoors which is building ext(
Outdoor Surface Type Breakout
The fraction of surface outdoors which is pavement
Roofing
Outdoor Surface Type Breakout
The fraction of surface outdoors which is roofing
Outdoor Surface Type Breakout
The fraction of surface outdoors which is water
Outdoor
|jl Underground
Underground
|~
Dutdoor Surface Type Breakout
The fraction of surface outdoors which is soil
Outdoor Miscellaneous
Outdoor Surface Type Breakout
The fraction of surface outdoors which is miscellaneo
Underground Walls
Jnderground Surface Type Breakou
The fraction of surface underground which is walls
Underground Ceilings
Jnderground Surface Type Breakou
The fraction of surface underground which is ceilings
Underground Carpet
Underground Surface Type Breakou
The fraction of surface underground which is carpet
I Extent of Contamination I
Figure 5: DefineScenario.xlsx Screenshot
Utilities were developed to convert both of these Excel worksheets to a usable format in the tool
for ease of user-editing and calculation purposes. Figure 6 below depicts a flowchart of resources
informing these worksheets which then inform the Wide-Area Decontamination Tool.
WADE
WEST App
TOTS
UTR OTD
n\
BOTE
Decontamination
Spreadsheet
DefirteScenario.il&x
BloDecontamination
Compendium
Wide Area
Decontamination Modeling
Tool
ModlfyParametersjdvK
Figure 6: Flowchart of Resources into the Wide-Area Decontamination Tool
The following sections detail the calculations performed within each element of the tool (e.g.,
incident command, characterization sampling) in order to estimate the cost and time associated
with a wide area decontamination incident. For a full guide on how to use the tool, refer to
Appendix C.
The model calculations are broken down by element: 1) Incident Command; 2) Characterization
Sampling; 3) Source Reduction; 4) Decontamination; 5) Clearance Sampling; 6) Waste
Sampling; and 7) Travel. The costs and times associated with each element are then summed to
17
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estimate the total resource demand of remediation for the incident. The following sections
describe the calculations performed for each of these elements of decontamination.
3.2 Incident Command
The IC element oversees the entire decontamination effort and is active during every model step.
It is important to note that the resulting IC costs do not change throughout the different elements.
The following sections list the parameters relevant to the IC model as well as the calculations
performed to characterize the cost and resource demands of this element.
3.2.1 Incident Command Parameters
The IC model parameters are listed in Table 5 below. Note that this table only includes user-
input and baseline parameters. All calculated quantities are explained in detail in the subsequent
section.
Table 5: IC Model Parameters
Parameter
Name
Description
Units
PQ
Personnel Required
Number of personnel of each type
required for one team (OSC, PL-1, PL-2,
PL-3, PL-4)
personnel
Pdo
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
Pdrt
Personnel Roundtrip Days
Number of travel days both to and from
site
days
Cp
Personnel Hourly Rate
Hourly wage of each personnel type
(OSC, PL-1, PL-2, PL-3, PL-4)
$/hour
Ced
Equipment Rental Cost Per
Day
Cost of Incident Command equipment
rentals per day
$ / day
CsD
Supplies Cost Per Day
Cost of Incident Command supplies per
day
$ / day
3.2.2 Incident Command Model
The overall cost of IC is broken down into two primary costs of equal weight: 1) cost of labor
(CL), and 2) cost of supplies (Cs). The cost of labor for IC is calculated using Equation 2 below.
CL= cj)* Tq (2)
Where:
• PH = Total IC labor horns.
• Pq = Number of personnel required per team by pera oniiel type
18
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• CP = Personnel hourly rare by personnel type
• Tq = Number of teams required for IC
The parameter PH is a calculated quantity for the total number of labor hours for IC. This
parameter is calculated using Equation 3 below. Note that 12-hour workdays were assumed in
keeping with what was found in the BOTE and UTR OTD project reports.
Ph = 12*Pd (3)
Personnel onsite, or PD, is calculated using Equation 4.
Pd — Pdcs Pdsr Pdqc ^'Dws ^Do (4)
Where:
• PDcs = Personnel onsite days for CS
• PdSr = Personnel onsite days for SR
• Pddc = Personnel onsite days for DC
• Pdws= Personnel onsite days for WS
• Pd0 = Personnel overhead days
Note that PDcs, Pdsr, Pddc¦¦ ar|d + Pdws are each calculated within their respective model
portion.
The cost of supplies for IC is calculated using Equation 5 below.
Q = P\v * (Ced + Csp) (5)
Where:
• Pw = IC workdays
• CEd = Equipment rental cost per day
• CSd = Supplies cost per day
19
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The parameter Pw is calculated using Equation 6 below.
P\v = Pd ~ Pd0 (6)
CL and Cs combine to give the overall cost of IC (Cic), as illustrated by Equation 7 below.
Clc = CL+ Cs (7)
3.3 Characterization Sampling
CS is required to determine the level of contamination which is present at the contaminated area.
This information is then used to determine which decontamination methods will be used and how
many applications will be needed. The following sections list the parameters relevant to the CS
model as well as the calculations performed to characterize the cost and resource demands of this
element.
3.3.1 Characterization Sampling Parameters
The CS model parameters are listed in Table 6 below. Note that this table only includes user-
input and baseline parameters. All calculated quantities are explained in detail in the subsequent
section.
Table 6: CS Model Parameters
Parameter
Name
Description
Units
At
Total Surface Area
Total surface area of the site
m2
As
Fraction of Surface Area to
be Sampled
Fraction of the total surface area that will
be sampled
unitless
WA
Surface Area Per Sponge
Stick
Surface area which can be sampled by
one sponge stick
m2/ sample
Ha
Surface Area Per 37 mm
Cassette
Surface area which can be sampled by
one 37 mm cassette
m2/ sample
WH
Quantity of Sponge Sticks
Used Per Hour Per Team
Number of sponge sticks used for
sampling per hour per team
samples /
hour * team
Hh
Quantity of 37 mm
Cassettes Used Per Hour
Per Team
Number of 37 mm cassettes used for
sampling per hour per team
samples /
hour * team
el
Entry Duration
Entry durations based on PPE levels
hours / entry
* team
EP
Entry Preparation Time
Time required for preparation into the
contaminated site area
hours / entry
* team
Edc
Decontamination Line Time
Time required for decontamination of
personnel upon exiting the contaminated
site area
hours / entry
* team
20
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Parameter
Name
Description
Units
Er
Post-Entry Rest Period
Time required for rest period upon exiting
the contaminated site area
hours / entry
* team
RP
Number of Respirators Per
Person
Number of respirators per one person
respirators /
person
To
Number of Teams
Number of teams required for element
teams
Personnel Required
Number of personnel of each type
required for one team (OSC, PL-1, PL-2,
PL-3, PL-4)
personnel
PD0
Personnel Overhead Days
Number of setup and teardown days at the
start and end of the element
days
Fraction of total PPE that is each level for
EPPETEAM
PPE Fraction Per Team
one team (Level A, Level B, Level C,
unitless
LevelD)
Labq
Number of Analysis Labs
Number of external labs to which samples
are sent for analysis
labs
Distance from
Distance of external lab from
km
ld
Contamination Site
contamination site
llf
Lab Throughput Per Day
Number of samples analyzed per day
samples / day
Tr
Time for Result
Transmission to IC
Time for sampling analysis results to be
sent from external labs to Incident
hours
Command
Tps
Time for One Sample to be
Packaged
Time for one sample to be packaged for
shipment to an external analysis lab
minutes /
sample
CEp
Entry Preparation Cost
Cost associated with preparation before
entering the site area
$ / entry *
team
CEDC
Decontamination Line Cost
Cost associated with the personnel decon
line
$ / entry *
team
CWA
Costs Per Sponge Stick
Sample
Analysis costs per one sponge stick
sample
$ / sample
cha
Costs Per 37 mm Sample
Analysis costs per one 37 mm cassette
sample
$ / sample
Cr
Cost Per Respirator
Cost per one respirator
$ / respirator
CEPPE
Cost Per Individual PPE
Cost per one unit of PPE of each level
$ / PPE level
cw
Cost Per Sponge Stick
Cost to purchase one sponge stick
$ / sample
CH
Cost Per 37 mm Cassette
Cost to purchase one 37 mm cassette
$ / sample
chd
37 mm Vacuum Rental
Cost Per Day
Cost of 37 mm vacuum rental per day
$ / day
rP
Personnel Hourly Rate
Hourly wage of each personnel type
(OSC, PL-1, PL-2, PL-3, PL-4)
$/hour
3.3.2 Characterization Sampling Model
Characterization Sampling is performed once before decontamination is performed in order to
characterize the amount of contaminant present on each surface. The overall cost of CS is broken
down into four primary costs of equal weight: 1) cost of labor (CL), 2) cost of supplies and
rentals (Cs), 3) cost associated with entering and exiting the contamination area (CE), and 4) cost
21
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of sample analysis, including shipping and packaging (CA). The cost of labor for CS is calculated
using Equation 8 below.
CL=PH* (PQ ¦ cp) * Tq (8)
Where:
• PH = Total CS labor hours
• PQ = Number of personnel required per team by personnel type
• CP = Personnel hourly rate by personnel type
• Tq = Number of teams required for CS
The parameter PH is calculated using Equation 9 below.
PH = 12 * PDcs (9)
Where the personnel onsite days, or Pocy is calculated using Equation 10.
PDCS = PDW + PD0 (1°)
Where:
• Pdw = Total workdays
• Pd0 = Personnel overhead days
The parameter PDw is calculated using Equation 11 below.
pdw = PoL + TEp + TEdc + TEr (11)
WThere:
• POL = Personnel labor days
• Tep = Total entry prep time
22
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* Tedc = Total personnel decon line time
• TEr = Total entry rest time
The parameter PDl is calculated using Equation 12 below.
p ,12)
p°L - 12 + 12
Where:
• WHR, Hhr = Number of hours spent sampling with sponge sticks or 37 mm vacuum,
respectively
These quantities are calculated using Equation 13 and Equation 14, respectively.
WQ
<13>
Hhr Hh * tq (14)
Where:
• WQ, Hq = Total quantity of sponge sticks or 37 mm cassettes used for sampling,
respectively
• WH, Hh = Quantity of sponge sticks or 37 mm cassettes used per hour per team,
respectively
The parameters WQ and HQ are calculated using Equation 15 and Equation 16, respectively.
i4c * At * 0.5
w" = —wT- <15)
i45 * Aj * 0.5
~Ha
Hq = -JL—^ (16)
Where:
23
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• As = Fraction of the surface area of the contamination site to be sampled
• At = Surface area of the contamination site
• WA, Ha = Surface area covered by one sponge stick or 37-mm cassette, respectively
Note that the total surface area sampled is evenly split between the sponge stick and 37-mm
cassette sampling types.
The parameter TEp is calculated using Equation 17 below.
TEp = Et * EP (17)
Where:
• ET = Total number of entries
• EP = Prep time required per entrance
The parameter ET is calculated using Equation 18 below.
*•1
PDl * 12
PPE Levels (18)
Ed;
Where:
• PPE Levels = The number of unique PPE levels required for the team (note that if a
specific level of PPE is not required, the default contribution to the total number of
entries for that level is 0)
• EDi = The entrance duration based on the PPE level i
The parameter TEdc is calculated using Equation 19 below.
TeDc = Et * Edc (19)
Where:
Edc = Time required for personnel decon line operations after each entrance
24
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The parameter TEr is calculated using Equation 20 below.
TEr = Et * Er (20)
Where:
• Er = Time required for rest after each entrance
The cost of supplies for CS is calculated using Equation 21 below.
Cs = (WQ * Cw) + (Hq * CH) + (Hd * CBd) (21)
Where:
• Cw, CH = Cost per one sponge stick or 37 mm cassette, respectively
• Hd = Total 37 mm vacuum rental days
• CHd =37 mm vacuum rental cost per day
The parameter HD is calculated using Equation 22 below.
Hd = (22)
A lag time due to time spent analyzing samples at external labs (TLAG) is also calculated for the
CS element. TLAG is calculated using Equation 23 below.
Tlag = + maxfT^j) + 7^ (23)
Where:
• TP = Total packaging time for all samples
• TLi = Total time samples spent at lab for each external lab i
• Tr = Time for completed sample result to be transmitted to IC
The parameter TP is calculated using Equation 24 below.
25
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T _tPs*{wq + hq)
F 60 min * 12 k
(24)
Where:
• TPs = Time for one sample to be packaged (minutes per sample)
Note that this equation includes a conversion from minutes to days as it was necessary to convert
the packaging time per sample given in minutes to a total packaging time for all samples in days.
The parameter TLi is calculated using Equation 25 below.
TLi = TSi + TAi (25)
Where:
• TSi = Total shipping time to each external lab i which is assumed to be 12 hours as
samples are overnighted to their destination
• TAi = Total sample analysis time per each external lab i
The parameter TAi is calculated using Equation 26 below.
Wq_+Hq_
LabQ LabQ (26)
Where:
• Labq = Number of external labs to which samples are sent for analysis
• Lt = Lab throughput for each external lab i
Note that an equal number of sponge stick and 37-mm cassette samples are sent to each external
lab for analysis.
The cost associated with entering and exiting the contamination site for CS is calculated using
Equation 27 below.
26
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Ce — Cel + * Cjj) + (Eppe ' ^Eppe) (27)
Where:
* cel - Entrance/exit labor cost
• Rq = Total number of respirators
• CR= Cost per respirator
* EppS = Total PPE quantity for all CS teams by PPE level
• CEppE = Cost per one PPE unit by PPE level
The parameter CEl is calculated using Equation 28 below.
Cel = [P« * (K * 5) * TQ] + Crp + (28)
Where:
• CTp = Total cost of entry prep
• CTj = Total cost of personnel decon line operations
The parameter CTp is calculated using Equation 29 below.
CTp = Et * CEp (29)
Where:
• CEp = The cost of entry prep per entrance
The parameter CT[)C is calculated using Equation 30 below.
Ctdc = Et * CE[)C (30)
• Cedc = The cost of personnel decon line operations per entrance
The parameter Rq is calculated using Equation 31 below.
27
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Rq = Pq * Tq * Rp
(31)
Where:
• RP = Number of respirators per person (typically either 0 or 1)
Hie parameter Eppe is calculated using Equation 32 below.
Eppe = Epp£TEAM * Eqt * ^ Pq
Where:
• ^ppeteam = Fract,0Q °f total PPE that is each level, per one team
c, = (IV, • + (fl, . (33)
Where:
• CWa, Ch a = Cost of one sponge stick sample or 37 mm sample for analysis, respectively
CL, Cs. CE, and CA combine to give the overall cost of CS (Ccs), as illustrated by Equation 34
below.
Ccs = CL + Cs + CE + CA (34)
3.4 Source Reduction
SR is the process of removing contaminated material to save the cost of decontaminating these
contaminated materials. SR is used to reduce the potential material demands associated with
different decontamination methods; material demand issues can significantly impact the amount
of decontamination chemicals required to decontaminate a given area. The cost and time savings
associated with SR being removed from the site is heavily dependent upon the decontamination
method that would have been used as well as the amount of material packaged and removed from
the site area. For example, if all roofing material is removed and hauled away from the site as
waste it will not be required to be decontaminated. However, the tool does not implicitly adjust
the amount of material removed based on the decontamination method chosen as the specific
28
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details of what the SR consists of (e.g., roofing, vehicles, vegetation) are user defined and
amounts and associated costs would be highly variable and difficult to automate. As such,
realistic differences in SR results between different decontamination methods are only seen if the
user adjusts the amount of material removed based on the decontamination methods they
selected.
The following sections list the parameters relevant to the SR model as well as the calculations
performed to characterize the cost and resource demands of this element.
3.4.1 Source Reduction Parameters
The SR model parameters are listed in Table 7 below. Note that this table only includes user-
input and baseline parameters. All calculated quantities are explained in detail in the subsequent
section.
29
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Table 7: SR Model Parameters
Parameter
Name
Description
Units
Af
Total Surface Area
Total surface area of the contamination
site
m2
Amass
Fraction of Mass to be Source
Reduced
Fraction of the total waste mass to be
removed
unitless
MASS,4
Mass Per Surface Area
Mass of waste per surface area of site
kg / m2
MASSh
Mass Removed Per Hour Per
Team
Mass of waste removed per hour per
team
kg / hour
* team
Entry Duration
Entry durations based on PPE levels
hours /
entry *
team
EP
Entry Preparation Time
Time required for preparation into the
contaminated site area
hours /
entry *
team
Edc
Decontamination Line Time
Time required for decontamination of
personnel upon exiting the contaminated
site area
hours /
entry *
team
Er
Post-Entry Rest Period
Time required for rest period upon
exiting the contaminated site area
hours /
entry *
team
RP
Number of Respirators Per
Person
Number of respirators per one person
respirators
/ person
T0
Number of Teams
Number of teams required for element
teams
Personnel Required
Number of personnel of each type
required for one team (OSC, PL-1, PL-2,
PL-3, PL-4)
personnel
PDo
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
1
eppeTEam
PPE Fraction Per Team
Fraction of total PPE that is each level
for one team (Level A, Level B, Level C,
Level D)
unitless
Cr
Cost Per Respirator
Cost per one respirator
$/
respirator
CEppe
Cost Per Individual PPE
Cost per one unit of PPE of each level
$ / PPE
level
Cmass
Cost Per Mass of Material
Removed
Cost per mass of waste materials
removed from site
$ / kg
CEp
Entry Preparation Cost
Cost associated with preparation before
entering the site area
$ / entry *
team
Cedc
Decontamination Line Cost
Cost associated with the personnel decon
line
$ / entry *
team
Cp
Personnel Hourly Rate
Hourly wage of each personnel type
(OSC, PL-1, PL-2, PL-3, PL-4)
$/hour
3.4.2 Source Reduction Model
30
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The overall cost of SR is broken down into two primary costs of equal weight: 1) cost of labor
(CL) and 2) cost associated with entering and exiting the contaminated area (CE). The cost of
labor for SR is calculated using Equation 35 below
0, — * [Pq ' Cp l] + (MASSq * CWAS5)
(35)
Where:
• PH = Total SR labor horns
• Tq= Number of teams required for SR
• PQ = Number of personnel required per team by personnel type
• Cp = Personnel hourly rate by personnel type
• MASSQ = Mass of waste removed from contamination site
• CMA5S = Cost per mass of waste material removed from contamination site
The parameter PH is calculated using Equation 36 below.
Where the personnel onsite days, or Pdsr- is calculated using Equation 37.
• Pw = Total workdays
* PD0 = Personnel overhead days
The total number of workdays for SR is calculated using the same equation as is used in the
calculation of total workdays for CS. See Equation 11 for the appropriate calculation.
The parameter PDl is calculated using Equation 38 below.
PH - 12 * PDsr
(36)
* 0 SR ' W 1 Dq
(37)
Where:
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D —
°L 12 * MASSh * Tq
MASSq
(38)
Where:
• MASSh = Mass of material removed from contamination site per hour per team
The parameter MASSq is calculated using Equation 39 below.
MASSq = At* A
MASS
* MASSa
(39)
Where:
• At = Total surface area of the contamination site
• Amass = Fraction of the total waste mass to be source reduced
• MASSa = Mass of waste per surface area of contamination site
The cost associated with entering and exiting the contamination site for SR is calculated using
the same equations as are used in the calculation of entrance and exit cost for CS. See Equations
27-33 for the appropriate calculations.
CL, and CE combine to give the overall cost of SR (CSR), as illustrated by Equation 40 below.
At the heart of the decontamination model is the Efficacy Model, which estimates the efficacy of
a given decontamination application method on a specific surface type. The development of the
Efficacy Model began with a detailed review of the BioDecontamination Compendium in order
to identify and utilize relevant data9.
The BioDecontamination Compendium consisted of 8,555 records of data from a myriad of
literature investigating the efficaciousness of different decontamination application methods on
various surface materials. This compendium contained valuable data pertaining to
decontamination which were used to develop a model estimating the efficaciousness of the
application methods found in the compendium on various indoor, underground, and outdoor
surface types. However, this compendium contained naming inconsistencies for various
parameters. It also contained ambiguous and supplemental data that were either unquantifiable or
Csr — CL + CE
(40)
3.5 Efficacy
32
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unnecessary. As such, the compendium underwent a rigorous review before any analysis on the
efficacy parameters was performed. The following sections describe not only this review and the
subsequent analysis of the cleaned data, but the resulting efficacy model as well.
3.5.1 BioDecontamination Compendium Review
The BioDecontamination Compendium review consisted of the following five steps:
1. Identification of relevant columns
2. Resolution of ambiguous values and removal of incomplete values
3. Removal of unnecessary records
4. Conversion of data
5. Additional calculations
Each of the steps is described in detail in the following sections.
3.5.1.1 Identification of Relevant Columns
It was important to first identify columns that were deemed relevant to developing an efficacy
model based on decontamination application type and surface material in order to reduce the
scope of the compendium. The BioDecontamination Compendium contained 71 columns, not all
of which were deemed necessary for modeling efficacy. Table 8 lists only the 27 columns within
the compendium that were kept.
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Table 8: Compendium Columns Deemed Relevant to the Efficacy Model
Column Name
Description
Ref
Reference where data given in the corresponding record can be found
AppMeth
Decontamination application method applied to surface
LoadingNum
Target number of spored the surface is initially contaminated with pre-
decontamination treatment
Loading Un
Units of the pre-treatment spore loading
LposRec
Log of the spores recovered from the positive control coupon
CoupArea
Area of the test coupon
CoupAreaUn
Units of the area of the test coupon
ConcDoseNum
Concentration of the active decontamination agent in the treatment
ConcDoseUn
Units of the concentration of active agent
VolApp
Volume of decontamination agent applied
VolAppUn
Units of the volume of agent applied
TempNum
Temperature of environment where decontamination was performed (in Celsius)
RHNum
Relative humidity of environment where decontamination was performed (in %)
ContTimeNumMin
Amount of time that a surface is exposed to a treatment method (in minutes)
EffMeas
Measure that the efficacy value is given in
Eff
Effectiveness of treatment in reducing spores on a given surface
ReApp
Number of times a decontamination method is reapplied
DeconAgent
Active decontamination agent
Rinsate
Number of spores rinsed off material after decontamination
RinsateUn
Units of the rinsate
EffVar
Value of efficacy variability statistic
EffV arStat
Variability statistic
Positives
Number of samples out of N positive for growth after treatment
C102(ppm)
Chlorine dioxide concentration applied
MB(mg/L)
Methyl bromide concentration applied
H202(ppm)
Hydrogen peroxide concentration applied
N
Number of replicates of test condition
Certain columns within the BioDecontamination Compendium were deemed redundant as
equivalent data could be found in another column. These columns were thus removed from the
compendium. A list of the columns that were removed on this basis can be found in Appendix D.
Finally, some columns within the BioDecontamination Compendium were deemed not relevant
for the purposes of efficacy model development. A list of the columns that were removed on this
basis can be found in Appendix E.
3.5.1.2 Resolution of Ambiguous Values and Removal of Incomplete Values
Data input into the compendium was not always in the right format (e.g., strings within
numerical columns). In order to enable further processing of these data, unwanted values were
removed, and ambiguous values were resolved, as follows:
• Strings that implied no value was given (i.e., "ambiguous", "undefined", "not reported")
34
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were removed from the numerical columns and given a null value.
• Strings that could not be converted to any specific value (i.e., "trigger pulls of spray", "as
needed to keep wetted", "until wetted") were removed from numerical columns and
given a null value.
• Values that were given with a ">" or "<" symbol were replaced with the numerical value
without the symbol.
• Values input as ranges were removed and replaced with the lower value in the given
range.
• Inconsistent naming was addressed within text columns to standardize naming
conventions. For instance, within the AppMethod column, "liquid (ambiguous)" was
changed to "liquid ambiguous", the latter of which was the naming convention that
occurred most throughout the column.
• All studies where the efficacy value was recorded as "Lrsurf' were changed to list "LR"
as the EffMeas. This was done because in the three studies for which "Lrsurf' was
recorded, efficacy values were reported as a log reduction (LR) and the term "Lrsurf
was never defined.
• For the ContTime column, most contact times found in the compendium were estimated
based on plot images using the WebPlotDigitizer tool. This tool extracts numerical data
from charts and graphs12. However, these data extraction is only an estimation of the
actual plotted data. As such, certain contact times were extracted and input into the
compendium as negative values. To ensure physical validity of the values utilized, any
negative times were set to zero.
• The list of application methods found in the compendium were narrowed down by
determining which methods could be surrogates of others. "Foam Ambiguous" was
deemed a sufficient surrogate for "Foam Spray". "Fumigation/Liquid" was found to
include only data that was applicable to the "Liquid" method and was thus replaced with
this naming convention. "Immersion" was found to be equivalent to "Liquid Immersion".
Finally, "Liquid", "Liquid Ambiguous", and "Liquid Dropper" were all found to be
equivalent to "Liquid Spray".
3.5.1.3 Removal of Unnecessary Records
Some of the data in the compendium were removed as certain records could not be used in the
development of the efficacy model. The records removed along with the justification for removal
are as follows:
• All records that did not list a decontamination treatment application method
(AppMethod) were removed as these records could not be classified based on their
application method and therefore did not help define any specific treatment. Four records
were removed on this basis.
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• The efficacy measure QualPos describes the number of test replicates that tested positive
for growth after decontamination treatment. Likewise, QualNeg describes the number
that tested negative for growth. These efficacy measures could not be used to calculate a
number of spores recovered from the test coupon after treatment and thus an investigation
into these studies was performed to determine if more detailed data could be gathered.
Through this investigation, it was found that one of two things occurred within the
studies with these efficacy measures: 1) for shorter studies, better data could not be
collected as the records in the compendium already contained all of the data found in the
study, and 2) for studies that provided more data regarding their findings, data were
typically presented in a more usable way (log reductions, number of spores recovered
from the test coupon after treatment) and these data was also input into the compendium
when available. However, these studies may have also included QualPos/QualNeg data
for various bio test strips which acted as supplemental data. For these reasons, QualPos
and QualNeg records were removed. Five hundred and thirteen records were removed on
this basis.
• Loading values were given in a variety of units. However, for standardization purposes,
all Loadings were converted to a value of CFU per area, mass, or volume of the test
coupon. Thus, a coupon area, mass, or volume was required for all Loadings given in
CFU. All records that gave LoadingUn in CFU but did not provide a coupon area, mass,
or volume were removed. Four hundred and thirty-nine records were removed on this
basis.
3.5.1.4 Conversion of Data
Data given in the compendium came in a variety of units, even within the same columns. In
order to compare data within and between columns, it was necessary to convert numerical
columns to standard units.
The following coupon area units (CoupAreaUn) shown in Table 9 were converted to standard
units. Note that some of the coupon surfaces were liquids and thus a volume was provided for the
area column. Additionally, some of the coupon surfaces were foods or irregular shapes and thus
a mass was provided for the area column.
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Table 9: Converted Coupon Area Units
Original Units
Converted Units
mm2
cm2
m2
cm2
In2
ft2
uL
ml
L
cm3
cm3
rrr
kg
9
9
The following units for the volume of decontamination agent applied to the surface (VolAppUn)
shown in Table 10 were converted to standard units. Note that some of the volumes were given
per area of the surface they were applied to. This was maintained as it was the desired unit, and
all other values were divided by their corresponding coupon area for consistency. Additionally,
the application methods "Foam Spray" and "Liquid Spray" gave a volume in mass.
Table 10: Converted Volume of Agent Applied Units
Original Units
Converted Units
uL
mL/cm2 or
L
mL/cm3
L/m2
mL/cm2
mL/m3
mL/cm3
9
g/cm2 or g/cm3
The following units for the initial coupon loading (LoadingUn) shown in Table 11 were
converted to standard units. Each value was then divided by the area of the coupon for those that
were not already in terms of area, volume, or mass. These same conversions were also performed
on the corresponding LposRec values as this column was assumed to have the same units.
37
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Table 11: Converted Loading Units
Original Units
Converted Units
CFU/mL
CFU/cm3
CFU/L
CFU/cm3
CFU
CFU/cm2 or CFU/cm3
log (CFU)
or
CFU/q
CFU/g
CFU/g
CFU/cm2
CFU/cm2
CFU/100cm2
CFU/cm2
A total of 31 unique units were provided for the concentration of decontamination agent applied
(ConcDoseUn). These were converted to standard units where possible, as illustrated by Table
12.
Table 12: Converted Concentration Dose Units
Original Units
Converted Units
kj
/
FAC ppm (FAC mg/L)
g/mL
mg/L
g/mL
W/m2
W /cm2
kW/m2
W/cm2
wt%
g/mL
uW/cm2
W /cm2
g/L
g/mL
mg tablet/L
g/mL
ppm
g/mL
J/cm2
J/cm2
% wt/vol
g/mL
ppmv
g/mL
mW/cm2
W /cm2
wt% NaOCl
g/mL
mj/cm2
J/cm2
mg/mL
g/mL
wt% (liquid applied)
g/mL
J/m2
J/cm2
maximum ppm
g/mL
g/m3
g/mL
wt% In wetting liquid
g/mL
While there were still quite a few disparate units found in ConcDose even after conversions were
performed, g/mL were the most common. The remaining units were dependent upon the
38
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application method. Table 13 lists the application methods and the respective unique ConcDose
units that applied to each.
Table 13: Unique Concentration Dose Units
Application Method
Unique ConcDose Units
Foam Spray
Aqueous Suspension
Liquid-Soaked Gauze Wipe
g/mL
Liquid-Soaked Gauze Covering
Aerosol
Liquid Wipe
J/cm2
Mrad
Gy
Physical
W/cm2
discharges (40A for 200nS)
W
W/cm3
bar
Fumigation
J
g/mL
Fogging
g/mL
mL
g/mL
Liquid Suspension
M
vol%
% available iodine
g/mL
Liquid Spray
M
vol%
Liquid Immersion
g/mL
M
Gel
vol%
Note that the Physical application method included a wide range of physical treatments,
including radiation and treatment with UV radiation. As such, this method accounted for most of
the disparate units. Also note that while / does not seem an appropriate unit for the Fumigation
application method, this unit was given in the compendium where the decontamination agent
applied was listed as plasma.
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3.5.1.5 Additional Calculations
Certain calculations were deemed necessary in order to create a full set of usable data for the
development of the efficacy model. Various columns were added to hold these new values, as
listed in Table 14.
Table 14: Columns Added to the BioDecontamination Compendium
Column Name
Description
Rep Surface
Representative surface based on the surface found in the compendium.
These representative surfaces are listed in Appendix A.
IndoorW alls
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for interior walls for the indoor
scenario. Surfaces were classified using the lookup tables in Appendix F.
IndoorCarpet
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for carpeted flooring for the indoor
scenario. Surfaces were classified using the lookup tables in Appendix F.
IndoorNonCarpet
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for non-carpeted flooring for the
indoor scenario. Surfaces were classified using the lookup tables in
Appendix F.
IndoorCeiling
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for ceilings for the indoor scenario.
Surfaces were classified using the lookup tables in Appendix F.
IndoorHVAC
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for HVAC and duct work for the
indoor scenario. Surfaces were classified using the lookup tables in
Appendix F.
IndoorMisc
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material found indoors but not already included
in the other categories for the indoor scenario. Surfaces were classified
using the lookup tables in Appendix F.
OutdoorExterior
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material found in exterior walls for the outdoor
scenario. Surfaces were classified using the lookup tables in Appendix G.
Roofing
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material found in roofing for the outdoor
scenario. Surfaces were classified using the lookup tables in Appendix G.
Pavement
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material found in outdoor flooring or pavement
for the outdoor scenario. Surfaces were classified using the lookup tables in
Appendix G.
Water
Holds a zero or one based on whether the representative surface in the
RepSurface column describes a body of water for the outdoor scenario.
Surfaces were classified using the lookup tables in Appendix G.
Soil
Holds a zero or one based on whether the representative surface in the
RepSurface column topsoil or vegetation for the outdoor scenario. Surfaces
were classified using the lookup tables in Appendix G.
40
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Column Name
Description
OutdoorMisc
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material found outdoors but not already included
in the other categories for the outdoor scenario. Surfaces were classified
using the lookup tables in Appendix G.
UndergroundWalls
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for interior walls for the
underground scenario. Surfaces were classified using the lookup tables in
Appendix H.
UndergroundCarpet
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for underground carpeted flooring
for the underground scenario. Surfaces were classified using the lookup
tables in Appendix H.
UndergroundNonCarpet
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for underground non-carpeted
flooring for the underground scenario. Surfaces were classified using the
lookup tables in Appendix H.
UndergroundCeiling
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for ceilings for the underground
scenario. Surfaces were classified using the lookup tables in Appendix H.
UndergroundHVAC
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material used for HVAC and duct work for the
underground scenario. Surfaces were classified using the lookup tables in
Appendix H.
UndergroundMisc
Holds a zero or one based on whether the representative surface in the
RepSurface column was a material found outdoors but not already included
in the other categories for the underground scenario. Surfaces were
classified using the lookup tables in Appendix H.
TotalApp
Total number of decontamination treatment applications. This column was
already calculated in the compendium; however, for some numerical values
within ReApp, the calculated TotalApp was NA which should not be the
case. Note that blank values and NA values within ReApp were replaced
with zeroes. This was done based on the assumption that at least one
treatment must be applied in order to decontaminate a surface with a given
decon method. If multiple treatments were not indicated, it was assumed
that at least one treatment was applied.
Nt
Number of spores recovered from the test coupon after treatment with a
decontamination agent. Values in this column were calculated differently
depending on the efficacy measure given.
Note that the Nt column calculation varied given the efficacy measure. The calculations used for
each efficacy measure are provided in Table 15.
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Table 15: Nt Calculations Based on EffMeas
EffMeas
Description
Equation
LR
Log reduction
Eff(LR) = LposRec -log(Nt)
Lsurv
Log of the spore survival count
Eff(LSurv) = log(Nt)
LsurvFrac
Log of the spore survival fraction
Eff (LSurvFrac) = log(Nt/Loading)
%Surv
Percent of spores that survive
treatment
Eff(%Surv) = (Nt/Loading) *100
%Kill
Percent of spores killed in treatment
Eff(%Kill) = (( Loading -Nt)/Loading)
*100
SurvFrac
Spore survival fraction
Eff {SurvFrac) = Nt/Loading
Finally, the efficacy measure SurvFrac describes the fraction of spores that are recovered from
the test coupon after decontamination given the initial loading of spores. Intuitively, this number
should be between zero and one. However, certain records provided values for SurvFrac that
were found to be unreasonably high. As such, all values greater than one were divided by 100
under the assumption that the value was given within the reference as a percentage rather than a
fraction.
3.5.2 Application Method Review
Upon completion of the BioDecontamination Compendium review, the application methods
found within the compendium were reviewed for their relevance to wide area scenarios as well
as the three scenario types to be considered within the model (i.e., indoor, outdoor, and
underground) based on subject matter expert (SME) determination. The following application
methods were deemed relevant to these scenarios and, thus, were included in the tool:
• Aerosol
• Foam Spray
• Fogging
• Fumigation
• Gel
• Liquid Immersion
• Liquid Spray
• Liquid Suspension
• Liquid Wipe
• Physical
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3.5.3 Application Method and Surface Type Combinations Review
The application method and surface type combinations included in the tool were also reviewed
by SMEs to identify which were valid for the three scenario types. Figure 7 lists all application
method and surface type combinations color-coded by their inclusion status. Green highlighted
cells indicate combinations that were found to be valid and were thus included in the tool. Black
highlighted cells indicate combinations that were included in the tool only for waste materials.
Red highlighted cells indicate combinations that had no underlying data in the compendium and,
thus, were not included in the tool. Finally, blue highlighted cells indicate combinations that
were deemed irrelevant and, thus, were not included in the tool.
Valid App Method + Surface Type Combinations
App Method + Surface Type Combinations Not Included in Compendium Data
Only Kept for Waste
Deemed Irrelevant and Not Included in the Tool
Figure 7: Reviewed Application Method and Surface Type Combinations
3.5.4 Bivariate Relationship Analysis
The development of the efficacy model began with an analysis of the bivariate relationships
within the BioDecontamination Compendium. Bivariate relationships are connections between
two parameters and an analysis of the connections that were present between efficacy and other
numerical factors was performed in order to identify those factors which had the greatest
influence on efficacy. This analysis facilitated the development of a guideline for predicting
efficacy based on the identified related factors. By determining the relationship between efficacy
and a given numerical parameter, the estimation of that parameter and application of the
appropriate relationship results in an estimated efficacy value. This analysis helped capture the
high amount of uncertainty associated with efficacy due to the sparsity of available data, the
myriad of factors that may change for decontamination and impact efficacy (e.g., temperature,
relative humidity), and the numerous decontamination application treatment methodologies. It
should be noted that for future iterations of the tool, a more rigorous multivariate analysis may
be beneficial to constructing the best possible efficacy model from the available data.
Three categorizations of Biodecon Compendium data were investigated: 1) application method,
2) surface type, and 3) application method and surface type. For each subset of data, Python
scripts were used to calculate a Pearson correlation coefficient r describing the strength of the
43
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linear relationship between efficacy in log reductions and each of the numerical columns found
in Table 16.
Table 16: Numerical Columns Included in the Bivariate Relationship Analysis
Numerical Columns Used for Analysis
Loading
H202
ContTime
ConcDose
VolApp
Rinsate
C102
Temp
TotalApp
MB
RH
A p-value (p) indicating the probability that an uncorrected dataset would produce a correlation
coefficient at least as extreme as the corresponding coefficient was also calculated for each
subset of data to describe the strength of the correlation coefficient.
Guidance on the breakdown of correlation coefficients and corresponding relationship strengths
was obtained from Statology.org12 as well as a paper by Diana Mindrila and Phoebe Balentyne
on scatterplots and correlations13 and is summarized in Table 17 below.
Table 17: Relationship Strength of Correlation Coefficients
Absolute Value of r12
Absolute Value of r13
Relationship Strength
r < 0.25
r < 0.30
No Relationship
0.25 0.75
r > 0.70
Strong Relationship
Despite discrepancies in the threshold between the moderate and strong relationship, the
threshold between the moderate and weak relationship was consistent. Based on this guidance,
the following threshold for r was defined in Equation 41 to include both moderate and strong
relationships:
\r\ > 0.50 (41)
A threshold for p was also determined, as illustrated by Equation 42. Guidance for this threshold
came from the Corporate Finance Institute stating that a p-value less than 0.01 is considered
highly statistically significant14.
p < 0.01 (42)
The combination of both thresholds ensured that only correlations which were moderate to
strong and statistically significant to 99% were considered when determining bivariate
44
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relationships between efficacy and other numerical parameters within the compendium. The
following datasets (application method or surface type) and subsets (application method and
surface type) listed in Table 18 were found to meet these thresholds.
Table 18: Compendium Datasets and Subsets Which Met r and p-value Thresholds
Application Method
Surface Type
Foam Spray
-
Liquid Suspension
-
Liquid Wipe
-
IndoorWalls
IndoorHVAC
Foam Spray
UndergroundHVAC
OutdoorExterior
Pavement
Roofing
IndoorHVAC
UndergroundHVAC
Fumigation
UndergroundNonCarpet
Roofing
IndoorNonCarpet
Physical
IndoorMisc
IndoorCeilings
IndoorCarpet
Liquid Immersion
IndoorMisc
OutdoorMisc
UndergroundCeilings
UndergroundCarpet
Table 19 below shows the datasets and subsets for which a strong correlation was found with
Loading, along with the sampled size of the set and the p-value corresponding to the correlation
coefficient.
45
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Table 19: Subsets with Strong Correlations with Loading
Dataset or Subset
r - Loading
Data Points
p-Value
Liquid Immersion and UndergroundCeilings
0.99
8
3.34E-06
Liquid Immersion and OutdoorMisc
0.50
62
3.16E-05
Foam Spray and Pavement
-0.97
5
5.41E-03
Foam Spray and Roofing
-0.97
5
5.41E-03
Foam Spray and OutdoorExterior
-0.90
11
1.70E-04
Liquid Immersion and IndoorMisc
0.53
30
2.68E-03
Liquid Immersion and IndoorCeilings
0.99
8
3.34E-06
Foam Spray and IndoorWalls
-0.90
11
1.70E-04
Table 20 below shows the datasets and subsets for which a strong correlation was found with
ConcDose, along with the sampled size of the set and the p-value corresponding to the
correlation coefficient.
Table 20: Subsets with Strong Correlations with ConcDose
Dataset or Subset
r - ConcDose
Data Points
p-Value
Foam Spray
0.87
55
9.31E-18
Liquid Immersion and IndoorMisc
0.64
30
1.29E-04
Fumigation and IndoorHVAC
-0.54
270
1.81E-21
Fumigation and UndergroundHVAC
-0.54
270
1.81E-21
Table 21 below shows the datasets and subsets for which a strong correlation was found with
H202, along with the sampled size of the set and the p-value corresponding to the correlation
coefficient.
Table 21: Subsets with Strong Correlations with H202
Dataset or Subset
r - H202
Data Points
p-Value
Fumigation and UndergroundNonCarpet
0.55
26
3.53E-03
Fumigation and Roofing
-0.88
12
1.81E-04
Fumigation and IndoorHVAC
0.78
22
2.03E-05
Fumigation and UndergroundHVAC
0.78
22
2.03E-05
Fumigation and IndoorNonCarpet
0.55
26
3.53E-03
Table 22 below shows the datasets and subsets for which a strong correlation was found with
Temp, along with the sampled size of the set and the p-value corresponding to the correlation
coefficient.
46
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Table 22: Subsets with Strong Correlations with Temp
Dataset or Subset
r - Temp
Data Points
p-Value
Foam Spray
0.66
52
1.08E-07
Liquid Suspension
0.54
1,402
1.22E-106
Liquid Immersion and UndergroundCarpet
-0.76
48
3.11E-10
Foam Spray and Pavement
0.97
5
5.41E-03
Foam Spray and Roofing
0.97
5
5.41E-03
Foam Spray and OutdoorExterior
0.89
11
2.47E-04
Foam Spray and IndoorHVAC
-0.99
5
1.37E-03
Foam Spray and UndergroundHVAC
-0.99
5
1.37E-03
Liquid Immersion and IndoorCarpet
-0.76
48
3.11E-10
Foam Spray and IndoorWalls
0.89
11
2.47E-04
Table 23 below shows the datasets and subsets for which a strong correlation was found with
RH, along with the sampled size of the set and the p-value corresponding to the correlation
coefficient.
Table 23: Subsets with Strong Correlations with RH
Dataset or Subset
r-RH
Data Points
p-Value
Foam Spray and OutdoorExterior
0.86
11
7.04E-04
Foam Spray and IndoorWalls
0.86
11
7.04E-04
Table 24 below shows the datasets and subsets for which a strong correlation was found with
ContTime, along with the sampled size of the set and the p-value corresponding to the
correlation coefficient.
Table 24: Subsets with Strong Correlations with ContTime
Dataset or Subset
r - ContTime
Data Points
p-Value
Liquid Wipe
-0.60
26
1.31E-03
Liquid Immersion and UndergroundCeilings
0.73
58
9.39E-11
Physical and IndoorMisc
0.71
17
1.51E-03
Liquid Immersion and IndoorCeilings
0.73
58
9.39E-11
A scatter plot was generated for each correlation of efficacy vs the given parameter. Each scatter
plot was then fit with a uniform x-dependent distribution. A uniform x-dependent distribution is
a uniform distribution generated from a maximum y-value and minimum y-value at a given x-
value. In order to fit this distribution to each scatter plot, the point with the highest corresponding
y-value and the point with the lowest corresponding y-value were chosen at each distinct x-value
on every plot. The red dotted line segments in Figure 8 indicate the maximum and minimum
boundary on the y-axis for each x-value. Note that the resulting minimum and maximum line
segments are monotonic, meaning each either increases or decreases but not both. Points for the
segments were chosen with this caveat.
47
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Foam Spray
00 01 02 0,3 04 0.5 06 07
ConcDose (g/mL)
Figure 8: Uniform X-Dependent Distribution for ConcDose and Efficacy for Foam Spray
For every x-value on the plot, a uniform distribution was created using the corresponding y-value
from the bottom-most line segment as the lower limit of the range (a), and the top-most line
segment as the upper limit of the range (b). This is demonstrated in Figure 9 below.
Foam Spray
00 01 0.2 0,3 04 05 06 0.7
ConcDose (g/mL)
Figure 9: Drawn a and b Values for Each X-Vaiue
The a and b values drawn from the scatter plot were then used to calculate the uniform
distribution using the following piecewise formula shown in Equation 43.
48
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1
/(x) = for a < x < b
b~a (43)
/(x) = 0 for x < a or x > b
As previously stated, scatter plots were generated for all datasets and subsets for which strong
correlations were found between efficacy and another numerical parameter. These plots can be
found in Appendix I.
3.5.5 Single Dimensional Uncertainty Analysis
Where there was a weak or no relationship between efficacy and other numerical parameters,
single dimensional uncertainty analysis (i.e., fitting a distribution to a histogram of efficacy for
different categorizations) was utilized to determine an adequate distribution to model efficacy at
a lower resolution. Since the efficacy model was parameterized by both application method and
surface type, histograms were first generated for efficacy in log reductions for each application
method. Based on the behavior of the histograms, further categorization was performed when
appropriate. For instance, when application method histograms indicated bimodality (two
means), additional histograms were generated for the application method and surface type in an
effort to produce a unimodal (one mean) histogram.
All histograms which indicated unimodality were fit with the following distributions:
• Beta
• Truncated Exponential
• Lognormal
• Truncated Normal
• Uniform
• Weibull Minimum
• Weibull Maximum
Each distribution was fit to the data using the built-in SciPy stats .fit method in Python and then
the distribution corresponding to the lowest AIC was subsequently fit to the data, as described in
Section 2.1.1. Additionally, all histograms which indicated bimodality were fit with bimodal
truncated normal distributions.
The Physical dataset, excluding IndoorMisc as this subset was already accounted for in the
bivariate relationship analysis, was fit with a lognormal distribution as shown in Figure 10.
49
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Physical
Efficacy -150 -
c
£ 100 -
50 ¦
0 l r-1 'l —i—
0 2 4 6 8
Efficacy (LR>
Figure 11: Bimodal Fumigation Efficacy Histogram
All Fumigation and surface type subsets that indicated unimodality were fit with appropriate
unimodal distributions and the data from these subsets was removed from the Fumigation
dataset.
50
-------
The Fumigation and IndoorCarpet subset was found to be unimodal and was fit with a beta
distribution as shown in Figure 12.
Efficacy (LR)
Figure 12: Histogram of Efficacy for Fumigation and IndoorCarpet
The Fumigation and IndoorCeilings subset was found to be unimodal and was fit with a beta
distribution as shown in Figure 13.
Efficacy (LR)
Figure 13: Histogram of Efficacy for Fumigation and IndoorCeilings
The Fumigation and IndoorMisc subset was found to be unimodal and was fit with a beta
distribution as shown in Figure 14.
51
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Efficacy (LR)
Figure 14: Histogram of Efficacy for Fumigation and IndoorMisc
The Fumigation and UndergroundCarpet subset was found to be unimodal and was fit with a
beta distribution as shown in Figure 15.
Efficacy (LR)
Figure 15: Histogram of Efficacy for Fumigation and UndergroundCarpet
The Fumigation and UndergroundCeilings subset was found to be unimodal and was fit with a
beta distribution as shown in Figure 16.
52
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Efficacy (LR)
Figure 16: Histogram of Efficacy for Fumigation and UndergroundCeilings
The subsets shown in Figure 12, Figure 13, Figure 14, Figure 15, and Figure 16 were removed
from the Fumigation dataset. The resulting dataset was still found to be bimodal and was fit with
a bimodal truncated normal distribution as shown in Figure 17.
Fumigation
Efficacy (LR)
Figure 17: Histogram of Efficacy for Fumigation
The Liquid Spray histogram shown in Figure 18 indicated bimodality. As such, an investigation
into the cause of this behavior indicated that various surface types combined with Liquid Spray
produced subsets possibly explaining the bimodality.
53
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Liquid Spray
140 •
120 -
* 100 "
LJ
I 80
S —I
60 ¦
40 ¦
20
0 — r* *—i —i —
0 2 4 6 8
Efficacy (LR)
Figure 18: Bimodal Liquid Spray Efficacy Histogram
The Liquid Spray and Roofing subset was found to be unimodal and was fit with a beta
distribution as shown in Figure 19.
Efficacy (LR)
Figure 19: Histogram of Efficacy for Liquid Spray and Roofing
The subset shown in Figure 19 was removed from the Liquid Spray dataset. The resulting dataset
was still found to be bimodal and was fit with a bimodal truncated normal distribution as shown
in Figure 20.
54
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Efficacy fLR)
Figure 20: Histogram of Efficacy for Liquid Spray
The Liquid Immersion histogram indicated bimodality. As such, an investigation into the cause
of this behavior indicated that the bimodality was not caused by any one factor but rather may be
the consequence of multiple confounding factors within the data. Therefore, this dataset was left
as-is and was fit with a bimodal truncated normal distribution as shown in Figure 21.
Efficacy (LR)
Figure 21: Histogram of Efficacy for Liquid Immersion
The Gel dataset was fit with a Weibull minimum distribution as shown in Figure 22.
55
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Gel
Efficacy (LR)
Figure 22: Histogram of Efficacy for Gel
The Aerosol dataset was fit with a beta distribution as shown in Figure 23.
Aerosol
Efficacy (LR)
Figure 23: Histogram of Efficacy for Aerosol
The Fogging dataset was fit with a beta distribution as shown in Figure 24.
56
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Fogging
14 -
12 -
10 -
£
£ 08
ru
a
o
£ 0.6 ¦
0 4 ¦
0.2 -
0.0 ' I I I I I
5.0 5.5 6.0 6.5 7.0 7.5
Efficacy (LR)
Figure 24: Histogram of Efficacy for Fogging
3.5.6 Creating a Single Model
The Efficacy model calculates a specific value for efficacy based on the application method and
surface type combination that the user chooses and the corresponding distribution that has been
applied to that subset. The grid in Figure 25 shows the possible combinations of application
method and surface type which the user can choose. The cells highlighted orange represent the
combinations for which efficacy is determined based on the bivariate relationship defined. The
cells highlighted green represent the combinations for which efficacy is drawn from a
distribution fit to the corresponding application method dataset. Finally, the cells highlighted
blue represent the combinations for which efficacy is drawn from a distribution fit to the
corresponding application method and surface type subset.
57
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Bivariate Relationship
Distribution Fit to the Application Method Dataset
Distribution Fit to the Application Method and Surface Type Subset
Figure 25: Efficacy Model Categorizations Grid
3.5.7 Efficacy Model Parameters
The Efficacy model includes various parameters which help fully define the treatment of
surfaces for the DC model. These parameters are listed in Table 25.
Table 25: Efficacy Model Parameters
Parameter
Name
Description
Units
PrehsTi
Previous Spore Loading
Spore loading on each surface type after
any number of decontamination
treatments
CFU
AMsti
Application Method for
Surface Type
The application method required to
decontaminate each corresponding
surface type
application
method
DCdam
Decontamination Days for
Application Method
Number of days required to fully treat a
given surface(s) with one application
method, including drying days, for each
application method
days
3.5.8 Efficacy Model
When an efficacy value (EffSTi) is drawn from the appropriate distribution based on the
application method and surface type, Equation 44 is used to determine the remaining spore
loading on each surface based on that reduction in spores.
PostLSTi = PreLSTi — EffST. (44)
Where:
• PreLSTi = Previous spore loading on each surface type i
58
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The number of treatments of each application method i (TQ) is determined by the number of
times Equation 44 is needed in order to reduce the spore count present on each surface type to
the desired spore threshold on each surface type i.
The parameter PDw is calculated in the Efficacy Model using Equation 45 below.
Pow ~ X
(45)
Where the workdays per application method, or Pdam, is calculated using Equation 46.
PDam = max(TQ.)*DCDjlM
(46)
Where:
• max
{tq = tbe max number of treatments for a given application method
DCDam = Number of days required for one treatment by application method (including drying
days)
3.6 Decontamination
DC is the process of reducing any contaminants to a safe level. The methods of removal and
threshold for safety are dependent on the input scenario parameters. The decontamination
element relies on the Efficacy Model to predict how effective a specific decontamination
application method will be when applied to a given surface. The following sections list the
parameters relevant to the DC model as well as the calculations performed to characterize the
cost and resource demands of this element. Note that certain Efficacy Model parameters are used
in the following DC calculations to fully define the costs associated with the DC element.
3.6.1 Decontamination Parameters
The DC model parameters are listed in Table 26 below. Note that this table only includes user-
input and baseline parameters. All calculated quantities are explained in detail in the subsequent
section.
59
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Table 26: DC Model Parameters
Parameter
Name
Description
Units
DC am
Number of Days for One
Treatment of Application
Method
Days required to apply one treatment of
each application method (includes drying
days)
days
To
Number of Teams
Number of teams required for element
teams
K
Personnel Required
Number of personnel of each type
required for one team (OSC, PL-1, PL-2,
PL-3, PL-4)
personnel
Pdo
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
RP
Number of Respirators Per
Person
Number of respirators per one person
respirators /
person
eppetean
PPE Fraction Per Team
Fraction of total PPE that is each level for
one team (Level A, Level B, Level C,
Level D)
unitless
Ed
Entry Duration
Entry durations based on PPE levels
hours / entry *
team
EP
Entry Preparation Time
Time required for preparation into the
contaminated site area
hours / entry *
team
Edc
Decontamination Line
Time
Time required for decontamination of
personnel upon exiting the contaminated
site area
hours / entry *
team
Er
Post-Entry Rest Period
Time required for rest period upon
exiting the contaminated site area
hours / entry *
team
Rv
Volume of Room
Volume of contamination site area or
room
m3
SAs
Room Surface Area
Surface area of the contamination site or
room
m2
VF
Volume of Agent
(Fogging/Fumigation)
Volume of decontamination agent needed
for Fogging or Fumigation for one cubic
meter of contamination site area
mL / m3
Vam
Volume of Agent (Other)
Volume of decontamination agent needed
for all other application methods for one
square meter of each surface
ml / m2
Cda
Cost of Decontamination
Agent
Cost per volume of decontamination
agent
$ / mL
Cr
Cost Per Respirator
Cost per one respirator
$ / respirator
Ceppe
Cost Per Individual PPE
Cost per one unit of PPE of each level
$ / PPE level
CEp
Entry Preparation Cost
Cost associated with preparation before
entering the site area
$ / entry *
team
Cedc
Decontamination Line Cost
Cost associated with the personnel decon
line
$ / entry *
team
C*Q
Cost of Decontamination
Materials
Cost of decontamination supplies and
equipment per surface area of
contamination site
$ / m2
Personnel Hourly Rate
Hourly wage of each personnel type
(OSC, PL-1, PL-2, PL-3, PL-4)
$/hour
60
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3.6.2 Decontamination Model
The overall cost of DC is broken down into three primary costs of equal weight: 1) cost of labor
(CL), 2) cost associated with entering and exiting the contaminated area (CE), and 3) cost of
supplies and rentals (Cs). The cost of labor for DC is calculated using Equation 47 below.
Q, = Ph * Tq * (]*q " ^p) (47)
Where:
• PM - Total DC labor hours
• Tq = Number of teams required for DC
• Pq = Number of personnel required per team by personnel type
• Cp = Personnel hourly rate by personnel type
The parameter PH is calculated using Equation 48 below.
PH= 12 * PD <48)
Where the personnel onsite days, or Pddc, is calculated using Equation 49.
PDdc = pw + PD0 (49)
Where:
• Pw = Total workdays (calculated in the Efficacy Model)
• Pd0 = Personnel overhead days
The cost associated with entering and exiting the contamination site for DC is calculated using
the same equations as are used in the calculation of entrance and exit cost for CS. See Equations
23-26 for the appropriate calculations. However, note that no entrances are made for the fogging
or fumigation decontamination methods and the total time used within the entrance and exit cost
calculation is adjusted to include only non-fogging and non-fumigation treatment methods.
The cost of supplies for DC is calculated using Equation 50 below.
61
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cs - (csQ * SAs) + {DAqp + Dj4i?am) Coa
(50)
Where:
• CSq = Cost of DC materials (supplies and equipment), per surface area of contamination
site
• Si45 = Site or room surface area
• DAqf = Volume of decon agent needed per room for fogging or fumigation for one
treatment
• DAq am = Volume of decon agent needed per room for one application method for one
treatment (excluding fogging and fumigation)
• CDA = Cost of decontamination agent per gallon
The parameter DAQp is calculated using Equation 51 below.
• Rv = Volume of room
• VF = Volume of decon agent applied for fogging or fumigation for one treatment per
cubic meter of room
Note that DAq p may be zero if fogging or fumigation were not performed.
The parameter DAqam is calculated using Equation 52 below.
• Rst - Percentage breakdown of room by surface type (only for the surfaces that do not
require fogging or fumigation)
DAq^ — Ry * Vp
(51)
Where:
(52)
Where:
62
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* Vam = Volurne of decon agent applied for one application method for each surface type
(excluding fogging and fumigation) for one treatment per square foot of surface
• At = Total surface area of the contamination site
Note that DAqam may be zero if only fogging or fumigation were performed.
CL. CE, and Cs combine to give the overall cost of DC (CDC), as illustrated by Equation 53 below.
Cdc — Cl + CE + Cs (53)
3.7 Clearance Sampling
CL is required to determine the level of contamination which is present at the contamination site
following each round of decontamination. This information is then used to determine additional
decontamination applications are necessary. The following sections list the parameters relevant
to the CL model as well as the calculations performed to characterize the cost and resource
demands of this element.
3.7.1 Clearance Sampling Parameters
The CL model parameters are listed in Table 27 below. Note that this table only includes user-
input and baseline parameters. All calculated quantities are explained in detail in the subsequent
section.
Table 27: CL Model Parameters
Parameter
Name
Description
Units
Total Surface Area
Total surface area of the site
m2
As
Fraction of Surface Area to
be Sampled
Fraction of the total surface area that will
be sampled
unitless
WA
Surface Area Per Sponge
stick
Surface area which can be sampled by
one sponge stick
m l sample
Ha
Surface Area Per 37 mm
Cassette
Surface area which can be sampled by
one 37 mm cassette
rri / sample
W„
Quantity of Sponge Sticks
Used Per Hour Per Team
Number of sponge sticks used for
sampling per hour per team
samples / hour
* team
H H
Quantity of 37 mm
Cassettes Used Per Hour
Per Team
Number of 37 mm cassettes used for
sampling per hour per team
samples / hour
* team
Entry Duration
Entry durations based on PPE levels
hours / entry *
team
EP
Entry Preparation Time
Time required for preparation into the
contaminated site area
hours / entry *
team
63
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Parameter
Name
Description
Units
Edc
Decontamination Line
Time
Time required for decontamination of
personnel upon exiting the contaminated
site area
hours / entry *
team
Er
Post-Entry Rest Period
Time required for rest period upon
exiting the contaminated site area
hours / entry *
team
RP
Number of Respirators Per
Person
Number of respirators per one person
respirators /
person
To
Number of Teams
Number of teams required for element
teams
pq
Personnel Required
Number of personnel of each type
required for one team (OSC, PL-1, PL-2,
PL-3, PL-4)
personnel
Pdo
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
Fraction of total PPE that is each level
EPPEteAM
PPE Fraction Per Team
for one team (Level A, Level B, Level C,
unitless
LevelD)
Labq
Number of Analysis Labs
Number of external labs to which
samples are sent for analysis
labs
Ld
Distance from
Distance of external lab from
km
Contamination Site
contamination site
Lr
Lab Throughput Per Day
Number of samples analyzed per day
samples / day
Tr
Time for Result
Transmission to IC
Time for sampling analysis results to be
sent from external labs to Incident
hours
Command
Tps
Time for One Sample to be
Packaged
Time for one sample to be packaged for
shipment to an external analysis lab
minutes /
sample
CEp
Entry Preparation Cost
Cost associated with preparation before
entering the site area
$ / entry *
team
CEDC
Decontamination Line Cost
Cost associated with the personnel decon
line
$ / entry *
team
CWA
Costs Per Sponge Stick
Sample
Analysis costs per one sponge stick
sample
$ / sample
cha
Costs Per 37 mm Sample
Analysis costs per one 37 mm cassette
sample
$ / sample
Cr
Cost Per Respirator
Cost per one respirator
$ / respirator
Ceppe
Cost Per Individual PPE
Cost per one unit of PPE of each level
$ / PPE level
cw
Cost Per Sponge Stick
Cost to purchase one sponge stick
$ / sample
CH
Cost Per 37 mm Cassette
Cost to purchase one 37 mm cassette
$ / sample
chd
37 mm Vacuum Rental
Cost Per Day
Cost of 37 mm vacuum rental per day
$ / day
tp
Personnel Hourly Rate
Hourly wage of each personnel type
(OSC, PL-1, PL-2, PL-3, PL-4)
$/hour
3.7.2 Clearance Sampling Model
Clearance Sampling is performed after each round of decontamination is performed in order to
characterize the amount of contaminant present on surfaces and to determine if additional rounds
64
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of decontamination are required. The Wide-Area Decontamination Tool calculated cost and time
results for Clearance Sampling using the same model used to calculate the cost and time of
Characterization Sampling. For these calculations, refer to Section 3.3.2.
3.8 Waste Sampling
WS is required to determine the level of contamination which is present in the waste that will be
removed from the contamination site and disposed of. This information is used to determine
whether waste acceptance criteria (usually established by the state decision makers and the
receiving treatment/disposal facility) have been met, as certain safety precautions are necessary
in order to dispose of biohazardous waste. The following sections list the parameters relevant to
the WS model as well as the calculations performed to characterize the cost and resource
demands of this element.
3.8.1 Waste Sampling Parameters
The WS model parameters are listed in Table 28 below. Note that this table only includes user-
input and baseline parameters. All calculated quantities are explained in detail in the subsequent
section.
Table 28: WS Model Parameters
Parameter
Name
Description
Units
i4 j1
Total Surface Area
Total surface area of the site
m2
/i
Fraction of Waste to be
Fraction of the total waste that will be
unitless
Aw
Sampled
sampled
SA
Mass Per Solid Waste
Sample
Mass of waste which can be sampled by
one solid waste sample
m2/ sample
La
Volume Per Liquid Waste
Sample
Volume of waste which can be sampled
by one liquid waste sample
m2/ sample
W„
Quantity of Waste Samples
Used Per Hour Per Team
Number of waste samples used for
sampling per hour per team
samples / hour
* team
Ws
Solid Waste Per Surface
Area
Total solid waste produced per surface
area of site
kg / m2
WL
Liquid Waste Per Surface
Area
Total liquid waste produced per surface
area of site
L/m2
Ed
Entry Duration
Entry durations based on PPE levels
hours / entry *
team
EP
Entry Preparation Time
Time required for preparation into the
contaminated site area
hours / entry *
team
Edc
Decontamination Line
Time
Time required for decontamination of
personnel upon exiting the contaminated
site area
hours / entry *
team
Er
Post-Entry Rest Period
Time required for rest period upon
exiting the contaminated site area
hours / entry *
team
RP
Number of Respirators Per
Person
Number of respirators per one person
respirators /
person
65
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Parameter
Name
Description
Units
To
Number of Teams
Number of teams required for element
teams
Pq
Personnel Required
Number of personnel of each type
required for one team (OSC, PL-1, PL-2,
PL-3, PL-4)
personnel
Pdo
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
Fraction of total PPE that is each level
Eppeteam
PPE Fraction Per Team
for one team (Level A, Level B, Level C,
Level D)
unitless
Labq
Number of Analysis Labs
Number of external labs to which
samples are sent for analysis
labs
io
Distance from
Distance of external lab from
km
Contamination Site
contamination site
If
Lab Throughput Per Day
Number of samples analyzed per day
samples / day
Tr
Time for Result
Transmission to IC
Time for sampling analysis results to be
sent from external labs to Incident
hours
Command
Tps
Time for One Sample to be
Packaged
Time for one sample to be packaged for
shipment to an external analysis lab
minutes /
sample
CEp
Entry Preparation Cost
Cost associated with preparation before
entering the site area
$ / entry *
team
^Edc
Decontamination Line
Cost
Cost associated with the personnel decon
line
$ / entry *
team
CsA
Costs Per Solid Waste
Sample
Analysis costs per one solid waste
sample
$ / sample
CLa
Costs Per Liquid Waste
Sample
Analysis costs per one liquid waste
sample
$ / sample
Cr
Cost Per Respirator
Cost per one respirator
$ / respirator
Ceppe
Cost Per Individual PPE
Cost per one unit of PPE of each level
$ / PPE level
cw
Cost Per Waste Sample
Cost to purchase one waste sample
$ / sample
Cp
Personnel Hourly Rate
Hourly wage of each personnel type
(OSC, PL-1, PL-2, PL-3, PL-4)
$/hour
3.8.2 Waste Sampling Model
Waste Sampling is performed after each round of decontamination is performed in order to
characterize the amount of contaminant present on the resulting waste. The Wide-Area
Decontamination Tool calculated cost and time results for Waste Sampling using the following
model.
The overall cost of WS is broken down into four primary costs of equal weight: 1) cost of labor
(CL), 2) cost of supplies and rentals (Cs), 3) cost associated with entering and exiting the
contamination area (CE), and 4) cost of sample analysis, including shipping and packaging (CA).
The cost of labor for WS is calculated using Equation 54 below.
66
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Where:
* PH = Total WS labor hours
* Pc; = Number of personnel required per team by personnel type
* Cp = Personnel hourly rate by personnel type
* Tq = Number of teams required for WS
The parameter PH is calculated using Equation 55 below.
Where the personnel onsite days, or Puws, is calculated using Equation 56.
• PDW = Total workdays
• Pd0 = Personnel overhead days
The parameter PDl is calculated using Equation 57 below.
Where:
• Sq = The total number of solid waste samples
• Lq = The total number of liquid waste samples
• WH = The quantity of waste samples used per hour per team
PH — 12 * Pdws
1 DWS ' 1 D W '* D o
Where:
67
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• Tq = The number of sampling teams required
The parameter SQ is calculated using Equation 58 below. Note that the total area sampled is
evenly split among the sample types.
VKc * At *
5?= 2.S. <58)
Where:
• Ws = The mass of solid waste produced per surface area
• At = The total surface area of the contamination site
• Aw = The fraction of the total waste produced that will be sampled
• = The mass of solid waste which can be sampled using one waste sample
The parameter LQ is calculated using Equation 59 below.
Wj * At * A\\t
L*=-LrkrL <59)
Where:
• WL = The volume of liquid waste produced per surface area
• La = The volume of liquid waste which can be sampled using one waste sample
The cost of supplies for WS is calculated using Equation 60 below.
Cs = (Sq + Lq) * Cw (60)
Where:
• Cw = Cost per one waste sample
A lag time due to time spent analyzing samples at external labs (TLAG) is also calculated for the
WS element. TLAG is calculated using Equation 61 below.
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^LAG — l? + max(^ii) "f" Tr
(61)
Where:
• TP = Total packaging time for all samples
• TLi = Total time samples spent at lab for each external lab i
• Tr = Time for completed sample result to be transmitted to IC
The parameter TP is calculated using Equation 62 below.
_ tps ~ *-
-------
Where:
• Labq = Number of external labs to which samples are sent for analysis
• Lt = Lab throughput for each external lab i
Note that an equal number of solid and liquid waste samples are sent to each external lab for
analysis.
The cost associated with entering and exiting the contamination site for WS is calculated using
the same equations as are used in the calculation of entrance and exit costs for CS. See Equations
27-33 for the appropriate calculations.
The cost of sample analysis for WS is calculated using Equation 65 below.
C* = (I« * CSJ + (le . CLJ <65>
Where:
• CSa, CLa = Cost of one solid waste sample or liquid waste sample for analysis,
respectively
CL, Cs, CE, and CA combine to give the overall cost of WS (Cws), as illustrated by Equation 66
below.
Cws = CL + Cs + CE + CA (66)
3.9 Travel
While not an element itself, the Wide-Area Decontamination Tool also considers additional cost
and time associated with travel to and from the site area after all calculations have been
performed for the indoor, outdoor, and underground scenarios. The following sections list the
parameters relevant to the various travel and lodging considerations that are not included in any
other element as well as the calculations performed to characterize the cost and resource
demands of these additional considerations.
3.9.1 Travel Parameters
The parameters related to the various travel and lodging considerations are listed in Table 29
below. Note that this table only includes user-input and baseline parameters. All calculated
quantities are explained in detail in the subsequent section.
70
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Table 29: Transportation and Miscellaneous Considerations Parameters
Parameter
Name
Description
Units
CARp
Number of Personnel Per
Rental Car
Number of personnel per one rental car
personnel
PQlC
Personnel Required (IC)
Number of personnel of each type
required for IC team only (OSC, PL-1,
PL-2, PL-3, PL-4)
personnel
pQcs
Personnel Required (CS)
Number of personnel of each type
required for one CS team only (OSC,
PL-1, PL-2, PL-3, PL-4)
personnel
pQsr
Personnel Required (SR)
Number of personnel of each type
required for one SRteam only (OSC,
PL-1, PL-2, PL-3, PL-4)
personnel
pQdc
Personnel Required (DC)
Number of personnel of each type
required for one DC team only (OSC,
PL-1, PL-2, PL-3, PL-4)
personnel
p0ws
Personnel Required (WS)
Number of personnel of each type
required for one WS team only (OSC,
PL-1, PL-2, PL-3, PL-4)
personnel
TQ rs
Number of Teams (CS)
Number of teams required for CS
teams
TQsr
Number of Teams (SR)
Number of teams required for SR
teams
TQnr
Number of Teams (DC)
Number of teams required for DC
teams
tqw<
Number of Teams (WS)
Number of teams required for WS
teams
PRTjC
Personnel Roundtrip Days
(IC)
Number of travel days both to and from
site for IC teams only
days
PrTcs
Personnel Roundtrip Days
(CS)
Number of travel days both to and from
site for CS teams only
days
PRTsr
Personnel Roundtrip Days
(SR)
Number of travel days both to and from
site for SR teams only
days
PrTdc
Personnel Roundtrip Days
(DC)
Number of travel days both to and from
site for DC teams only
days
PRTwS
Personnel Roundtrip Days
(WS)
Number of travel days both to and from
site for WS teams only
days
C CAR
Cost of Rental Car Per
Day
Cost of one rental car per one day
$ / day
CTK
Cost of Roundtrip Ticket
Per Person
Cost of one roundtrip ticket per one
person
$ / ticket *
person
CDpn
Per Diem Cost
Allowed per diem cost
$ / day
3.9.2 Travel Model
The travel model consists of airfare for a specified number of travel days, rental car costs for a
specified number of travel days, and per diem and lodging costs for the duration of the event (for
IC teams) or the corresponding element (for all other teams which are only onsite while needed).
The total travel cost is calculated using Equation 67.
71
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Ct CTjc + ^Tcs CTSR ^TDC + CT\vs
(67)
The cost of travel for IC (CT[C) is calculated using Equation 68.
CTlC = CPlC + CAlC + CRlC (68)
Where the cost of per diem and lodging for IC (CPlc) is calculated using Equation 69.
Cpic~ (/\ ^Qici) * ^Dic* ^°pd
Where:
• PQic = The total number of IC personnel available by type i
= The total number of onsite days for IC teams
• (-Dpi) = The cost of per diem and lodging for one day
The cost of airfare for IC (C/1/c) is calculated using Equation 70.
CAlC ~ (XP
-------
• PRTlC = The number of roundtrip travel days for IC teams
• CCAR = The cost of one rental car for one day
The cost of travel for CS (CTcs) is calculated using Equation 72
C'l'cs ~ CPCS + ('Acs Crcs (72)
Where the cost of per diem and lodging for CS (CPcs) is calculated using Equation 73.
= <73>
Where:
• = The total number of CS personnel available by type i
v CS
• r0 = The total number of CS teams
v CS
• PdCs= total number of onsite days for CS teams
The cost of airfare for CS (CAcs) is calculated using Equation 74.
CAcs = * Tqc5 * Ctk (74)
The cost of rental cars for CS (CjRrs.) is calculated using Equation 75.
(EO*7^ „ „ (75)
Cacs ~~ CAR~-, * PrTcs * CcA*
WThere:
• Prtcs = number of roundtrip travel days for CS teams
The cost of travel for SR. (£Tsr), DC (CToc), and WS (CTws) are each calculated using the same
equations as are used to calculate the cost of travel for CS. Refer to Equations 72-75 for the
appropriate calculations.
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3.10 Model Assumptions
Several assumptions were made within the Wide-Area Decontamination Tool in order to
simplify the scenarios being modeled and the processes being performed throughout the
decontamination incident. These assumptions include the following:
• Fixed Team Sizes
• Application of Multiple Decontamination Methods to the Same Area
• Multiple Sample Analysis Labs
Each of these assumptions is explained in detail in the subsequent sections below.
3.10.1 Fixed Team Sizes
For an individual building, each element may have multiple teams which carry out the processes
required for that element (e.g., characterization sampling teams, source reduction teams,
decontamination teams). It was assumed that for a given element, the size of each team was fixed
(i.e., each characterization sampling team had the same number of members for building one).
Note that the team sizes for equivalent elements between buildings could be different. Figure 26
shows the makeup of personnel per one team for each element as well as the number of teams for
each element as reported in U.S. EPA's BOTE report and Figure 27 shows equivalent data from
U.S. EPA's UTR OTD report.
74
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4J
TJ
C
m
E
E
a
U
8
EMT
H
st
w
s!
m
St
£
H
£
3
~-
3
H
Hon Team
Oof Teams
Folks
Labor Rates($/hr Loaded)
$147
$ 58
$86
$102
$124
$170
$66
$79
$88
Sampling Team
0.33
3.00
3.3
6
20.0
Decontamination Team (Level C)
0.33
2.33
0.67
3.3
3
10.0
Removal Team (Level B)
0.33
3.33
0.67
4.3
3
13.0
Removal Team (Level C)
0.33
2.33
0.67
3.3
3
10.0
Decontamination Team (Level B)
0.33
3.33
0.67
4.3
3
13.0
Decon Line Setup Te3m
2.00
2.0
1
2.0
Decon Line Ops Team
1.00
1.00
3.00
5.0
1
SO
Instrumentation Team
0.50
4.00
4.5
1
4.5
Sample Packaging Team
1.00
1.00
1.00
3.0
1
3.0
Waste Handling Team
1.00
3.00
4.0
1
4.0
Figure 26: Team Makeup and Number of Teams for Each Element7
t_
¦
?
E
E
E
(/i
E
s
QJ
K
O)
K
(A
a
?
H
3
m
H
3
m
C
O
O
£
o
UJ
Q.
a
a
a.
>-
i-
i-
at
tc
u.
Labor Rates ($/hr Loaded)
$155
$61
$101
$118
$142
$210
$71
$81
$101
Sampling Team
0.3
3.0
3.3
6
20.0
Decontamination Team (Level C)
0.3
3.0
1.0
4.3
1
4.3
Decontamination Team (Level A)
0.3
6.0
2.0
8.3
1
8.3
Decon Line Setup Team
2.0
2.0
1
2.0
Decon Line Ops Team
0.3
1.0
3.0
4.3
1
4.3
Sample Packaging Team
1.0
1.0
1.0
3.0
1
3.0
Figure 27: Team Makeup and Number of Teams for Each Element8
3.10.2 Application of Multiple Decontamination Methods to the Same Area
It was assumed that one decontamination application method would be fully applied to all
applicable surfaces and allowed to dry before another method would then be applied to any
remaining surfaces. Not all application methods are suitable for every surface type. As such,
different surfaces may require different application methods. If two or more application methods
were required to decontaminate every available surface, one treatment of each method was
applied at a time and was allowed to fully dry before treatment with another method began. A
single round of decontamination ended after one treatment of each necessary application method
had been applied to each surface type.
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3.10.3 Multiple Sample Analysis Labs
It was assumed that the number of samples sent to each analysis lab is fixed and that the same
number of samples would be sent to each external analysis lab. Although text within the UTR
OTD report indicated that a variable number of samples were sent to each external lab, this was
done for simplicity.
4 FUTURE IMPROVEMENTS
This report outlines the initial development of the Wide-Area Decontamination Tool. While it
captures the essentials of a wide-area incident, future improvements can be made to better define
and calculate the costs associated with the incident. Future efforts to further develop this model
should include the following:
• Currently, indoor, outdoor, and underground scenarios can be modeled in the tool.
However, the outdoor scenario model has significantly less supporting detail behind it as
a resource similar to the BOTE or UTR OTD field studies could not be found for outdoor
events. A similar resource should be identified to support the validity of the outdoor
scenarios modeled within the tool.
• The model currently allows for only traditional sampling types, such as sponge sticks and
37 mm cassettes, to be performed. However, EPA expressed interest in the ability to
model the use of non-traditional sampling types, such as robotic household vacuum-type
sampling and wet vac sampling, as well as air sampling. As such, data for these sampling
types should be added to the baseline workbook and should be made available as
sampling types within the model.
• Currently, decontamination supplies, equipment, and rental costs are fixed estimates for
all decontamination application methods. However, there are notable discrepancies
between these costs depending on the application method used. For example, tenting is
required for fumigation while it is not required for aerosol spraying. This would add an
additional supplies cost when fumigation is performed. As such, higher resolution data
regarding the cost of supplies, equipment, and rentals for each application method should
be compiled and added to the baseline workbook.
• Currently, for scenarios involving only one building, CS, SR, DC, CL, and WS are
performed sequentially. Each element is completed fully before the next element began.
The current model applies this same functionality to scenarios with multiple buildings.
However, for a scenario involving multiple buildings, model changes should be
implemented such that the pre-decontamination CS element would be performed on all
buildings first, followed by the SR, DC, CL, and WS elements consecutively one
building at a time.
• Currently, the model simulates the CS and CL elements by implementing basic
calculations that determine the shipment time of samples to external labs and the analysis
time of these samples. However, the CS and CL models should be modified to use a
76
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Stock and Flow model to better simulate the movement of samples, from shipment to
external labs to analysis time.
• Currently, there is no functionality within the model to account for additional safety or
support teams that may be required to survey the site after decontamination or support
sampling efforts. As such, functionality should be added to allow the user to specify any
additional teams required for the decontamination process.
• Currently, the model only allows PPE units to be used once, assuming PPE (other than
respirators) is discarded after only one use. However, model changes should be
implemented to allow the user to designate the number of uses for each PPE unit. PPE
would be discarded after this number of uses. Further, the model should also be modified
to allow PPE units to be "cleaned" after the specified number of uses and added back into
the stockpile of new PPE units. This will reduce the number of units needed for the
decontamination incident and, thus, reduce the overall cost associated with PPE for the
incident. Both the reuse and cleaning of PPE units could offer users an easy comparison
of how each might reduce the overall cost of resources required for the remediation
effort.
• Currently, there is no functionality within the model to queue buildings based on
personnel availability and buildings are treated sequentially, one after the other.
However, functionality should be implemented such that buildings with the largest
surface area are prioritized for decontamination when there are not enough personnel
available for simultaneous decontamination of all buildings. Geospatial data should also
be utilized to determine building populations for the contaminated site areas so that
buildings with larger populations can be prioritized for decontamination. In the event that
there were an inadequate number of personnel available to decontaminate multiple
buildings simultaneously, a priority queue was created.
5 CASE STUDIES
Two real-world examples of biological incidents were used as data inputs into the Wide-Area
Decontamination Tool in order to evaluate the validity of the tool: 1) The BOTE Project, and 2)
The UTR OTD. Following the conclusion of both mock decontamination events, a report was
generated for each summarizing the various scenario details and conditions specific to that effort.
A detailed cost and time analysis was also included in each report. The BOTE and UTR OTD
projects were chosen as verification cases for the Wide-Area Decontamination Tool since
sufficient data from each report could be identified and used to define each scenario within the
tool. Additionally, the existing cost and time analyses could be easily compared with model
results.
Both incidents were recreated within the tool and the resulting cost and resource estimates were
compared to those defined in the literature documenting these incidents, facilitating the
assessment of the tool's performance. The following sections detail the incidents used as case
studies, the data pulled from the incidents and used within the model, and the results in
comparison with what was observed during the mock incidences.
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5.1 Case 1
5.1.1 Approach
The BOTE Project report details a comprehensive investigation into the decontamination of a
biological agent in a mock indoor scenario. For details about the BOTE project, refer to Section
2.2.1. Table 30 shows the cost results from the BOTE report that were used to validate the
resulting cost estimates calculated by the tool. Note that Clearance Sampling was not included as
an individual value within the BOTE report. As such, this element was combined here into the
CS results.
Table 30: BOTE Cost Results
Cost Results
Result Name
Value
Characterization Sampling Cost
$618,085 -$621,934
Source Reduction Cost
$30,497
Decontamination Cost
$109,943 -$172,112
Waste Sampling Cost
$5,096-$124,218
Incident Command Cost
$46,737 - $54,907
Total Cost of Effort
$774,765 -$887,915
Table 31 shows the time results from the BOTE report that were used to validate the resulting
time estimates calculated by the tool.
Table 31: BOTE Time Results
Time Results
Result Name
Value
Characterization Sampling Workdays
4
Characterization Sampling Onsite Days
4
Source Reduction Workdays
2
Source Reduction Onsite Days
2
Decontamination Workdays
3-5
Decontamination Onsite Days
3-5
Waste Sampling Workdays
*Included in CS
Waste Sampling Onsite Days
*Included in CS
Incident Command Onsite Days
9-11
Numerous model tests were performed, each run with 10,000 realizations to allow sampling to
account for all uncertainty within the parameters. Results were averaged over all realizations.
Changes were made to the model between each test to address any shortcomings of the model.
The input values used for the BOTE verification case can be found in Appendix J. Single values
were input as constants, ranges of values were input as a uniform distribution between the
minimum and maximum values identified, and any values with a distribution specified in the text
78
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were input accordingly. Additionally, some values were estimated or calculated based on
contextual information found in the source and surrogate values were used when a value could
not be found in the respective text. The WADE tool was used as a source for surrogate values
wherever information could not be obtained from either project report.
The BOTE facility consisted of one building with different room compositions throughout to
simulate commercial, industrial, and residential spaces. In the initial model verification runs, this
was input into the model as three individual buildings of each type (commercial, industrial, and
residential). However, certain processes which happened concurrently in the BOTE effort were
performed sequentially in the modeling tool, over-estimating the time and cost demand. As such,
as the modeling progressed, only one building of the commercial type was simulated in the tool.
Note that while different building types are generally characterized by a different breakdown of
surfaces, since surface types can be explicitly defined by the user in the tool, the building type
did not change the results.
The BOTE facility was decontaminated using three different rounds of treatment method and
agent combinations and contaminant was disseminated in between each round of
decontamination. As such, each round of decontamination within the BOTE report was
considered an individual decontamination event and the cost estimates for decontamination were
considered as a range rather than summed between each round.
Note also that the number of lab days was not included in the Characterization Sampling onsite
days during the initial stages of model verification as this value was not included in the CS onsite
days in the BOTE report. As this time estimate directly affects the Incident Command cost, it
was removed so that the resulting IC cost from the tool more accurately reflected the
corresponding cost in the BOTE report. However, the UTR OTD model verification effort did
include this value in the overall onsite days. As such, it was included in the final test runs for
BOTE in order to remain consistent.
5.1.2 Model Changes
After each model test, changes were made to the model to address known shortcomings and
discrepancies between the model results and the results identified in the BOTE report. These
changes consisted of various model edits and input data edits, including the following:
• In the original model, decontamination treatment methods were chosen at random for
every surface type. This resulted in an over-estimation of the number of unique treatment
methods applied to surfaces as some methods can be applied to multiple different surface
types. Functionality was added to allow the user to explicitly select the decontamination
treatment methods applied to each surface, eliminating this over-estimation.
• In the original model, an 8-hour workday constant was used for various time calculations.
This was updated to a 12-hour workday constant to remain consistent with the length of
the workday assumed in the BOTE project report.
79
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• In the original model, only pre-decontamination Characterization Sampling was
performed. However, sampling to determine the contaminant present on surfaces after
each round of decontamination was deemed necessary to include within the tool. As such,
post-decontamination Characterization Sampling was added to the model and a total time
and cost estimate was included in the final results as a summation of both the pre-
decontamination and post-decontamination values.
• In the original model, the lab analysis time was based on the total number of samples sent
to each lab and the amount of time it took to analyze one sample. However, this method
assumed only one sample was analyzed at a time, eliminating the concurrency of sample
analysis given multiple lab personnel. This calculation was updated to consider lab
throughput samples per day which accounts for multiple lab personnel analyzing samples
at the same time.
• In the original model, a cost for entrances/exits was included. This cost was found to
incorrectly double count labor costs for the element durations. As such, this cost was
removed.
5.1.3 Results
Table 32 shows the cost results calculated from the Wide-Area Decontamination Tool in
comparison with the values identified from the BOTE report, along with the corresponding 5th
and 95th percentile values for each result.
Table 32: Wide-Area Decontamination Tool Cost Results: BOTE
Cost Results
Model Value -
Model Value - Liquid
Result Name
BOTE Value
Fumigation
(5th, 95th)
Spray
(5th, 95th)
Characterization
Sampling Cost
$618,085 -$621,934
$533,112
($281,867, $812,251)
$533,112
($281,867, $812,251)
Source Reduction Cost
$30,497
$161,852
($147,895, $176,130)
$161,852
($147,895, $176,130)
Decontamination Cost
$109,943 -$172,112
$192,817
($149,503, $238,989)
$220,870
($172,737, $271,427)
Waste Sampling Cost
$5,096-$124,218
$6,482
($6,328, $6,673)
$72,465
($69,719, $75,851)
Incident Command
Cost
$46,737 - $54,907
$104,704
($69,513, $151,204)
$120,173
($83,817, $166,779)
Total Cost of Effort
$774,765 -$887,915
$998,967
($710,232, $1,318,030)
$1,108,472
($818,024, $1,426,867)
Note that Clearance Sampling was not included as an individual value within the BOTE report.
As such, this element was combined here into the CS results. Note additionally that these values
do not include waste management and the inclusion of waste management will likely increase the
overall cost associated with remediation of the event. These values also do not account for
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differences in the amount of material removed during SR given the two different
decontamination methods. Realistically SR costs would not be the same between the two;
however, available data was limited and separate SR values could not be determined for each
method.
Table 33 shows the time results calculated from the Wide-Area Decontamination Tool in
comparison with the values identified from the BOTE report, along with the corresponding 5th
and 95th percentile values for each result.
Table 33: Wide-Area Decontamination Tool Time Results: BOTE
Time Results
Result Name
BOTE Value
Model Value -
Fumigation
(5th, 95th)
Model Value -
Liquid Spray
(5th, 95th)
Characterization Sampling
Workdays
4
3.34
(1.22, 7.27)
3.34
(1.22, 7.27)
Characterization Sampling Onsite
Days
4
23.22
(12.25, 37.73)
23.22
(12.25, 37.73)
Source Reduction Workdays
2
3.14
(3.14, 3.14)
3.14
(3.14, 3.14)
Source Reduction Onsite Days
2
3.14
(3.14, 3.14)
3.14
(3.14, 3.14)
Decontamination Workdays
3-5
4.00
(3.11,4.90)
3.99
(3.09,4.91)
Decontamination Onsite Days
3-5
4.00
(3.11,4.90)
3.99
(3.09,4.91)
Waste Sampling Workdays
* Included in CS
0.12
(0.08,0.16)
2.06
(1.49,2.92)
Waste Sampling Onsite Days
* Included in CS
2.29
(2.18,2.42)
7.14
(5.25, 9.53)
Incident Command Onsite Days
9-11
32.66
(21.63,47.23)
37.50
(26.11, 52.11)
Note that Clearance Sampling was not included as an individual value within the BOTE report.
As such, this element was combined here into the CS results. Note additionally that these values
do not include waste management and the inclusion of waste management will likely increase the
overall time associated with remediation of the event. These values also do not account for
differences in the amount of material removed during SR given the two different
decontamination methods. Realistically SR times would not be the same between the two;
however, available data was limited and separate SR values could not be determined for each
method.
In general, the model results were within (or near) the same order of magnitude as the
comparison results from the BOTE report. However, there are particular noteworthy
discrepancies within the cost results. Each result is detailed below, including the reasoning for
any discrepancies that may have existed as well as a note if there were none:
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• Characterization Sampling Cost. In general, the model results for CS cost were an
under-estimation of the report values due to the various number of additional support
teams that contribute to labor costs within the BOTE effort. As these teams were not
strictly CS teams, they were not accounted for within the tool.
• Source Reduction Cost. The model results for SR cost were an over-estimation of the
report values likely due to an over-estimation in the fraction of the area that was source
reduced. As this value was not explicitly stated in the report, contextual information was
used to estimate this value. The result may not be an accurate depiction of the actual
value, significantly increasing the total cost calculated by the tool. Additionally, it is
unclear if travel costs for the SR teams were included within the total SR cost given in
the report. No breakdown of the SR cost was given in the report and, thus, it is difficult to
identify what was included and what was not.
• Decontamination Cost. While the values calculated for the DC cost were slightly higher
than the range of values given within the report, these values are considered reasonably
close to the given range.
• Waste Sampling Cost. The calculated values are well within the ranges given in the
report.
• Incident Command Cost. The values calculated for the IC cost were an over-estimation
of the report values due to the fact that the total IC onsite days includes the lab days for
both CS and WS, days which were not accounted for within the report. The result is a
longer event duration and, thus, higher labor costs for the IC teams which are on site
during the entire event.
• Total Cost of Effort. The total cost of the effort calculated by the tool is an over-
estimation of the report values due to the over-estimation in other cost areas.
Additionally, there are noteworthy discrepancies within the time results. Each result is detailed
below, including the reasoning for any discrepancies that may have existed as well as a note if
there were none:
• Characterization Sampling Workdays. While the values calculated for the CS
workdays were slightly lower than the range of values given within the report, these
values are considered reasonably close to the given range considering the addition of the
WS workdays (which are included in one value within the BOTE report).
• Characterization Sampling Onsite Days. The values calculated for the CS onsite days
were an over-estimation of the report values due to the fact that this value includes lab
days, days which were not accounted for within the report.
• Source Reduction Workdays. The model results for SR workdays were an over-
estimation of the report values, again, likely due to an over-estimation in the fraction of
the area that was source reduced.
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• Source Reduction Onsite Days. The model results for SR on site were an over-
estimation of the report values, again, likely due to an over-estimation in the fraction of
the area that was source reduced.
• Decontamination Workdays. The calculated values are well within the ranges given in
the report.
• Decontamination Onsite Days. The calculated values are well within the ranges given in
the report.
• Waste Sampling Workdays. The workdays for WS were included in the workdays
given for CS within the report. As such, it is difficult to determine if the calculated values
are realistic or not. However, given that the addition of these values to the corresponding
CS values does not result in significant over-estimation, it is believed that these values
are somewhat reasonable.
• Waste Sampling Onsite Days. The onsite days for WS were included in the onsite days
given for CS within the report. As such, it is difficult to determine if the calculated values
are realistic or not. However, given that the addition of these values to the corresponding
CS values does not result in significant over-estimation, it is believed that these values
are somewhat reasonable. Additionally, the values calculated for the WS onsite days were
an over-estimation of the CS report values due to the fact that this value includes lab
days, days which were not accounted for within the report.
• Incident Command Onsite Days. The overall IC onsite days calculated by the tool are
an over-estimation of the report values due to the over-estimation in other cost areas, as
well as the inclusion of CS and WS lab days.
5.1.4 Additional Analysis
Table 34 below shows a further comparison of the cost results, with each result presented as a
percentage of the total cost of the effort. Note that the percentages for the BOTE Project report
may not add to 100%. That is because the averages were used wherever a range of values was
given. As such, these percentages are not exact, and some range should be applied.
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Table 34: BOTE Cost Percentages
Cost Percentage Results
Result Name
BOTE %
Model % -
Fumigation
Model % -
Liquid Spray
Characterization Sampling Cost
75%
52%
47%
Source Reduction Cost
4%
15%
14%
Decontamination Cost
17%
19%
19%
Waste Sampling Cost
8%
1%
6%
Incident Command Cost
6%
12%
12%
Table 35 below shows a further comparison of the workday results, with each result presented as
a percentage of the total IC onsite days (which have been adjusted to exclude any lab days
associated with CS or WS). Note that the percentages for the BOTE Project report may not add
to 100%. That is because the averages were used wherever a range of values was given. As such,
these percentages are not exact, and some range should be applied. Additionally, the CS and WS
workdays have been added, as they are presented as one value within the BOTE Project report.
Table 35: BOTE Time Percentages
Cost Percentage Results
Result Name
BOTE %
Model % -
Fumigation
Model % -
Liquid Spray
Characterization Sampling +
Waste Sampling Workdays
40%
32%
43%
Source Reduction Workdays
20%
29%
25%
Decontamination Workdays
40%
38%
32%
Overall, the percentage breakdowns of all the model results were fairly consistent with what was
calculated based on the report values. Slight discrepancies do exist, specifically in the cost
percentages; however, given that the comparison percentages are based on averages, there is
room for some of this discrepancy.
5.2 Case 2
5.2.1 Approach
The UTR OTD report details a comprehensive investigation into the decontamination of a
biological agent in a mock underground transportation scenario. For details about the UTR OTD
effort, refer to Section 2.2.2. Table 36 shows the cost results from the UTR OTD report that were
used to validate the resulting cost estimates calculated by the tool. Note that Source Reduction
for all waste materials was not included in the UTR OTD mock scenario and that a portion of
these materials were left in the contaminated area and decontaminated. As such, the cost of SR
was assumed to be zero. Additionally, note that Clearance Sampling was not included as an
individual value within the UTR OTD report. As such, this element was combined here into the
CS results.
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Table 36: UTR OTD Cost Results
Cost Results
Result Name
Value
Characterization Sampling Cost
$196,436-$199,604
Decontamination Cost
$29,910-$43,849
Waste Sampling Cost
$1,347-$2,605
Incident Command Cost
$108,669
Total Cost of Effort
$276,542 - $354,727
Table 37 shows the time results from the UTR OTD report that were used to validate the
resulting time estimates calculated by the tool. Again, note that the SR workdays and onsite days
were assumed to be zero as this element was not performed during the mock scenario.
Table 37: UTR OTD Time Results
Time Results
Result Name
Value
Characterization Sampling Workdays
2
Characterization Sampling Onsite Days
2
Decontamination Workdays
3-5
Decontamination Onsite Days
3-5
Waste Sampling Workdays
*Included in CS
Waste Sampling Onsite Days
*Included in CS
Incident Command Onsite Days
6-8
Numerous model tests were performed, each run with 10,000 realizations to allow sampling to
account for all uncertainty within the parameters. Results were averaged over all realizations.
Changes were made to the model between each test to address any shortcomings of the model.
The input values used for the UTR OTD verification case can be found in Appendix K. Single
values were input as constants, ranges of values were input as a uniform distribution between the
minimum and maximum values identified, and any values with a distribution specified in the text
were input accordingly. Additionally, some values were estimated or calculated based on
contextual information found in the source and surrogate values were used when a value could
not be found in the respective text. The WADE tool was used as a source for surrogate values
wherever information could not be obtained from either project report.
The UTR OTD facility was decontaminated using two different rounds of treatment method and
agent combinations and contaminant was disseminated in between each round of
decontamination. As such, each round of decontamination within the UTR OTD report was
considered an individual decontamination event and the cost estimates for decontamination were
considered as a range rather than summed between each round.
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Note that, unlike the BOTE verification case, the number of lab days was included in the
Characterization Sampling onsite days during the model verification in order to assess a more
accurate version of the model results since this value was included in the overall onsite days
upon delivery of the final model.
5.2.2 Model Changes
After each model test, changes were made to the model to address known shortcomings and
discrepancies between the model results and the results identified in the UTR OTD report. These
changes consisted of various model edits and input data edits, including the following:
• In the original model, Waste Sampling was not accounted for. However, waste sampling
was deemed an important contributing cost in both the BOTE and UTR OTD analyses, as
well as real-world scenarios. As such, this process was implemented in the model in a
similar fashion to the Characterization Sampling implementation.
• In the original model, the total number of entries for teams during a specific element was
calculated using a number of entries per day. However, it was decided that this did not
fully encompass the complexity of entries as entry durations varied based on the level of
PPE donned by personnel. As such, this calculation was adjusted to use entry durations
based on PPE level instead.
• In the original model, site entries were considered for all decontamination methods,
regardless of the differences between the methods. However, in an effort to provide more
distinction and accuracy to the specific treatment methods, model functionality was
changed such that the fumigation and fogging decontamination methods were assumed to
require zero site entries by decontamination teams. Note that although entries by safety
teams may still be required for these methods in order to ensure the site is safe for re-
entry post-decontamination, this is not yet accounted for in the tool.
• In the original model, per diem and lodging costs were calculated for all teams for the
entire event duration. However, this was deemed unrealistic as during a real-world
incident, only the necessary teams would be onsite at a given time. As such, the per diem
and lodging costs, and by extension, total travel costs, were calculated for each team only
for the time that team spent onsite and working.
• In the original model, time and costs associated with entry preparation, decontamination
line processes, and post-entry rest periods was not accounted for. However, these
contributions were considered significant in terms of producing more accurate results. As
such, the model was adjusted to account for all three.
• In the original model, no waste quantities were calculated or included in the model
results. However, as this was a desired function of the tool, solid and aqueous waste
quantities as a result of decontamination were added as model results.
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5.2.3 Results
Table 38 shows the cost results calculated from the Wide-Area Decontamination Tool in
comparison with the values identified from the UTR OTD report, along with the corresponding
5th and 95th percentile values for each result.
Table 38: Wide-Area Decontamination Tool Cost Results: UTR OTD
Cost Results
Result Name
UTR OTD Value
Model Value - Fogging
(5th, 95th)
Model Value - Liquid
Spray
(5th, 95th)
Characterization
Sampling Cost
$196,436-$199,604
$322,979
($263,988, $429,041)
$322,979
($263,988, $429,041)
Decontamination
Cost
$29,910-$43,849
$129,804
($96,745, $167,617)
$168,298
($126,227, $217,224)
Waste Sampling Cost
$1,347-$2,605
$9,658
($9,194, $10,046)
$8,899
($8,449, $9,249)
Incident Command
Cost
$108,669
$135,716
($106,940, $179,552)
$135,418
($106,573, $179,521)
Total Cost of Effort
$276,542 - $354,727
$598,157
($500,993, $733,277)
$635,594
($532,742, $773,387)
Note that Clearance Sampling was not included as an individual value within the UTR OTD
report. As such, this element was combined here into the CS results. Note additionally that these
values do not include waste management and the inclusion of waste management will likely
increase the overall cost associated with remediation of the event.
Table 39 shows the time results calculated from the Wide-Area Decontamination Tool in
comparison with the values identified from the UTR OTD report, along with the corresponding
5th and 95th percentile values for each result.
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Table 39: Wide-Area Decontamination Tool Time Results: UTR OTD
Time Results
Result Name
UTR OTD Value
Model Value -
Fogging
(5th, 95th)
Model Value-
Liquid Spray
(5th, 95th)
Characterization Sampling
Workdays
2
1.58
(0.72, 3.76)
1.58
(0.72, 3.76)
Characterization Sampling Onsite
Days
2
16.02
(11.06, 23.76)
16.02
(11.06, 23.76)
Decontamination Workdays
3-5
4.00
(3.10,4.90)
4.00
(3.09, 4.90)
Decontamination Onsite Days
3-5
4.00
(3.10,4.90)
4.00
(3.09, 4.90)
Waste Sampling Workdays
* Included in CS
0.13
(0.09,0.18)
0.10
(0.07,0.15)
Waste Sampling Onsite Days
* Included in CS
3.83
(3.41,4.11)
3.79
(3.37,4.05)
Incident Command Onsite Days
5-7
23.85
(18.76, 31.62)
23.80
(18.69, 31.62)
Note that Clearance Sampling was not included as an individual value within the UTR OTD
report. As such, this element was combined here into the CS results. Note additionally that these
values do not include waste management and the inclusion of waste management will likely
increase the overall time associated with remediation of the event.
In general, the model results were within (or near) the same order of magnitude as the
comparison results from the UTR OTD report. However, there are particular noteworthy
discrepancies within the cost results. Each result is detailed below, including the reasoning for
any discrepancies that may have existed as well as a note if there were none:
• Characterization Sampling Cost. In general, the model results for CS cost were an
over-estimation of the report values due to the inclusion of CS lab days in the overall
onsite days, resulting in increased travel costs for the CS teams as per diem and lodging
was required for a significantly longer duration.
• Decontamination Cost. The values calculated for the DC cost were an over-estimation
of the report values, due to discrepancies between labor costs for the DC teams. It is not
immediately clear if DC teams were contributing to labor costs during decontamination
treatment drying days within the report. However, it is assumed that DC personnel are
paid hourly during this time within the tool.
• Waste Sampling Cost. The values calculated for the WS cost were an over-estimation of
the report values, likely due to the estimation of the fraction of total waste that was
sampled. As this value was not explicitly stated within the report, it was estimated based
on contextual information. The result may not be an accurate depiction of the actual
value, significantly increasing the total cost calculated by the tool. Additionally, it is
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unclear if travel costs for the WS teams were included within the total WS cost given in
the report. No breakdown of the WS cost was given in the report and, thus, it is difficult
to identify what was included and what was not.
• Incident Command Cost. The values calculated for the IC cost were an over-estimation
of the report values due to the fact that the total IC onsite days includes the lab days for
both CS and WS, days which were not accounted for within the report. The result is a
longer event duration and, thus, higher labor costs for the IC teams which are on site
during the entire event.
• Total Cost of Effort. The total cost of the effort calculated by the tool is an over-
estimation of the report values due to the over-estimation in other cost areas.
Additionally, there are noteworthy discrepancies within the time results. Each result is detailed
below, including the reasoning for any discrepancies that may have existed as well as a note if
there were none:
• Characterization Sampling Workdays. While the values calculated for the CS
workdays were slightly lower than the range of values given within the report, these
values are considered reasonably close to the given range considering the addition of the
WS workdays (which are included in one value within the UTR OTD report).
• Characterization Sampling Onsite Days. The values calculated for the CS onsite days
were an over-estimation of the report values due to the fact that this value includes lab
days, days which were not accounted for within the report.
• Decontamination Workdays. The calculated values are well within the ranges given in
the report.
• Decontamination Onsite Days. The calculated values are well within the ranges given in
the report.
• Waste Sampling Workdays. The workdays for WS were included in the workdays
given for CS within the report. As such, it is difficult to determine if the calculated values
are realistic or not. However, given that the addition of these values to the corresponding
CS values does not result in significant over-estimation, it is believed that these values
are somewhat reasonable.
• Waste Sampling Onsite Days. The onsite days for WS were included in the onsite days
given for CS within the report. As such, it is difficult to determine if the calculated values
are realistic or not. However, given that the addition of these values to the corresponding
CS values does not result in significant over-estimation, it is believed that these values
are somewhat reasonable. Additionally, the values calculated for the WS onsite days were
an over-estimation of the CS report values due to the fact that this value includes lab
days, days which were not accounted for within the report.
• Incident Command Onsite Days. The overall IC onsite days calculated by the tool are
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an over-estimation of the report values due to the over-estimation in other cost areas, as
well as the inclusion of CS and WS lab days.
5.2.4 Additional Analysis
Table 40 below shows a further comparison of the cost results, with each result presented as a
percentage of the total cost of the effort. Note that the percentages for the UTR OTD report may
not add to 100%. That is because the averages were used wherever a range of values was given.
As such, these percentages are not exact, and some range should be applied.
Table 40: UTR OTD Cost Percentages
Cost Percentage Results
Result Name
UTR OTD %
Model % -
Fogging
Model % -
Liquid Spray
Characterization
Sampling Cost
63%
54%
51%
Decontamination Cost
12%
22%
26%
Waste Sampling Cost
1%
2%
1%
Incident Command Cost
34%
23%
21%
Table 41 below shows a further comparison of the workday results, with each result presented as
a percentage of the total IC onsite days (which have been adjusted to exclude any lab days
associated with CS or WS). Note that the percentages for the UTR OTD report may not add to
100%. That is because the averages were used wherever a range of values was given. As such,
these percentages are not exact, and some range should be applied. Additionally, the CS and WS
workdays have been added, as they are presented as one value within the UTR OTD report.
Table 41: UTR OTD Time Percentages
Cost Percentage Results
Result Name
UTR OTD
%
Model % -
Fogging
Model % -
Liquid Spray
Characterization Sampling +
Waste Sampling Workdays
33%
30%
30%
Decontamination Workdays
67%
70%
71%
Overall, the percentage breakdowns of all the model results were fairly consistent with what was
calculated based on the report values. Slight discrepancies do exist, specifically in the cost
percentages; however, given that the comparison percentages are based on averages, there is
room for some of this discrepancy.
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6 QUALITY ASSURANCE
Several methods of quality assurance were utilized throughout the development of the WADT,
including 1) case studies, 2) hand calculations, 3) SME discussions, and 4) data quality. Each of
these is described in more detail below.
6.1 Case Studies
The case studies discussed in Section 5 were used to determine how closely model results
aligned with cost and time estimates for similar real-world incidents, in this case represented by
mock decontamination events performed and documented by the EPA. These mock events were
simulated in the tool to help identify areas of improvement within the tool. For more details on
how this was done and some of the changes made to the tool as a result, refer back to Section 5.
6.2 Hand Calculations
Hand calculations were performed to verify that tool results aligned with the expected outcomes
of the equations that were developed during this effort. An Excel file was generated
implementing all of the developed calculations within the WADT. A notional input file was
generated for simulation in the WADT, and similar inputs were used within the Excel file. The
results of each were then compared to ensure that they matched.
6.3 SME Discussions
Throughout the development of the WADT, numerous discussions were had with EPA SME's
who gave input on realistic processes which occur during remediation events as well as the data
driving the tool and the quality of specific values as they relate to wide-area incidents. These
discussions helped highlight areas for improved applicability of the tool to the processes it was
developed to capture as well as ensured that throughout its development, expert logic pertaining
to remediation was being used to guide this development.
6.4 Data Quality
The data driving the WADT was primarily obtained from sources developed by the EPA which
underwent their own quality assurance and quality control efforts during their development.
7 CONCLUSION
After assessing various existing decontamination models, studies on mock decontamination
scenarios, and a large efficacy dataset, the Wide-Area Decontamination Tool for indoor, outdoor,
and underground scenarios was developed to estimate the cost, time, and resource demand
associated with biological incident remediation efforts. The careful review of the WADE tool,
the WEST application, the Decontamination spreadsheet, and the TOTS tool revealed that these
models were limited in scope and didn't fully characterize indoor, outdoor, and underground
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scenarios or efficacy. Additionally, the review of the BOTE report and the UTR OTD report
identified valuable information that was deemed important to include in the development of the
tool. Finally, the BioDecontamination Compendium played an integral role in defining efficacy
and, subsequently, the Efficacy Model. The resulting application was a comprehensive modeling
tool that captured the complexity of these decontamination scenarios, including the
characterization of efficacy.
The resulting tool performed reasonably well when tested against two case studies, detailed in
Section 5. While there is still room for the improvement of various model functionality, the
updates made to the model as a result of the analysis of these case studies drastically improved
the accuracy of the overall results and, thus, the tool's applicability to real-world scenarios.
8 LITERATURE CITED REFERENCES
[1] FBI.gov. Amerithrax or Anthrax Investigation, https://www.fbi.gov/history/famous-
cases/amerithrax-or-anthrax-investigation
[2] Schmitt, K., Zacchia, N. A. Total Decontamination Cost of the Anthrax Letter Attacks.
Biosecur Bioterror, 10(2012), pp. 1-10.
https://spectrum. library. concordia.ca/974056/l/Schmitt_Spectrum.pdf
[3] U.S. EPA (2016). Spreadsheet Tool to Estimate Costs Associated with Wide-Area
Response to a Chemical, Biological, or Radiological Incident. EPA/600/R-16/249
[4] SciPy.org. scipy.stats.rv_continuous.fit. November 2020.
https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_continuous.fit.html
[5] U.S. EPA. Waste Estimation Support Tool and User Guide . U.S. Environmental Protection
Agency, Washington, DC, EPA/600/B-14/235, 2014.
[6] Boe, T., W. Calfee, S. Lee, L. Mickelsen, C. Hayes, AND M. Rodgers. A GIS Application
for Developing Biological Sampling Designs and Estimating Resources Necessary for
Implementation. EPADecon Conference, Norfolk,VA, November 19 - 21, 2019.
[7] U.S. EPA. Bio-Response Operational Testing and Evaluation (BOTE) Project - Phase 1:
Decontamination Assessment. U.S. Environmental Protection Agency, Washington, DC,
EPA/600/R-13/168, 2013.
[8] U.S. EPA. Underground Transport Restoration (UTR) Operational Technology
Demonstration (OTD). U.S. Environmental Protection Agency, Washington, DC,
EPA/600/R-17/272, 2017.
[9] Wood, J. P., & Adrion, A. C. Review of Decontamination Techniques for the Inactivation
of Bacillus anthracis and Other Spore-Forming Bacteria Associated with Building or
Outdoor Materials, 2019. Environmental Science & Technology , Vol. 53, No. 8. p. 4045-
4062.
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[10] Rohatgi, A. WebPlotDigitizer. 2020. https://automeris.io/WebPlotDigitizer/
[11] Statology.org. What is Considered to Be a "Strong" Correlation? January 2020.
https://www.statology.org/what-is-a-strong-correlation/
[12] Balentyne, Mindrila. Scatterplots and Correlation.
https://www.westga.edu/academics/research/vrc/assets/docs/scatterplots_and_correlation_n
otes.pdf
[13] Corporate Finance Institute. P-value: A probability measure of finding the observed, or
more extreme results, when the null hypothesis of a given statistical test is true. 2015.
https://corporatefinanceinstitute.com/resources/knowledge/other/p-value/
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APPENDIX A: REPRESENTATIVE SURFACE NAMES
The following table contains every surface type found in the BioDecontamination Compendium
along with the corresponding representative surface types that were chosen for each.
Table A-l: Representative Surface Names for BioDecontamination Compendium Surfaces
BioDecontamination Compendium
Representative Surface Name
acoustic ceiling tiles
Acoustic Ceiling Tiles
aerosol
aerosol (2.8 um spore clusters)
Aerosol
aerosol (4.4 um spore clusters)
aerosol (single spores)
agar plate
Agar Plate
aircraft performance coated aluminum (APC)
Aircraft Performance Coated Aluminum
aluminum with aircraft performance coating
aluminum
Aluminum
aluminum foil
Aluminum Foil
ambiguous surface
Ambiguous Surface
anti-skid grit tape
Anti-skid Grit Tape
Anti-skid material on aluminum
Anti-skid Material on Aluminum
any painted surface
Any Painted Surface
AOAC carrier (porcelain and suture)
AOAC Carrier (Porcelain and Suture)
apples
Apples
aqueous
Aqueous
aqueous buffer
Aqueous Buffer
aqueous paint mixture
Aqueous Paint Mixture
aqueous solution
Aqueous Solution
aqueous solution of lg/L glucose
aqueous suspension
aqueous suspension with 10% serum
aqueous suspension with 40% ethanol
Aqueous Suspension
aqueous suspension with protein load
aqueous suspension
Archival Paper
Archival Paper
Arizona Test Dust
Arizona test dust (dried)
Arizona Test Dust
AZ test dust (1-cm deep)
AZ test dust (2-cm deep)
asphalt
Asphalt
Asphalt Paving
Asphalt Paving
BI Stainless Steel in Tyvek® Packaging
BI Stainless Steel in Tyvek Packaging
A-l
-------
BioDecontamination Compendium
Representative Surface Name
biofilm covered copper pipe
Biofilm Covered Copper Pipe
biofdm covered PVC pipe
Biofilm Covered PVC Pipe
Biological indicator
biological indicator 304 SS
Biological Indicator Strip
biological indicator strip
biological indicator strips
BioStrip (paper)
Brick
Brick
butyl rubber
Butyl Rubber
Carbon Steel
Carbon Steel
CARC-W coated stainless steel
CARC-W Coated Stainless Steel
carpet
Carpet Horizontal
floor 1: floors and ceilings (epoxy-coated, wood
laminate, carpet, and ceiling tile)
Carpet
floor 2: floors and ceilings (epoxy-coated, wood
laminate, carpet, and ceiling tile)
cassava starch 18% moisture
Cassava Starch
cassava starch 30% moisture
ceiling tile
floor 1: floors and ceilings (epoxy-coated, wood
laminate, carpet, and ceiling tile)
Ceiling Tile
floor 2: floors and ceilings (epoxy-coated, wood
laminate, carpet, and ceiling tile)
Cellulose Insulation
Cellulose Insulation
Cement
Cement
ceramic
Ceramic
Ceramics
chair back
Chair Back
chair seat
Chair Seat
cinder block
Cinder Block
Cinderblock
Composite epoxy
Composite Epoxy
Concrete
concrete (ceiling)
concrete (floors)
concrete (walls)
Concrete
concrete blocks
Concrete Horizontal
Concrete vertical
Unpainted Concrete
A-2
-------
BioDecontamination Compendium
Representative Surface Name
cork boards
Cork Boards
cotton cloth
Cotton Cloth
Cotton swab
Cotton Swab
Cotton swab with serum
custard cream
Custard Cream
Deck Wood Horizontal
Deck Wood
deck wood Vertical
Decorative laminate
Decorative Laminate
desk top
Desk Top
DI water
DI Water
diamond burs
Diamond Burs
dried fig
Dried Fig
Dry Wall Vertical
Dry Wall
egg-yolk residue on stainless steel
Egg-Yolk Residue on Stainless Steel
epoxy
Epoxy
fiberglass lined HVAC duct location A
fiberglass lined HVAC duct location B
fiberglass lined HVAC duct location C
fiberglass lined HVAC duct location D
Fiberglass Lined HVAC Duct
fiberglass lined HVAC duct location E
fiberglass lined HVAC duct location F
fiberglass lined HVAC duct location G
fiberglass lined HVAC duct location H
fiberglass wall paneling
Fiberglass Wall Paneling
filing cabinet
Filing Cabinet
filter paper (2.8 um spore clusters)
filter paper (4.4 um spore clusters)
Filter Paper
filter paper (single spores)
filter paper spore trip
flour paste on stainless steel
Flour on Stainless Steel
flour residue on stainless steel
food packaging material (presumably plastic)
Food Packaging Material (Presumably Plastic)
Galvanized Metal
Galvanized Metal
galvanized metal ductwork
galvanized metal HVAC duct location A
galvanized metal HVAC duct location B
galvanized metal HVAC duct location C
Galvanized Metal HVAC Duct
galvanized metal HVAC duct location D
galvanized metal HVAC duct location E
galvanized metal HVAC duct location F
A-3
-------
BioDecontamination Compendium
Representative Surface Name
galvanized metal HVAC duct location G
Galvanized Metal HVAC Duct
galvanized metal HVAC duct location H
galvanized steel
Galvanized Steel
glass
Glass
Glass (small)
Glass (Small)
Glass AOAC 2008.05
Glass AOAC 2008.05
glass beads
Glass Beads
glass bottle interior
Glass Bottle Interior
glass bottle interior coated with bovine serum
Glass Bottle Interior Coated with Bovine Serum
Glass fiber filter swab
Glass Fiber Filter Swab
glass helices
Glass Helices
glass petri dish
Glass Petri Dish
gold foil
Gold Foil
Granite
Granite
greasy aluminum stub
Greasy Aluminum Stub
grimed and washed concrete
Grimed Concrete
grimed and washed steel
Grimed Steel
grimed and washed tile
Grimed and Washed Tile
grimed Concrete
Grimed Concrete
grimed rough-cut barn wood
Grimed Wood
grimed steel
Grimed Steel
grimed tile
Grimed Tile
hardwood
Hardwood
healthcare waste
Healthcare Waste
horse serum residue on stainless steel
Horse Serum Residue on Stainless Steel
Hypalon® Rubber Glove
Rubber Glove
Industrial carpet
Industrial Carpet
Industrial-grade carpet
industrial sucrose syrup
Industrial Sucrose Syrup
InsulFab
InsulFab
interior of aluminum carton
Interior of Aluminum Carton
interior of polyethylene carton
Interior of Polyethylene Carton
isopore polycarbonate membrane filter
Isopore Polycarbonate Membrane Filter
keyboard
Keyboard
Laminate
Laminate
lard coated stainless steel (spores under lard)
Lard Coated Stainless Steel (Spores Under
Lard)
Linoleum
Linoleum
liquid
Liquid
liquid suspension atop agar
Liquid Suspension atop Agar
A-4
-------
BioDecontamination Compendium
Representative Surface Name
loop-pile carpet
Loop-Pile Carpet
Metal Ductwork
Metal Ductwork
MgF2 glass
MgF2 Glass
milk
Milk
molecular sieves
Molecular Sieves
mylar
Mylar
natural water (cedar)
Natural Water
natural water (marysville)
navy ship topcoated stainless steel (NTC)
Navy Ship Topcoated Stainless Steel (NTC)
nitrocellulose filter
Nitrocellulose Filter
nitrocellulose membrane
Nitrocellulose Membrane
nonexposed areas of surgical instruments
Nonexposed Areas of Surgical Instruments
Nylon
Nylon
nylon carpet
Nylon Carpet
office air
Office Air
office carpet
Carpet
paint
Paint
painted aluminum (aircraft performance coating)
Painted Aluminum (Aircraft Performance
Coating)
painted aluminum alloy
Painted Aluminum Alloy
Painted Canvas
Painted Canvas
Painted cinder block
Painted Cinder Block
Painted concrete
Painted Concrete
Painted dry wall
painted office drywall
Painted Dry Wall
Painted drywall paper
painted I-beam steel
Painted Steel
painted steel
painted joint tape
Painted Joint Tape
painted metal
Painted Metal
painted paper
Painted Paper
floor 1: walls (painted wallboard and plastic walls)
floor 2: walls (painted wallboard and plastic walls)
painted wallboard
Painted Wallboard
painted wallboard coupon
Painted Wallboard Horizontal
painted wallboard paper
paper
Paper
paper catalog
paprika (low moisture)
Paprika
paprika (medium moisture)
A-5
-------
BioDecontamination Compendium
Representative Surface Name
paprika water slurry interior
Paprika Water Slurry Interior
paprika water slurry overall
Paprika Water Slurry Overall
paprika water slurry surface
Paprika Water Slurry Surface
Particle Board
Particle Board
phosphate buffer pH=6
phosphate buffer pH=7
Phosphate Buffer
phosphate buffer pH=8
pin cushion screen
Pin Cushion Screen
Plastic
Plastic
plastic (LDPE) fdms containing titanium dioxide
Plastic (LDPE) Films Containing Titanium
Dioxide
plastic syringe barrel
Plastic Syringe Barrel
floor 1: walls (painted wallboard and plastic walls)
Plastic Walls
floor 2: walls (painted wallboard and plastic walls)
Plate Glass
Plate Glass
Plywood
Plywood
Polycarbonate
Polycarbonate
Lexan
Polyethylene
LDPE
Polyethylene
Low-density polyethylene
polyolefin
Polyolefin
polypropylene
Polypropylene
Polypropylene swab
Polypropylene Swab
Polypropylene swab with serum
Polystyrene
Polystyrene
polystyrene petri dish
polyurethane
Polyurethane
polyurethane painted aluminum
Polyurethane Painted Aluminum
polyvinyl chloride
Polyvinyl Chloride
Porcelain
Porcelain
porcelain penicylinder
prehumidified cotton cloth
Prehumidified Cotton Cloth
prehumidified glass
Prehumidified Glass
prehumidified painted steel
Prehumidified Painted Steel
prehumidified polyurethane
Prehumidified Polyurethane
prehumidified polyvinyl chloride
Prehumidified Polyvinyl Chloride
prehumidified stainless steel
Prehumidified Stainless Steel
pure sucrose syrup
Pure Sucrose Syrup
rough surface patio tiles
Rough Surface Patio Tiles
rubber flooring
Rubber Flooring
A-6
-------
BioDecontamination Compendium
Representative Surface Name
rubber silicone butyl blend
Rubber Silicone Butyl Blend
scaffold of polycaprolactone
Scaffold of Polycaprolactone
scalpel blade
Scalpel Blade
seeds
Seeds
shaved porcine skin
Shaved Porcine Skin
silicone and butyl rubber blend
Silicone and Butyl Rubber Blend
Silk Fabric
Silk Fabric
smooth surface patio tiles
Smooth Surface Patio Tiles
Sol Cont
Sol Cont
soy milk
Soy Milk
spore solution on petri dish inside ambulance
Spore Solution on Petri Dish inside Ambulance
stainless steel
stainless steel (Floor, left side)
Stainless steel (Floor, right side
stainless steel (horizontal)
stainless steel (Left wall)
Stainless Steel
stainless steel (Rear wall, left side)
stainless steel (Rear wall, right side)
stainless steel (Right wall)
stainless steel (vertical)
Stainless steel 304
stainless steel (spores applied after decon agent)
Stainless Steel (Spores Applied after Decon
Agent)
stainless steel + 0.3% organic burden
Stainless Steel + 0.3% Organic Burden
stainless steel BI
stainless steel BI inside a manufacturing machine
Stainless Steel BI
stainless steel BI inside a tube
stainless steel bioindicator
Stainless Steel Bioindicator
stainless steel biological indicator
stainless steel in Tyvek
Stainless Steel in Tyvek
stainless steel knife handle
Stainless Steel Knife Handle
stainless steel with organic and soil load
Stainless Steel with Organic and Soil Load
stainless steel with organic load
Stainless Steel with Organic Load
Steel
Steel
steel (chemical resistant coating)
Steel (Chemical Resistant Coating)
suspension of nutrient rich media
Suspension of Nutrient Rich Media
Suture Loop
Suture Loop
swine skin
Swine Skin
Teflon
Teflon
Tile
Tile
tire
Tire
A-7
-------
BioDecontamination Compendium
Representative Surface Name
Agvise Topsoil
Topsoil
topsoil (1-cm deep)
Topsoil
topsoil (2-cm deep)
topsoil (dried)
Earthgro Topsoil
treated wood
treated wood vertical
Treated Wood
Pressure-Treated Lumber
Tyvek
Tyvek
untreated wood
Untreated Wood
used cut-pile carpet
Used Cut-Pile Carpet
vinyl chloride plate
Vinyl Chloride Plate
vinyl floor tile
Vinyl Tile
Vinyl Tile
vinyl flooring
Vinyl Flooring
vinyl seating
Vinyl Seating
Wallboard
Wallboard
Wallboard Paper
Wallboard Paper
wash down water
wash down water with 1% Alconox detergent
Wash Down Water
wash down water with 1% Dawn detergent
water
Water
water (ECA1)
water (ECA2)
water (ECA3)
Water (ECA#)
water (ECA4)
water (ECA5)
wet polypropylene
Wet Polypropylene
whole milk residue on stainless steel
Whole Milk Residue on Stainless Steel
wiring insulation
Wiring Insulation
wiring insulation
bare fir wood
Bare pine wood
Bare Wood
maple wood
Pine Wood
Wood
wood
rough-cut barn wood
rough-cut barn wood coupon
Rough-cut Wood Vertical
A-8
-------
BioDecontamination Compendium
Representative Surface Name
floor 1: floors (epoxy-coated and wood laminate)
floor 2: floors (epoxy-coated and wood laminate)
floor 1: floors and ceilings (epoxy-coated, wood
laminate, carpet, and ceiling tile)
Wood Laminate
floor 2: floors and ceilings (epoxy-coated, wood
laminate, carpet, and ceiling tile)
Wood Laminate
wood tiles
Wood Tiles
woven carpet
Woven Carpet
A-9
-------
APPENDIX B: BASELINE PARAMETERS
Table B-l presents the baseline Incident Command parameters that are used as the default values within the tool.
Table B-l: Baseline Incident Command Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Personnel Required (OSC)
Number of OSC personnel per team
people/team
1
0
100
Personnel Required (PL-4)
Number of PL-4 personnel per team
people/team
0
0
100
Personnel Required (PL-3)
Number of PL-3 personnel per team
people/team
0
0
100
Personnel Required (PL-2)
Number of PL-2 personnel per team
people/team
0
0
100
Personnel Required (PL-1)
Number of PL-1 personnel per team
people/team
0
0
100
Personnel Overhead Days
Number of setup and tear-down days
for element
days
0
0
10
Roundtrip Days
Total number of travel days
days
2
0
10
Table B-2 presents the baseline Characterization Sampling parameters that are used as the default values within the tool.
Table B-2: Baseline Characterization Sampling Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Teams Required
Number of teams required
team
1-6
1
50
Personnel Required (OSC)
Number of OSC personnel required
per team
person / team
0.3-0.333
0
100
Personnel Required (PL-4)
Number of PL-4 personnel required
per team
person / team
0-2
0
100
Personnel Required (PL-3)
Number of PL-3 personnel required
per team
person / team
2-3
0
100
Personnel Required (PL-2)
Number of PL-2 personnel required
per team
person / team
0-2
0
100
Personnel Required (PL-1)
Number of PL-1 personnel required
per team
person / team
0
0
100
B-l
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Number of Respirators per
Person
Number of respirators required per
each person
respirator / person
1
0
5
Surface Area per Wipe
Surface area that can be sampled per
one wipe
mA2 / wipe
0.064516
0.5
25
Surface Area per HEPA
Sock
Surface area that can be sampled per
one HEPA sock
mA2 / sock
0.09-0.37
0.5
25
Wipes per Hour per Team
Number of wipes used per hour per
team
wipe / (hour *
team)
mean: 14.51
stdev: 7.35
0
50
HEPA Socks per Hour per
Team
Number of HEPA socks used per
hour per team
sock / (hour * team)
mean: 10.56
stdev: 7.70
0
50
Entry Duration Based on
PPE Level (A)
Duration of each entry for one
personnel donning PPE Level A
hours / entry
1.18
0
5
Entry Duration Based on
PPE Level (B)
Duration of each entry for one
personnel donning PPE Level B
hours / entry
1.495
0
5
Entry Duration Based on
PPE Level (C)
Duration of each entry for one
personnel donning PPE Level C
hours / entry
1.81
0
5
Entry Duration Based on
PPE Level (D)
Duration of each entry for one
personnel donning PPE Level D
hours / entry
2.125
0
5
Number of Labs
Number of labs to which samples
will be sent
labs
6-8
1
50
Lab Uptime Hours per Day
Number of hours lab is operational
per day
hours / day
12
1
12
Lab Throughput Samples
per Day
Number of samples analyzed per day
samples / day
5-84
1
100
Roundtrip Days
Travel days to and from the site area
days
2
0
10
Personnel Overhead Days
Number of setup and teardown days
at the start and end of the element
days
0
0
10
Packaging Time per
Sample
Time required to package one sample
minutes / sample
1.63
0
5
Analysis Time per HEPA
Sample
Time required for one HEPA sample
to be analyzed in a lab
hours / sample
0.77-1
0
5
Analysis Time per Wipe
Sample
Time required for one wipe sample to
be analyzed in a lab
hours / sample
0.67-0.79
0
5
B-2
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Prep Time per Team per
Entry
Time required for each team to
prepare to enter the contamination
site
hours / team * entry
0.6
0
2
Lab Distance from Site
Distance of each external lab from
the contamination site
kilometers
322 - 3,700
0
1.00E+06
Personnel Decon Line
Time per Team per Exit
Time spent in the personnel decon
line upon exiting the contamination
site
hours / team * exit
0.81
0
5
Post-Entry Rest Period
Time required for rest after each site
entry
hours / team * entry
0.5-0.55
0
2
Time of Result
Transmission to IC
Time required to transmit analysis
results from external labs to Incident
Command
hours
24
0
72
Fraction PPE Required (A)
Fraction of all PPE required for one
team that is Level A
unitless
0
1
o
vo
0
1
Fraction PPE Required (B)
Fraction of all PPE required for one
team that is Level B
unitless
0
1
o
0
1
Fraction PPE Required (C)
Fraction of all PPE required for one
team that is Level C
unitless
p
1
p
vo
0
1
Fraction PPE Required (D)
Fraction of all PPE required for one
team that is Level D
unitless
0
1
o
0
1
Fraction of Surface
Sampled
The fraction of the total surface area
that will be sampled
unitless
p
1
p
vo
0
1
Table B-3 presents the baseline Source Reduction parameters that are used as the default values within the tool.
Table B-3: Baseline Source Reduction Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Teams Required
Number of teams required
team
1-6
1
50
Personnel Required (OSC)
Number of OSC personnel required
per team
person / team
0.333
0
100
Personnel Required (PL-4)
Number of PL-4 personnel required
per team
person / team
0-0.67
0
100
B-3
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Personnel Required (PL-3)
Number of PL-3 personnel required
per team
person / team
1-3.33
0
100
Personnel Required (PL-2)
Number of PL-2 personnel required
per team
person / team
0-2
0
100
Personnel Required (PL-1)
Number of PL-1 personnel required
per team
person / team
0
0
100
Mass of Waste Removed
per Hour per Team
Mass of waste material removed from
site per hour per team
kg /(hour *
team)
45.36
0
1000
Entry Duration Based on
PPE Level (A)
Duration of each entry for one
personnel donning PPE Level A
hours / entry
1.18
0
5
Entry Duration Based on
PPE Level (B)
Duration of each entry for one
personnel donning PPE Level B
hours / entry
1.495
0
5
Entry Duration Based on
PPE Level (C)
Duration of each entry for one
personnel donning PPE Level C
hours / entry
1.81
0
5
Entry Duration Based on
PPE Level (D)
Duration of each entry for one
personnel donning PPE Level D
hours / entry
2.125
0
5
Number of Respirators per
Person
Number of respirators required per
each person
respirator /
person
1
0
5
Roundtrip Days
Travel days to and from the site area
days
2
0
10
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
0
0
10
Mass of Waste per Surface
Area
Mass of waste per surface area of site
kg / mA2
0-9.3
0
50
Prep Time per Team per
Entry
Time required for each team to
prepare to enter the contamination site
hours / team *
entry
0.6
0
2
Personnel Decon Line Time
per Team per Exit
Time spent in the personnel decon
line upon exiting the contamination
site
hours / team *
exit
0.81
0
5
Post-Entry Rest Period
Time required for rest after each site
entry
hours / team *
entry
0.5-0.55
0
2
Fraction PPE Required (A)
Fraction of all PPE required for one
team that is Level A
unitless
O
1
o
0
1
Fraction PPE Required (B)
Fraction of all PPE required for one
team that is Level B
unitless
p
1
o
vo
0
1
B-4
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Fraction PPE Required (C)
Fraction of all PPE required for one
team that is Level C
unitless
0
1
o
vo
0
1
Fraction PPE Required (D)
Fraction of all PPE required for one
team that is Level D
unitless
0
1
o
0
1
Fraction Surface Area to be
Source Reduced
Fraction of the total surface area to be
source reduced
unitless
p
1
o
vo
0
1
Table B-4 presents the baseline Decontamination parameters that are used as the default values within the tool.
Table B-4: Baseline Decontamination Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Decon + Drying Days
Number of days required for one
decontamination application method
including drying days
days
3-5
0
10
Personnel Required (OSC)
Number of OSC personnel required
per team
person / team
0.3
0
100
Personnel Required (PL-4)
Number of PL-4 personnel required
per team
person / team
1-2
0
100
Personnel Required (PL-3)
Number of PL-3 personnel required
per team
person / team
3-6
0
100
Personnel Required (PL-2)
Number of PL-2 personnel required
per team
person / team
0
0
100
Personnel Required (PL-1)
Number of PL-1 personnel required
per team
person / team
0
0
100
Number of Respirators per
Person
Number of respirators required per
each person
respirator /
person
1
0
5
Teams Required
Number of teams required
teams
2-6
1
50
Entry Duration Based on
PPE Level (A)
Duration of each entry for one
personnel donning PPE Level A
hours / entry
1.18
0
5
Entry Duration Based on
PPE Level (B)
Duration of each entry for one
personnel donning PPE Level B
hours / entry
1.495
0
5
Entry Duration Based on
PPE Level (C)
Duration of each entry for one
personnel donning PPE Level C
hours / entry
1.81
0
5
B-5
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Entry Duration Based on
PPE Level (D)
Duration of each entry for one
personnel donning PPE Level D
hours / entry
2.125
0
5
Volume of Agent Applied
for Fogging/Fumigation
Volume of agent required for fogging
or fumigation per room volume
L/mA3
0.33
0
50
Volume of Agent Applied
Volume of agent required for
decontaminating room square footage
L/mA2
0.65 - 1.30
0
50
Roundtrip Days
Travel days to and from the site area
days
2
0
10
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
0
0
10
Prep Time per Team per
Entry
Time required for each team to
prepare to enter the contamination site
hours / team *
entry
0.6
0
2
Personnel Decon Line Time
per Team per Exit
Time spent in the personnel decon line
upon exiting the contamination site
hours / team *
exit
0.81
0
5
Post-Entry Rest Period
Time required for rest after each site
entry
hours / team *
entry
0.5-0.55
0
2
Fraction PPE Required (A)
Fraction of all PPE required for one
team that is Level A
unitless
0
1
o
vo
0
1
Fraction PPE Required (B)
Fraction of all PPE required for one
team that is Level B
unitless
0
1
o
0
1
Fraction PPE Required (C)
Fraction of all PPE required for one
team that is Level C
unitless
p
1
p
vo
0
1
Fraction PPE Required (D)
Fraction of all PPE required for one
team that is Level D
unitless
0
1
o
0
1
Table B-5 presents the baseline Clearance Sampling parameters that are used as the default values within the tool.
Table B-5: Baseline Clearance Sampling Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Teams Required
Number of teams required
team
1-6
1
50
Personnel Required (OSC)
Number of OSC personnel required
per team
person / team
0.3-0.333
0
100
B-6
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Personnel Required (PL-4)
Number of PL-4 personnel required
per team
person / team
0-2
0
100
Personnel Required (PL-3)
Number of PL-3 personnel required
per team
person / team
2-3
0
100
Personnel Required (PL-2)
Number of PL-2 personnel required
per team
person / team
0-2
0
100
Personnel Required (PL-1)
Number of PL-1 personnel required
per team
person / team
0
0
100
Number of Respirators per
Person
Number of respirators required per
each person
respirator / person
1
0
5
Surface Area per Wipe
Surface area that can be sampled per
one wipe
mA2 / wipe
0.064516
0.5
25
Surface Area per HEPA
Sock
Surface area that can be sampled per
one HEPA sock
mA2 / sock
0.09-0.37
0.5
25
Wipes per Hour per Team
Number of wipes used per hour per
team
wipe / (hour *
team)
mean: 14.51
stdev: 7.35
0
50
HEPA Socks per Hour per
Team
Number of HEPA socks used per
hour per team
sock / (hour * team)
mean: 10.56
stdev: 7.70
0
50
Entry Duration Based on
PPE Level (A)
Duration of each entry for one
personnel donning PPE Level A
hours / entry
1.18
0
5
Entry Duration Based on
PPE Level (B)
Duration of each entry for one
personnel donning PPE Level B
hours / entry
1.495
0
5
Entry Duration Based on
PPE Level (C)
Duration of each entry for one
personnel donning PPE Level C
hours / entry
1.81
0
5
Entry Duration Based on
PPE Level (D)
Duration of each entry for one
personnel donning PPE Level D
hours / entry
2.125
0
5
Number of Labs
Number of labs to which samples
will be sent
labs
6-8
1
50
Lab Uptime Hours per Day
Number of hours lab is operational
per day
hours / day
12
1
12
Lab Throughput Samples
per Day
Number of samples analyzed per day
samples / day
5-84
1
100
Roundtrip Days
Travel days to and from the site area
days
2
0
10
B-7
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Personnel Overhead Days
Number of setup and teardown days
at the start and end of the element
days
0
0
10
Packaging Time per
Sample
Time required to package one sample
minutes / sample
1.63
0
5
Analysis Time per HEPA
Sample
Time required for one HEPA sample
to be analyzed in a lab
hours / sample
0.77-1
0
5
Analysis Time per Wipe
Sample
Time required for one wipe sample to
be analyzed in a lab
hours / sample
0.67-0.79
0
5
Lab Distance from Site
Distance of each external lab from
the contamination site
kilometers
322 - 3,700
0
1.00E+06
Prep Time per Team per
Entry
Time required for each team to
prepare to enter the contamination
site
hours / team * entry
0.6
0
2
Personnel Decon Line
Time per Team per Exit
Time spent in the personnel decon
line upon exiting the contamination
site
hours / team * exit
0.81
0
5
Post-Entry Rest Period
Time required for rest after each site
entry
hours / team * entry
0.5-0.55
0
2
Time of Result
Transmission to IC
Time required to transmit analysis
results from external labs to Incident
hours
24
0
72
Command
Fraction PPE Required (A)
Fraction of all PPE required for one
team that is Level A
unitless
0
1
o
vo
0
1
Fraction PPE Required (B)
Fraction of all PPE required for one
team that is Level B
unitless
0
1
o
0
1
Fraction PPE Required (C)
Fraction of all PPE required for one
team that is Level C
unitless
p
1
p
vo
0
1
Fraction PPE Required (D)
Fraction of all PPE required for one
team that is Level D
unitless
0
1
o
0
1
Fraction of Surface
The fraction of the total surface area
unitless
p
1
p
vo
0
1
Sampled
that will be sampled
1
Table B-6 presents the baseline Waste Sampling parameters that are used as the default values within the tool.
B-8
-------
Table B-6: Baseline Waste Sampling Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Teams Required
Number of teams required
team
1
1
50
Personnel Required (OSC)
Number of OSC personnel required per
team
person / team
0
0
100
Personnel Required (PL-4)
Number of PL-4 personnel required per
team
person / team
0
0
100
Personnel Required (PL-3)
Number of PL-3 personnel required per
team
person / team
0
0
100
Personnel Required (PL-2)
Number of PL-2 personnel required per
team
person / team
0
0
100
Personnel Required (PL-1)
Number of PL-1 personnel required per
team
person / team
3
0
100
Mass per Waste Sample
Mass that can be sampled per one waste
sample
kg / sample
15.12-16.67
0
150
Volume per Waste Sample
Volume that can be sampled per one
waste sample
L / sample
200.00-208.20
0
200
Waste Samples per Hour
per Team
Number of waste samples used per hour
per team
samples / (hour
* team)
5.9- 12.5
0
50
Number of Labs
Number of labs to which samples will
be sent
labs
6-8
1
50
Lab Uptime Hours per Day
Number of hours lab is operational per
day
hours / day
12
0
12
Lab Throughput Samples
per Day
Number of samples analyzed per day
samples / day
5-84
1
100
Personnel Overhead Days
Number of setup and teardown days at
the start and end of the element
days
0
0
10
Packaging Time per Sample
Time required to package one sample
minutes /
sample
1.63
0
5
Analysis Time per Waste
Sample
Time required for one waste sample to
be analyzed in a lab
hours / sample
0.79
0
5
Lab Distance from Site
Distance of each external lab from the
contamination site
meters
322 - 3,700
0
1.00E+06
B-9
-------
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Time of Result
Transmission to IC
Time required to transmit analysis
results from external labs to Incident
Command
hours
24
0
72
Roundtrip Days
Travel days to and from the site area
days
2
0
10
Solid Waste Produced per
Surface Area
Mass of solid waste produced per
surface area during decontamination
kg / mA2
0-9.30
0
100
Liquid Waste Produced per
Surface Area
Volume of liquid waste produced per
surface area during decontamination
L/mA2
0-7.67
0
100
Fraction of Waste Sampled
The fraction of the total waste produced
that will be sampled
unitless
O
1
o
0
1
Entry Duration Based on
PPE Level (A)
Duration of each entry for one
personnel donning PPE Level A
hours / entry
0
0
5
Entry Duration Based on
PPE Level (B)
Duration of each entry for one
personnel donning PPE Level B
hours / entry
0
0
5
Entry Duration Based on
PPE Level (C)
Duration of each entry for one
personnel donning PPE Level C
hours / entry
0
0
5
Entry Duration Based on
PPE Level (D)
Duration of each entry for one
personnel donning PPE Level D
hours / entry
0
0
5
Fraction PPE Required (A)
Fraction of all PPE required for one
team that is Level A
unitless
0
0
1
Fraction PPE Required (B)
Fraction of all PPE required for one
team that is Level B
unitless
0
0
1
Fraction PPE Required (C)
Fraction of all PPE required for one
team that is Level C
unitless
0
0
1
Fraction PPE Required (D)
Fraction of all PPE required for one
team that is Level D
unitless
0
0
1
Prep Time per Team per
Entry
Time required for each team to prepare
to enter the contamination site
hours / team *
entry
0
0
2
Personnel Decon Line Time
per Team per Exit
Time spent in the personnel decon line
upon exiting the contamination site
hours / team *
exit
0
0
5
Post-Entry Rest Period
Time required for rest after each site
entry
hours / team *
entry
0
0
2
Number of Respirators per
Person
Number of respirators required per each
person
respirator /
person
0
0
5
B-10
-------
Table B-7 presents the baseline travel parameters that are used as the default values within the tool.
Table B-7: Baseline Travel Parameters
Parameter
Description
Units
Value
Lower Limit
Upper Limit
Number of Personnel per
Rental Car
Number of personnel in one rental car
personnel / car
4-8
1
10
Table B-8 presents the baseline Cost parameters that are used as the default values within the tool.
Table B-8: Baseline Cost Parameters
Parameter
Description
Units
Value
Lower
Limit
Upper
Limit
Cost of Decon Agent
Cost of decontamination agent per volume
$ / L
0.52-
1.58
0
100
Cost per HEPA Sample Analyzed
Cost per HEPA sample analyzed
$ / sample
247.27-
370.00
100
1000
Cost per One HEPA Sock
Cost per one HEPA sock
$ / sample
29
10
50
Cost per One Waste Sample
Cost per one waste sample
$ / sample
20-29
10
50
Cost per Waste Sample Analyzed
Cost per waste sample analyzed
$ / sample
254.19
100
1000
HEPA Vacuum Rental per Day
HEPA vacuum rental cost per day
$ / day
15
10
50
Per Diem
Per diem cost per day plus lodging
$ / day
185 -341
150
500
OSC Hourly Wage
Hourly wage for OSC personnel
$/hour
147-155
80
200
PL-1 Hourly Wage
Hourly wage for PL-1 personnel
$/hour
86- 101
60
105
PL-2 Hourly Wage
Hourly wage for PL-2 personnel
$/hour
102-118
100
125
PL-3 Hourly Wage
Hourly wage for PL-3 personnel
$/hour
124 - 142
120
170
PL-4 Hourly Wage
Hourly wage for PL-4 personnel
$/hour
170-210
165
250
Rentals per Day (IC)
Cost of incident command rentals per day
$ / day
235.42
100
500
Respirator
Cost per one respirator
$ / unit
238
100
500
Cost per One Wipe
Cost per one sampling wipe
$ / sample
19-20
10
50
B-ll
-------
Parameter
Description
Units
Value
Lower
Limit
Upper
Limit
Decon Material Cost per Surface
Area
Cost of decontamination materials per surface area
of site area
$/mA2
1.54-
42.76
0
100
PPE Level A Cost
Cost per one unit of level A PPE
$ / unit
391.59
300
500
PPE Level B Cost
Cost per one unit of level B PPE
$ / unit
144.83
100
300
PPE Level C Cost
Cost per one unit of level C PPE
$ / unit
66.6
0
100
PPE Level D Cost
Cost per one unit of level D PPE
$ / unit
64.32
0
100
Cost for Prep per Entry
Preparation costs for contamination site entry
$ / team *
entry
252 - 345
0
1000
Cost for Personnel Decon Line per
Exit
Personnel decon line costs for contamination site
exit
$ / team *
exit
697 - 822
0
1000
Supplies Cost per Day (IC)
Incident command supplies cost per day
$ / day
1,007.08
500
1500
Cost per Wipe Sample Analyzed
Cost per sample analyzed
$ / sample
231 -640
100
1000
Rental Car Cost per Day
Cost of rental car per day
$ / day
58.00-
64.29
0
500
Material Removal per Mass
Cost of removing material during Source Reduction
based on mass
$ / kg
0.11
0
10
Roundtrip Ticket Cost per Person
Price per one roundtrip ticket to and from
contamination site
$ / ticket
450-518
0
500
B-12
-------
APPENDIX C: USER GUIDE
The following is a user guide for the Wide-Area Decontamination Tool. Upon launching the
application, users will see the screen shown in Figure C-l. Users can select the "Create New
Scenario" button to begin defining a scenario.
WAD Wide Area Decontamination Application
Wide Area Decontamination Application
Environment Protection Agency : Office of Research and Development
/os\
fJL'\
1^1
Create New Scenario Q
f5*
**
Developed by Battelle Memorial Institute Version 0.0.4.0
Figure C-l: Wide-Area Decontamination Tool Home Screen
Once the "Create New Scenario" button has been selected, the user is then able to both define the
scenario parameters which have no values found in the DefineScenario.xlsx workbook and
modify the parameter values which have distributions associated with them in the
ModifyParameters.xlsx workbook. Figure C-2 shows the "Define Scenario" tab, where users can
define the extent of contamination, the initial spore loading, and the breakdown of surfaces for
that particular scenario.
C-l
-------
H ^ WAD Wide Area Decontamination Application
#
DEFINE SCENARIO MOOIFY PARAMETERS
Q Extent of Contamination ^
Area Contaminated
Loading
Indoor Contamination Breakout
Indoor Surface Type Breakout
Outdoor Surface Type Breakout
Underground Surface Type Breakout
Select a parameter to edit from the left
menu...
Developed by Battelle Memorial Institute
Version 0.0.4.0
Figure C-2: Define Scenario Tab
The Define Scenario tab allows users to set values for parameters related to the extent of
contamination for the scenario. Parameters that are unset will be highlighted in red. By default,
all parameters are set except the Area Contaminated and the Toading. Users can select a value
for a parameter using either the slider or by typing a value into the textbox, shown in Figure C-3
below.
WAD
Wide Area Decontamination Application
#
l*
DEFINE SCENARIO
MOOIFV PARAMETERS
e Extent of Contamination
Area Contaminated
Loading
Indoor Contamination Breakout
Indoor Surface Type Breakout
Outdoor Surface Type Breakout
Underground Surface Type Breakout
Extent of Contamination - Area Contaminated
Category: |ndoor
Developed by Battelle Memorial Institute
Version 0.0.4.0
Figure C-3: Area Contaminated Parameter Adjustment
C-2
-------
Users can also select a distribution to describe the parameter values. The various distributions are
shown in Figure C-4 below.
WAD
Wide Area Decontamination Application
1
#
©
DEFINE SCENARIO
MODIFY PARAMETERS
© Extent of Contamination
Area Contaminated
Loading
Indoor Contamination Breakout
Indoor Surface Type Breakout
Outdoor Surface Type Breakout
Underground Surface Type Breakout
Extent of Contamination - Area Contaminated
Constant
Uniform
Beta PERT
Truncated Normal
Truncated Log Normal m"2
Log Normal
Log Uniform
Weibull
Bimodal Truncated Normal
Category: |ndoor
Developed by Battelle Memorial Institute
Version 0.0.4.0
Figure C-4: Define Scenario Distribution List
The selected distribution can be defined using the slider, the textboxes, or the graph itself, as
shown in Figure C-5 below.
IrJL' WAD
Wide Area Decontamination Application
#
a
DEFINE SCENARIO
Extent of Contamination
B*
QfArea Contaminated
Loading
Indoor Contamination Breakout
Indoor Surface Type Breakout
Outdoor Surface Type Breakout
Underground Surface Type Breakout
Category: ,ndoor
Developed by Battelle Memorial Institute
Figure C-5: Parameter Distribution Graph
C-3
-------
Users must set an Indoor, Outdoor, and Underground value for both Area Contaminated and
Loading before running the model. By default, these values are unset. Users can switch between
Indoor, Outdoor, and Underground by using the Category dropdown list, as shown in Figure C-6
below.
Itik WAD
Wide Area Decontamination Application
#
r*
DEFINE SCENARIO
MODIFY PARAMETERS
I
Extent of Contamination
ar
QjArea Contaminated
Loading
Indoor Contamination Breakout
Indoor Surface Type Breakout
Outdoor Surface Type Breakout
Underground Surface Type Breakout
8.0e-8
7.0e-8
o 6.0e-8
"S 5.0e-8
V)
0 4.0e-8
>.
1 3.0e-8
n
ja
£ 2.0e-8
Q.
1.0e-8
Underground
Outdoor
5.0e+6 1.0e+7 1.5e+7 2.0e+7 2.5e+7 3.0e+7 3.5e+7 4.0e+7
Developed by Battelle Memorial Institute
4.5e+7 5.0e+7
Version 0.0.4.0
Figure C-6: Category Dropdown List
Once all parameters have been set, the "Run Scenario" button becomes active, allowing the user
to run the scenario, as seen in Figure C-7.
WAD
Wide Area Decontamination Application
#
m
DEFINE SCENARIO
MOO'IFV PARAMETERS
Extent of Contamination
B'
QjArea Contaminated
r3ft-oading
Indoor Contamination Breakout
Indoor Surface Type Breakout
Outdoor Surface Type Breakout
Underground Surface Type Breakout
Extent of Contamination - Loading
Distribution: Con...
log(cfu / mA2)
Category: |ndoor
Developed by Battelle Memorial Institute
Version 0.0.4.0
Figure C-7: Active Run Scenario Button
C-4
-------
The Modify Parameters tab allows users to adjust values for parameters related to each element
of decontamination, including cost parameters, efficacy, and the decontamination treatment
methods used on each surface, as shown in Figure C-8.
[A] WAD
Incident Command
Characterization Sampling
Source Reduction
Decontamination
Other
Cost per Parameter
Efficacy
Decontamination Treatment Method-
Wide Area Decontamination Application
MODIFY PARAMETERS
Select a parameter to edit from the left
menu...
Developed by Battelle Memorial Institute
Version 0.0.4.0
Figure C-8: Modify Parameters Tab
Users can adjust various personnel, logistic, supplies, and safety parameters. Personnel Required
(OSC) for Incident Command is shown as an example of a personnel parameter in Figure C-9
below.
Personnel Required (PL-1)
Logistic
Characterization Sampling
Source Reduction
Decontamination
Developed by Battelle Memorial Institute
¦ 5. WAD
Wide Area Decontamination Application
RUN SCENARIO
i*
DEFINE SCENARIO
MODIFY PARAMETERS
Incident Command •*">
Incident Command - Personnel - Personnel Required (OSC)
Constant
-
Personnel
I 0 •
, 100
Personnel Required (OSC)
Personnel Required (PL-4)
Personnel Required (PL-3)
Value
¦I person / team
Personnel Required (PL-2)
Figure C-9: Example Personnel Parameter
C-5
Version 0.0.4.0
-------
Personnel Overhead Days for Source Reduction is shown as an example of a logistic parameter
in Figure C-10 below.
WAD
Wide Area Decontamination Application
RUN SCENARIO
DEFINE SCENARIO
MODIFY PARAMETERS
Incident Command ^
Source Reduction - Logistic - Personnel Overhead Days
Constant
¦r
Characterization Sampling v
Source Reduction ^
5
~ Personnel
Safety
0 days
* Logistic
Personnel Overhead Days
Mass of Waste per Surface Area
Fraction Surface Area to be Source...
Decontamination v
Other v
Developed by Battelle Memorial Institute Version 0.0.4.0
Figure C-10: Example Logistic Parameter
Wipes per Flour per Team for Characterization Sampling is shown as an example of a supplies
parameter in Figure C-l 1 below.
If'jfc WAD
Wide Area Decontamination Application
MODIFY PARAMETERS
RUN SCENARIO 1
Incident Command v
Characterization Sampling
Characterization Sampling - Supplies - Wipes per Hour per Team
Constant ~
~ Personnel
50
Safety
Supplies
Surface Area per Wipe
v,l°' wipe / (hour *
6 team)
Surface Area per HEPA Sock
Wipes per Hour per Team
HEPA Socks per Hour per Team
Fraction of Wipe Samples to Each 1
Fraction of HEPA Samples to Each ...
-
Developed by Battelle Memorial Institute Version 0.0.4.0 „
Figure C-l 1: Example Supplies Parameter
C-6
-------
Number of Respirators per Person for Decontamination is shown as an example of a safety
parameter in Figure C-12 below.
WAD
Wide Area Decontamination Application
RUN SCENARIO
pi.
DEFINE SCENARIO
MODIFY PARAMETERS
-
Characterization Sampling v
Decontamination - Safety - Number of Respirators per Person
Constant
-
Source Reduction v
Decontamination ^
5
•» Logistic
~ Personnel
Value respirator/
1 person
Safety
Number of Respirators per Person
PPE Required (A)
PPE Required (B)
PPE Required (C)
PPE Required (D)
Developed by Battelle Memorial Institute Version 0.0.4.0
Figure C-12: Example Safety Parameter
Users can again choose between multiple distributions, as shown in Figure C-13.
1 'St WAD
Wide Area Decontamination Application
RUN SCENARIO
p
MODIFY PARAMETERS
Incident Command •"»
Incident Command - Personnel - Personnel Required (OSC)
Constant ^
Personnel
Constant
o «
Uniform
1 100
Personnel Required (OSC)
Beta PERT
Personnel Required (PL-4)
Truncated Normal
Personnel Required (PL-3)
1
person / team
Truncated Log Normal
Personnel Required (PL-2)
Log Normal
Log Uniform
Personnel Required (PL-1)
Weibull
* Logistic
Bimodal Truncated Normal
Personnel Overhead Days
Characterization Sampling ^
Source Reduction v
-
Developed by Battelle Memorial Institute Version 0.0.4.0 „
Figure C-13: Modify Parameters Distribution List
Once the scenario parameters have been fully defined, the user can run the scenario using the
"Run Scenario" button. The user can select the number of runs for the model to perform as well
C-7
-------
as set the seeds which allow for repeatability. They can then select the "Run" button to run the
scenario. The Run Scenario modal is shown in Figure C-14 below.
&
Incident Command
Logistic
Characterization Sampling
Source Reduction
Decontamination
Developed by Battelle Memorial Institute
Wide Area Decontamination Application
MODIFY PARAMETERS
Incident Command - Personnel - Personnel Required (OSC)
Personnel Required (PL-4)
Run Scenario
Number of Runs Seed 1 Seed 2
100 12345 678910
Personnel Required (PL-3)
1 10 100 1000
Personnel Required (PL-2)
Job Status: Unknown
Personnel Required (PL-1)
RUN CANCEL
Version 0 0.4.0
Figure C-14: Run Scenario Modal
Once the scenario has been successfully run, the Job Status will say "Completed". The "View
Results" button will then be available for users to view the results of the completed scenario run,
as shown in Figure C-15 below.
WAD
Incident Command
Personnel Required (PL-4)
Personnel Required (PL-3)
Personnel Required (PL-2)
Personnel Required (PL-1)
Logistic
Characterization Sampling
Source Reduction
Decontamination
Developed by Battelle Memorial Institute
Wide Area Decontamination Application
p?
MODIFY PARAMETERS
Incident Command - Personnel - Personnel Required (OSC) Constant
Run Scenario
1 10 100 1000
Job Status: Completed
VIEW RESULTS CANCEL
Version 0.0.4.0
Figure C-15: Completed Job Status
C-8
-------
The results dashboard displays various values averaged over all realizations run as well as a cost
breakdown and time breakdown by element. From this dashboard, users can select to view the
results summary by selecting the "Summary" button, they can return to the parameter definitions
using the "View Parameters" button, they can re-run the job by selecting the "Run Job Again"
button, or they can export the results to an xlsx by selecting the "Export Results" button, as
shown in Figure C-16 below.
SUITS-
$2,315,732.8
0
Average Total Cost
747.87 mA2
Average Total Area
Contaminated
15.04
Average Total
Workdays
3.00
Average Number of
Cost Breakdown By Element
Workday Breakdown By Element
45.04
Average Number of
Days Spent on Setup
and Teardown
| Pre Decon Characterization Sampling
| Post Decon Characterization Sampling
I Source Reduction
Decontamination
100
Number of
Realizations
Pre Decon Characterization Sampling
Post Decon Characterization Sampling
Source Reduction
Decontamination
Actions
SUMMARY ¦ VIEW PARAMETERS ¦ RUN JOB AGAIN ¦ EXPORT RESULTS
Developed by Battelle Memorial Institute
Figure C-16: Results Dashboard
The results summary page allows users to generate different histograms and scatter plots based
on the parameters they choose. An example scatter plot of total cost vs element cost is shown in
Figure C-17 below.
C-9
-------
~
PEFINfi SCSI*ARIO
Wide Area Decontamination Application
1 MODIFY PARAMETERS
Output Statistics
I Total Cost vs. Phase Cost
StdDev 79143.75117963666
Total Cost
Mean 2315732.8
Maximum 2526470
Std Dev 117779.49438384057
Developed by Battelle Memorial Institute
• g \% *"•*
•• • IV*
• •• • \
• • • • •«
2000000 %
400000 450000 500000 550000 600000 650000 700000 750000
Version 0.0.4.0
Figure C-17: Results Summary Scatterplot
The results summary page also allows users to view results by realization, as shown in Figure C-
18 below.
11 WAD
Wide Area Decontamination Application
RUN SCENARIO |
(V
MODIFY PARAMETERS
1
VIEW RESULTS
Realization Comparison
r Building
All
. Run Number
~ 1
Pre Decon Characterization
Sampling Results
Residential Building
Commercial Building
Run 1 ©
Industrial Building
Outdoor Underground
Work Days
0.13372351220716508
0.5396820941263976
0.051632381210233294
0 0
On Site Days
0.13372351220716508
0.5396820941263976
0.051632381210233294
0 0
Lab Days
Phase Cost
Post Decon Characterization
Sampling Results
4.509750958580463
37068
7 990672641679379
107574
3.7737730682398984 3.6894485175218072 3.8899151120752213
19347 4760 4760
Work Days
0.22320259371429135
0.2364734404245142
0.08676012801496127
0 0
On Site Days
Lab Days
Phase Cost
Total Characterization
Sampling Results
0.22320259371429135
5.34831434181679
58686
0.2364734404245142
5.18491045785847
49810
0.08676012801496127
3.898086795424347
29271
0 0
0 0
0 0
Work Days
On Site Days
Developed by Battelle Memorial Institute
0.35692610592145646
0.35692610592145646
0.7761555345509118
0.7761555345509118
0.13839250922519458
0.13839250922519458
0 0
0 0
Figure C-
18: Results by Realization
Finally, users can export their results to
a xlsx file by selecting the "
Export Results" I
Version 0.0.4.0
file will be generated and automatically downloaded, as shown in Figure C-19.
C-10
-------
Fs&] WAD
Wide Area Decontamination Application
$2,315,732.8
0
Average Total Cost
MODIFY PARAMETERS
747.87 mA2
Average Total Area
Contaminated
VIEW RESULTS
3.00
Average Number of
Decontamination
Iterations
Cost Breakdown By Element
Workday Breakdown By Element
I Pre Decon Characterization Sampling
I Post Decon Characterization Sampling
I Source Reduction
Decontamination
I Pre Decon Characterization Sampling
I Post Decon Characterization Sampling
I Source Reduction
, Decontamination
45.04
Average Number of
Developed by Battelle Memorial Institute
100
Actions
Version 0.0.4.0
Figure C-19: Exported Results
C-ll
-------
APPENDIX D: REDUNDANT BIODECONTAMINATION
COMPENDIUM COLUMNS
The following table lists the columns that were removed from the BioDecontamination
Compendium as they were deemed redundant.
Table D-l: Columns Removed from the BioDecontamination Compendium for
Redundancy
Column Name
Description
Equivalent Column
Loading
Target number of spores the surface is initially
contaminated with pre-treatment
LoadingNum
ConcDose
Concentration of the active decontamination agent in the
treatment
ConcDoseNum
Temp
Temperature of the environment where decontamination
is performed
TempNum
RH
Relative humidity of the environment where
RHNum
decontamination is performed
ContTime
Amount of time that a surface is exposed to a treatment
method
ContTimeNumMin
Total App
Total number of applications of decontamination
Similar column was
calculated in a later step
SurfMed
Material treated
Similar column was
calculated in a later step
D-l
-------
APPENDIX E: UNRELATED BIODECONTAMINATION
COMPENDIUM COLUMNS
The following table lists the columns that were removed from the BioDecontamination
Compendium as they were deemed unrelated to the analysis.
-------
Table E-l: Columns Removed from the BioDecontamination Compendium Due to Being
Unrelated to the Analysis
Column Name
Description
EntryDate
Date that data was extracted from the reference
EncRec
Endnote record number
Phys State
Physical state of the surface material
GrimeDirt
Description of dirt or grime if present on the surface
ContTimeDesc
Description of the contact time
InocMeth
Method used to add spores to a surface
SampMeth
Method used to sample a surface after decontamination
AppMethNote
Description of the application method
Strain
Genus species and strain of spore decontaminated
ConcDoseCtrl
Range that the concentration dose falls within
TempCtrl
Range that the environment temperature falls within
RHCtrl
Range that the environment relative humidity falls within
VendProd
Name of the decontamination agent bv the vendor
ContTimeUn
Units of the contact time
EffGreater
Indicates if efficacy is reported as ">=EFF"
MatComp
Description of the decontamination method impact on a surface
aesthetic or functionality
VendProdDeconAgent
'VendProd" + "DeconAgent' columns
VendProdDeconAgentSurfMed
'VendProd" + "DeconAgent' + "SurfMed' columns
Entry order
Order in which records were entered
RinsateLess
Indicates if rinsate is reported as "< Rinsate"
WaterRinse
Indicates if water rinse was used
VolAppDenUn
Units of the volume divided by the coupon area
V endProdDeconAgent AppMeth
'VendProd" + "DeconAgent' + 'AppMeth" columns
Surface
'SurfMed" cleaned using a lookup table in the compendium
TempNumCheck
Boolean indicating if the 'Temp" value is a number
ConcDoseNumCheck
Boolean indicating if the 'ConcDoseNum" value is a number
ContTimeNumCheck
Boolean indicating if the 'ContTimeNum" value is a number
ContTimeNum
Boolean indicating if the 'Temp" value is a number
ContTimeNumHrs
Contact time converted to hours
LoadingNumCheck
Boolean indicating if the 'LoadingNum" value is a number
RHNumCheck
Boolean indicating if the 'RHNum" value is a number
DeconMethod
'AppMeth" cleaned using a lookup table with specific decon agents
noted
VolAppDen(L/mA2)
Density of the volume of decontamination agent applied in L/mA2
PosCalc
Calculates the number of 'Positives" if one is not listed
LposRecCalc
Calculates the 'LposRec" for all records that don't provide one as the
efficacy if'EffMeas' is 'LR' and 'EffGreater' is '>' or '>='
CT*
Concentration multiplied bv contact time
CTUn
Units of the concentration multiplied bv contact time
Notes:
* Compendium documentation implies that CT is the concentration multiplied by the contact time. A
value is given for this variable for 378 records. Of these records, six have values that are identical to the
contact time with the same units. The remaining 372 have zeroes and no units provided. Therefore, this
E-2
-------
column was deemed unusable as the data did not imply the same definition given within compendium
documentation.
E-3
-------
APPENDIX F: SURFACE TYPE LOOKUP TABLES FOR
INTERIOR SURFACES
The following tables show the lookup tables used to categorize the representative surface names
by interior surface type. Note these are for indoor scenarios only.
Table F-l: Indoor Scenario - Interior Walls Surfaces Lookup Table
Interior Walls Surfaces
Any Painted Surface
Cellulose Insulation
Cement
Cinder Block
Concrete
Decorative Laminate
Drywall
Fiberglass Wall Paneling
Glass
Painted Cinderblock
Painted Dry Wall
Painted Wallboard
Plastic Walls
Plywood
Stainless Steel
Treated Wood
Wallboard
Wallboard Paper
Brick
Wood
Plate Glass
Tyvek
F-l
-------
Table F-2: Indoor Scenario - Carpeted Floors Surfaces Lookup Table
Carpeted Floors Surfaces
Carpet
Industrial Carpet
Loop-pile Carpet
Nylon Carpet
Office Carpet
Woven Carpet
F-2
-------
Table F-3: Indoor Scenario - Non-Carpeted Floors Surfaces Lookup Table
Non-Carpeted Floors Surfaces
Cement
Ceramic
Concrete
Decorative Laminate
Granite
Grimed and Washed Tile
Grimed Tile
Hardwood
Laminate
Linoleum
Rubber Flooring
Stainless Steel
Tile
Treated Wood
Vinyl Tile
Vinyl Flooring
Wood
Wood Laminate
Wood Tiles
Grimed Concrete
Painted Concrete
Table F-4: Indoor Scenario - Ceilings Surfaces Lookup Table
Ceiling Surfaces
Acoustic Ceiling Tiles
Ceiling Tile
Cement
Concrete
Stainless Steel
F-3
-------
Table F-5: Indoor Scenario - HVAC and Duct Work Surfaces Lookup Table
HVAC/Duct Work Surfaces
Biofilm Covered Copper Pipe
Biofilm Covered PVC Pipe
Carbon Steel
Fiberglass Lined HVAC Duct
Galvanized Metal
Galvanized Metal HVAC Duct
Galvanized Steel
Metal Ductwork
Polyvinyl Chloride
Stainless Steel
Steel
Wiring Insulation
F-4
-------
Table F-6: Indoor Scenario - Miscellaneous Surfaces Lookup Table
Miscellaneous Surfaces
Aluminum
Butyl Rubber
Chair Back
Chair Seat
Cork Boards
Cotton Cloth
Desktop
Epoxy
Filing Cabinet
Food Packaging Material (Presumably Plastic)
Keyboard
Mylar
Nylon
Office Air
Paint
Painted Canvas
Paper
Particle Board
Plastic
Plywood
Polycarbonate
Polyethylene
Polyolefin
Polypropylene
Polystyrene
Polyurethane
Porcelain
Silk Fabric
Teflon
Vinyl Seating
Painted Paper
F-5
-------
APPENDIX G: SURFACE TYPE LOOKUP TABLES FOR
EXTERIOR SURFACES
The following tables show the lookup tables used to categorize the representative surface names
by exterior surface type. Note these are for outdoor scenarios only.
Table G-l: Outdoor Scenario - Exterior Walls Surfaces Lookup Table
Exterior Walls Surfaces
Brick
Cement
Cinder Block
Glass
Painted Cinder Block
Plate Glass
Treated Wood
Tyvek
Table G-2: Outdoor Scenario - Roofing Surfaces Lookup Table
Roofing Surfaces
Asphalt
Cement
Ceramic
Galvanized Metal
Galvanized Steel
Wood
Wood Tiles
Treated Wood
Grimed Wood
G-l
-------
Table G-3: Outdoor Scenario - Flooring and Pavement Surfaces Lookup Table
Outdoor Flooring and Pavement Surfaces
Asphalt
Asphalt Paving
Cement
Concrete
Deck Wood
Rough Surface Patio Tiles
Rough-Cut Wood
Smooth Surface Patio Tiles
Tile
Treated Wood
Wood Laminate
Wood Tiles
Grimed Concrete
Painted Concrete
Wood
Grimed Wood
Table G-4: Outdoor Scenario - Water Lookup Table
Water
Natural Water
Water
Table G-5: Outdoor Scenario - Topsoil and Vegetation Lookup Table
Topsoil and Vegetation
Arizona Test Dust
Topsoil
G-2
-------
Table G-6: Outdoor Scenario - Miscellaneous Surfaces Lookup Table
Miscellaneous Surfaces
Any Painted Surface
Chair Back
Chair Seat
Cotton Cloth
Nylon
Painted Aluminum Alloy
Painted Canvas
Painted Steel
Painted Metal
Particle Board
Plastic
Plate Glass
Plywood
Polycarbonate
Polyolefin
Polystyrene
Polyurethane
Polyvinyl Chloride
Silk Fabric
Stainless Steel
Steel
Teflon
Tire
Vinyl Seating
Grimed Steel
Carbon Steel
Aluminum
G-3
-------
APPENDIX H: SURFACE TYPE LOOKUP TABLES FOR
UNDERGROUND SURFACES
The following tables show the lookup tables used to categorize the representative surface names
by underground surface type. Note these are for underground scenarios only.
Table H-l: Underground Scenario - Interior Walls Surfaces Lookup Table
Interior Walls Surfaces
Any Painted Surface
Cellulose Insulation
Cement
Cinder Block
Concrete
Decorative Laminate
Drywall
Fiberglass Wall Paneling
Glass
Painted Cinder Block
Painted Dry Wall
Painted Wallboard
Plastic Walls
Plate Glass
Plywood
Stainless Steel
Tile
Treated Wood
Wallboard
Wallboard Paper
Brick
Wood
Grimed Wood
Tyvek
H-l
-------
Table H-2: Underground Scenario - Carpeted Flooring Surfaces Lookup Table
Carpeted Flooring Surfaces
Carpet
Industrial Carpet
Loop-Pile Carpet
Nylon Carpet
Office Carpet
Woven Carpet
Table H-3: Underground Scenario - Non-Carpeted Flooring Surfaces Lookup Table
Non-Carpeted Flooring Surfaces
Cement
Ceramic
Concrete
Decorative Laminate
Granite
Grimed and Washed Tile
Grimed Tile
Hardwood
Laminate
Linoleum
Rubber Flooring
Stainless Steel
Tile
Treated Wood
Vinyl Tile
Vinyl Flooring
Wood
Wood Laminate
Wood Tiles
Asphalt
Asphalt Paving
Grimed Concrete
Painted Concrete
Grimed Wood
H-2
-------
Table H-4: Underground Scenario - Ceilings Surfaces Lookup Table
Ceilings Surfaces
Acoustic Ceiling Tiles
Ceiling Tile
Cement
Concrete
Stainless Steel
Table H-5: Underground Scenario - HVAC and Duct Work Surfaces Lookup Table
HVAC/Duct Work Surfaces
Biofilm Covered Copper Pipe
Biofilm Covered PVC Pipe
Carbon Steel
Fiberglass Lined HVAC Duct
Galvanized Metal
Galvanized Metal HVAC Duct
Galvanized Steel
Metal Ductwork
Polyvinyl Chloride
Stainless Steel
Steel
Wiring Insulation
Table H-6: Underground Scenario - Miscellaneous Surfaces Lookup Tab
Miscellaneous Surfaces
Butyl Rubber
Carbon Steel
Chair Back
Chair Seat
Cotton Cloth
Desktop
Filing Cabinet
Galvanized Metal
Galvanized Metal HVAC Duct
Galvanized Steel
Keyboard
H-3
-------
Miscellaneous Surfaces
Metal Ductwork
Nylon
Painted Aluminum Alloy
Painted Steel
Painted Metal
Painted Paper
Particle Board
Plastic
Plate Glass
Polycarbonate
Polyethylene
Polyolefin
Polypropylene
Polystyrene
Polyurethane
Polyurethane Painted Aluminum
Polyvinyl Chloride
Silk Fabric
Stainless Steel
Steel
Teflon
Tire
Treated Wood
Tyvek
Untreated Wood
Vinyl Seating
Wiring Insulation
Grimed Steel
Aluminum
Painted Canvas
Fiberglass Lined HVAC Duct
Wood
Paint
H-4
-------
APPENDIX I: HIGHLY CORRELATED SCATTER PLOTS
The following scatter plots were fit with a uniform x-dependent distribution in order to calculate
an efficacy value.
Liquid Immersion and UndergroundCeilings
0.6 o.s
Loading (CFU/cm~2)
le6
Figure 1-1: Correlation Between Efficacy and Loading for Liquid Immersion and
UndergroundCeilings
Liquid Immersion and OutdoorMisc
2 3 4 5
Loading (CFU/crri'v2)
Figure 1-2: Correlation Between Efficacy and Loading for Liquid Immersion and
OutdoorMisc
1-1
-------
Foam Spray and Pavement
2 3 4 5
Loading (CFU/crm''2)
Figure 1-3: Correlation Between Efficacy and Loading for Foam Spray and Pavement
Foam Spray and Roofing
2 3
Loading (CFU/crn^)
Figure 1-4: Correlation Between Efficacy and Loading for Foam Spray and Roofing
1-2
-------
Foam Spray and OutdoorExterior
3 4 5
Loading (CFUifcnn^2)
Figure 1-5: Correlation Between Efficacy and Loading for Foam Spray and
OutdoorExterior
Liquid Immersion and IndoorMisc
2 3 4 5
Loading (CFU/cm~2)
Figure 1-6: Correlation Between Efficacy and Loading for Liquid Immersion and
IndoorMisc
1-3
-------
Liquid Immersion and IndoorCeilings
0.6 0.8
Loading (CFJ/cm~2)
le6
Figure 1-7: Correlation Between Efficacy and Loading for Liquid Immersion and
IndoorCeilings
Foam Spray and IndoorExterior
9.0 -
_ B.5 -
_l
5 B.O -
i
7.5 -
7.0 -
Figure 1-8: Correlation Between Efficacy and Loading for Foam Spray and IndoorExterior
Loading (CFU/cm
1-4
-------
Foam Spray
0.3 0.4
ConcDose (g/mL)
Figure 1-9: Correlation Between Efficacy and ConcDose for Foam Spray
Liquid Immersion and IndoorMisc
B ¦
•
7 -
*
•
£ 5"
•
• •
_i
•
is 5"
•
E
LU
» *
* *
4 ¦
• •
3-
> : •
*
*
2 -
-0.010 -0.005 0.000 0.005 0.010 0.015 0.020 0.025 0.030
ConcDose (g/mL)
Figure 1-10: Correlation Between Efficacy and ConcDose for Liquid Immersion and
IndoorMisc
1-5
-------
Fumigation and HVAC
io4
fT3
1
I j r
!
[ !'
' * •
L H
i • l!
1
I • I*
<
i r
» • *
%
0
-0.010
-0.005 0.000 0.005 0.010
ConcDose (g/mL)
0.015 0.020
Figure 1-11: Correlation Between Efficacy and ConcDose for Fumigation and HVAC
Fumigation and UndergroundNonCarpet
250
300
350 400
H202 (ppm)
450
500
Figure 1-12: Correlation Between Efficacy and H202 for Fumigation and
UndergroundNonCarpet
1-6
-------
Fumigation and Roofing
250 255 260 265 270 275
H202 (ppm)
280 285
290
Figure 1-13: Correlation Between Efficacy and H2O2 for Fumigation and Roofing
Fumigation and HVAC
250
300
350 400
H202 (ppm)
450
500
Figure 1-14: Correlation Between Efficacy and H2O2 for Fumigation and HVAC
1-7
-------
Fumigation and IndoorNonCarpet
250
300
350 400
H202 (ppm)
450
500
Figure 1-15: Correlation Between Efficacy and H2O2 for Fumigation and IndoorNonCarpet
Foam Spray
0 10
Temp (C)
Figure 1-16: Correlation Between Efficacy and Temp for Foam Spray
1-8
-------
Liquid Suspension
AO
Temp (C)
Figure 1-17: Correlation Between Efficacy and Temp for Liquid Suspension
Liquid Immersion and Underground Carpet
22 23
Temp (£)
Figure 1-18: Correlation Between Efficacy and Temp for Liquid Immersion and
UndergroundCarpet
1-9
-------
Foam Spray and Pavement
Figure 1-19: Correlation Between Efficacy and Temp for Foam Spray and Pavement
Foam Spray and Roofing
Figure 1-20: Correlation Between Efficacy and Temp for Foam Spray and Roofing
1-10
-------
Foam Spray and OutdoorExterior
76B -
7.66 -
7 64 ¦
>,
U
fQ
r 762 -
760 ¦
7.5 B -
22.0
22.1
22.2 22.3
Temp (C)
22.4 22 5
Figure 1-21: Correlation Between Efficacy and Temp for Foam Spray and
OutdoorExterior
Foam Spray and HVAC
24 25
Temp (C)
Figure 1-22: Correlation Between Efficacy and Temp for Foam Spray and HVAC
1-11
-------
Liquid Immersion and IndoorCarpet
22 23
Temp (C)
Figure 1-23: Correlation Between Efficacy and Temp for Liquid Immersion and
IndoorCarpet
Foam Spray and IndoorExterior
24 25
Temp (C)
Figure 1-24: Correlation Between Efficacy and Temp for Foam Spray and IndoorExterior
1-12
-------
Foam Spray and OutdoorExterior
RH f%)
Figure 1-25: Correlation Between Efficacy and RH for Foam Spray and OutdoorExterior
Foam Spray and IndoorExterior
RH f%)
Figure 1-26: Correlation Between Efficacy and RH for Foam Spray and IndoorExterior
1-13
-------
Liquid Wipe
5 6 7 8
ContTime (Minutes)
Figure 1-27: Correlation Between Efficacy and ContTime for Liquid Wipe
Liquid Immersion and UndergroundCeilings
10 12 14 16
ContTime (Minutes)
Figure 1-28: Correlation Between Efficacy and ContTime for Liquid Immersion and
UndergroundCeilings
1-14
-------
Physical and IndoorMisc
6 B 10
ContTime (Minutes)
Figure 1-29: Correlation Between Efficacy and ContTime for Physical and IndoorMisc
Liquid Immersion and IndoorCeilings
10 12 14 16
ContTime (Minutes)
Figure 1-30: Correlation Between Efficacy and ContTime for Liquid Immersion and
IndoorCeilings
1-15
-------
APPENDIX J: VERIFICATION CASE 1 INPUT DATA
The following tables contain the data that were input into the tool to simulate the BOTE scenario
for verification case 1, as well as the source of these data if they were not found in the BOTE
Project report. Note that at the time this verification case was run, Clearance Sampling had not
yet been implemented as an individual element of the model but rather was included within the
Characterization Sampling element.
Table J-l below shows the contamination area and initial spore loading reported in the BOTE
Project report for each scenario type. Note that the decontamination event described in the BOTE
report was only relevant to the indoor scenario type. As such, the outdoor and underground
scenarios were not simulated.
Table J-l: Contamination Area and Loading
Scenario Type
Area Contaminated
(m2)
Loading
(log(CFU/m2))
Indoor
747.87
3.03-8.03
Outdoor
0
0
Underground
0
0
Table J-2 lists the fraction of the total contamination area which each building type makes up.
These values were estimated based on room-specific information found in the text. Note that the
contamination breakout by building type is only relevant to indoor scenarios.
Table J-2: Indoor Contamination Breakout
Indoor Contamination Breakout
Building Type
Value
Residential
0
Commercial
1.0
Industrial
0
Agricultural
0
Religious
0
Government
0
Educational
0
Table J-3 shows the breakdown of each surface type as a fraction of the total contamination area
for the indoor scenario type. Note that the decontamination event described in the BOTE report
was only relevant to the indoor scenario type. As such, the outdoor and underground surface
types were not defined.
J-l
-------
Table J-3: Indoor Surface Type Breakout
Indoor Surface Type Breakout
Surface Type
Value
Walls
0.5
Carpet
0.0625
Non-Carpet
0.0625
Ceilings
0.125
HVAC
0.125
Miscellaneous
0.125
Table J-4 lists the values identified from the BOTE Project report for each Incident Command
parameter in the tool.
Table J-4: Incident Command Parameters
Parameter
Value
Units
Note
Personnel Required (OSC)
1
people / team
-
Personnel Required (PL-4)
0
people / team
-
Personnel Required (PL-3)
0
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Value was estimated as
Personnel Overhead Days
0
days
it was not found in the
text
Personnel Roundtrip Days
2
days
-
Table J-5 and Table J-6 list the values identified from the BOTE Project report for each
Characterization Sampling parameter in the tool.
J-2
-------
Table J-5: Characterization Sampling Parameters
Parameter
Value
Units
Note
Personnel Required (OSC)
0.333
people / team
-
Personnel Required (PL-4)
0
people / team
-
Personnel Required (PL-3)
3
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Personnel Overhead Days
0
days
-
Teams Required
6
teams
-
Fraction of Surface Sampled
0.02-0.14
unitless
-
Entry Duration (A)
1.18
hours / entry * team
-
Entry Duration (B)
1.495
hours / entry * team
-
Entry Duration (C)
1.81
hours / entry * team
-
Entry Duration (D)
2.125
hours / entry * team
-
Number of Respirators per Person
1
respirators
-
Fraction PPE Required (A)
0
unitless
-
Fraction PPE Required (B)
0
unitless
-
Fraction PPE Required (C)
1
unitless
-
Fraction PPE Required (D)
0
unitless
-
Surface Area per Sponge Stick
0.06
m2 / sample
Based on sponge sticks in
text
Surface Area per 37-mm Cassette
0.37
m2 / sample
Based on vacuum socks in
text
Sponge Sticks per Hour per Team
*
sample / hour *
team
-
37-mm Cassettes per Hour per
**
sample / hour *
Team
team
Number of Labs
8
labs
-
Value not found in text;
Lab Throughput Samples per Day
5-84
samples / day
UTR OTD value used as
surrogate
Value not found in text;
Packaging Time per Sample
1.63
minutes / day
UTR OTD value used as
surrogate
Lab Distance from Site
321.87-
3,701.49
kilometers
Values were rounded for
estimation purposes
Time of Result Transmission to
24
hours
Value was estimated as it
IC
was not found in the text
Entry Prep Time
0.6
hours / team * entry
-
Personnel Decon Line Time
0.81
hours / team * entry
-
Parameter
Value
Units
Note
J-3
-------
Post-Entry Rest Period
0.55
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
Table J-6: Additional Sample Parameters
Parameter
Distribution
Mean
Std
Dev
Units
* Sponge Sticks per Hour per Team
Normal
14.51
7.35
sample / hour *
team
**37-mm Cassettes per Hour per
Team
Normal
10.56
7.69
sample / hour *
team
Table J-7 lists the values identified from the BOTE Project report for each Source Reduction
parameter in the tool.
Table J-7: Source Reduction Parameters
J-4
-------
Parameter
Value
Units
Note
Personnel Required (OSC)
0.333
people / team
-
Personnel Required (PL-4)
0.67
people / team
-
Personnel Required (PL-3)
2.33-3.33
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Personnel Overhead Days
0
days
-
Teams Required
6
teams
-
Mass of Waste Removed per
Hour per Team
45.36
kg / hour * team
Value not found in
text; WADE value
used as surrogate
Mass of Waste per Surface Area
9.30
kg /m2
-
Entry Duration (A)
1.18
hours / entry * team
-
Entry Duration (B)
1.495
hours / entry * team
-
Entry Duration (C)
1.81
hours / entry * team
-
Entry Duration (D)
2.125
hours / entry * team
-
Fraction of Surface Area to be
Source Reduced
0.67
unitless
Value estimated based
on information found
in text
Number of Respirators per
Person
1
respirators
Value estimated based
on information found
in text
Fraction PPE Required (A)
0
unitless
-
Fraction PPE Required (B)
0.5
unitless
-
Fraction PPE Required (C)
0.5
unitless
-
Fraction PPE Required (D)
0
unitless
-
Entry Prep Time
0.6
hours / team * entry
-
Personnel Decon Line Time
0.81
hours / team * entry
-
Post-Entry Rest Period
0.55
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
Table J-8 lists the values identified from the BOTE Project report for each Decontamination
parameter in the tool.
Table J-8: Decontamination Parameters
J-5
-------
Parameter
Value
Units
Note
Decon + Drying Days
3-5
days
-
Personnel Required (OSC)
0.33
people / team
-
Personnel Required (PL-4)
0.67
people / team
-
Personnel Required (PL-3)
2.33-3.33
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Personnel Overhead Days
0
days
-
Teams Required
6
teams
-
Entry Duration (A)
1.18
hours / entry * team
-
Entry Duration (B)
1.495
hours / entry * team
-
Entry Duration (C)
1.81
hours / entry * team
-
Entry Duration (D)
2.125
hours / entry * team
-
Number of Respirators per
Person
1
respirators
-
Fraction PPE Required (A)
0
unitless
-
Fraction PPE Required (B)
0.5
unitless
-
Fraction PPE Required (C)
0.5
unitless
-
Fraction PPE Required (D)
0
unitless
-
Volume of Agent Applied
(Fogging or Fumigation)
0.03
L/m3
Value estimated based
on information found in
text
Volume of Agent Applied (Non-
Fogging and Fumigation)
2.56
L/m2
Value estimated based
on information found in
text
Entry Prep Time
0.6
hours / team * entry
-
Personnel Decon Line Time
0.81
hours / team * entry
-
Post-Entry Rest Period
0.55
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
Table J-9 lists the values identified from the BOTE Project report for each Waste Sampling
parameter in the tool.
Table J-9: Waste Sampling Parameters
Parameter
Value
Units
Note
Personnel Required (OSC)
0
people / team
-
Personnel Required (PL-4)
0
people / team
-
Personnel Required (PL-3)
0
people / team
-
Parameter
Value
Units
Note
Personnel Required (PL-2)
0
people / team
-
J-6
-------
Personnel Required (PL-1)
3
people / team
-
Value was estimated as
Personnel Overhead Days
0
days
it was not found in the
text
Teams Required
1
teams
-
Value was estimated as
Fraction of Waste Sampled
1
unitless
it was not found in the
text
Value was estimated as
Entry Duration (A)
0
hours / entry * team
it was not found in the
text
Value was estimated as
Entry Duration (B)
0
hours / entry * team
it was not found in the
text
Value was estimated as
Entry Duration (C)
0
hours / entry * team
it was not found in the
text
Value was estimated as
Entry Duration (D)
0
hours / entry * team
it was not found in the
text
Number of Respirators per
Person
0
respirators
Value was estimated as
it was not found in the
text
Value was estimated as
Fraction PPE Required (A)
0
unitless
it was not found in the
text
Value was estimated as
Fraction PPE Required (B)
0
unitless
it was not found in the
text
Value was estimated as
Fraction PPE Required (C)
0
unitless
it was not found in the
text
Value was estimated as
Fraction PPE Required (D)
0
unitless
it was not found in the
text
Mass per Waste Sample
15.12
kg / sample
-
Volume per Waste Sample
208.20
L / sample
-
Waste Samples per Hour per
5.88-12.5
sample / hour *
-
Team
team
Number of Labs
8
labs
-
Lab Throughput Samples per
Day
5-84
samples / day
Value not found in text;
UTR OTD value used
as surrogate
Parameter
Value
Units
Note
J-7
-------
Packaging Time per Sample
1.63
minutes / day
Value not found in text;
UTR OTD value used
as surrogate
Lab Distance from Site
321.87-3,701.49
kilometers
Values were rounded
for estimation purposes
Time of Result Transmission to
IC
24
hours
Value was estimated as
it was not found in the
text
Analysis Time per Waste
Sample
0.79
hours / sample
-
Entry Prep Time
0
hours / team * entry
Value was estimated as
it was not found in the
text
Personnel Decon Line Time
0
hours / team * entry
Value was estimated as
it was not found in the
text
Post-Entry Rest Period
0
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
Table J-10 lists the values identified from the BOTE Project report for each travel parameter in
the tool.
Table J-10: Miscellaneous Parameters
Parameter
Value
Units
Note
Number of Personnel per Rental
Car
4
people / rental car
Value estimated based
on information found
in text
Table J-l 1 lists the values identified from the BOTE Project report for each Cost parameter in
the tool.
J-8
-------
Table J-ll: Cost Parameters
Parameter
Value
Units
Note
Cost of Decon Agent
1.84
$ / L
Value estimated based
on information found
in text
Cost of 37-mm Cassette Sample
Analyzed
288.00
$ / sample
-
Cost per Sponge Stick Sample
Analyzed
239.00
$ / sample
-
Cost per Solid Waste Sample
Analyzed
254.19
$ / sample
-
Cost per Liquid Waste Sample
Analyzed
254.19
$ / sample
-
Cost per One Waste Sample
20.00-29.00
$ / sample
-
Cost per One 37-mm Cassette
29.00
$ / sample
-
Cost per One Sponge Stick
20.00
$ / sample
-
37-mm Vacuum Rental per Day
15.00
$ / day
Value not found in
text; WADE value
used as surrogate
Supplies Cost per Day (IC)
1,007.08
$ / day
Value not found in
text; WADE value
used as surrogate
OSC Hourly Wage
147.00
$/hour
-
PL-4 Hourly Wage
170.00
$/hour
-
PL-3 Hourly Wage
124.00
$/hour
-
PL-2 Hourly Wage
102.00
$/hour
-
PL-1 Hourly Wage
86.00
$/hour
-
Per Diem
185.00
$ / day
-
Rental Costs per Day (IC)
64.00
$ / day
-
Decon Material Cost per Surface
Area
2.12-42.76
$/m2
-
Rental Car Cost per Day
225.00
$ / day
-
Material Removal per Mass
0.11
$ / kg
Standard MSW
disposal fee
Roundtrip Ticket Cost per
Person
450.00
$ / ticket
-
Respirator
238.00
$ / respirator
Value not found in
text; WADE value
used as surrogate
PPE Level A Cost
391.59
$ / unit
Value not found in
text; UTR OTD value
used as surrogate
PPE Level B Cost
144.83
$ / unit
Value not found in
text; UTR OTD value
used as surrogate
J-9
-------
Parameter
Value
Units
Note
Value not found in
PPE Level C Cost
66.60
$ / unit
text; UTR OTD value
used as surrogate
PPE Level D Cost
64.32
$ / unit
Value not found in
text; UTR OTD value
used as surrogate
Table J-12 lists the efficacy values identified from the BOTE Project.
Table J-12: Efficacy Values
Efficacy in Log Reductions
Fumigation
Liquid Spray
All Other Treatment
Methods
1.98-5.91
5.49
1.98-5.91
J-10
-------
APPENDIX K: VERIFICATION CASE 2 INPUT DATA
The following tables contain the data that were input into the tool to simulate the UTR OTD
scenario for verification case 2, as well as the source of these data if they were not found in the
UTR OTD report. Note that at the time this verification case was run, Clearance Sampling had
not yet been implemented as an individual element of the model but rather was included within
the Characterization Sampling element.
Table K-l below shows the contamination area and initial spore loading reported in the UTR
OTD Project report for each scenario type. Note that the decontamination event described in the
UTR OTD report was only relevant to the underground scenario type. As such, the indoor and
outdoor scenarios were not simulated.
Table K-l: Contamination Area and Loading
Scenario Type
Area Contaminated
(m2)
Loading
(log(CFU/m2))
Indoor
0
0
Outdoor
0
0
Underground
2682.85
5.63-6.13
Table K-2 shows the breakdown of each surface type as a fraction of the total contamination area
for the underground scenario type. Note that the decontamination event described in the UTR
OTD report was only relevant to the underground scenario type. As such, the indoor and outdoor
surface types were not defined.
Table K-2: Underground Surface Type Breakout
Underground Surface Type Breakout
Surface Type
Value
Walls
0.5
Carpet
0.0
Non-Carpet
0.125
Ceilings
0.125
HVAC
0.0
Miscellaneous
0.25
Table K-3 lists the values identified from the UTR OTD report for each Incident Command
parameter in the tool.
K-l
-------
Table K-3: Incident Command Parameters
Parameter
Value
Units
Note
Personnel Required (OSC)
2
people / team
-
Personnel Required (PL-4)
0
people / team
-
Personnel Required (PL-3)
0
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Value was estimated as
Personnel Overhead Days
0
days
it was not found in the
text
Personnel Roundtrip Days
2
days
-
Table K-4 and Table K-6 list the values identified from the UTR OTD report for each
Characterization Sampling parameter in the tool.
Table K-4: Characterization Sampling Parameters
Parameter
Value
Units
Note
Personnel Required (OSC)
0.3
people / team
-
Personnel Required (PL-4)
0
people / team
-
Personnel Required (PL-3)
3
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Personnel Overhead Days
0
days
Value was estimated as
it was not found in the
text
Teams Required
6
teams
-
Fraction of Surface Sampled
7.10 x 10"3- 7.17 x
io-3
unitless
Value was estimated as
it was not found in the
text
Entry Duration (A)
1.18
hours / entry * team
Value not found in text;
BOTE value used as
surrogate
Entry Duration (B)
1.495
hours / entry * team
Value not found in text;
BOTE value used as
surrogate
Entry Duration (C)
1.81
hours / entry * team
Value not found in text;
BOTE value used as
surrogate
Entry Duration (D)
2.125
hours / entry * team
Value not found in text;
BOTE value used as
surrogate
K-2
-------
Parameter
Value
Units
Note
Number of Respirators per
Person
1
respirators
Value was estimated as
it was not found in the
text
Fraction PPE Required (A)
0
unitless
-
Fraction PPE Required (B)
0
unitless
-
Fraction PPE Required (C)
1
unitless
-
Fraction PPE Required (D)
0
unitless
-
Surface Area per Sponge Stick
0.06
m2 / sample
Based on sponge sticks
in text
Surface Area per 37-mm
Cassette
0.09
m2 / sample
Based on vacuum socks
in text
Sponge Sticks per Hour per
Team
*
sample / hour *
team
Value not found in text;
BOTE value used as
surrogate
37-mm Cassettes per Hour per
Team
**
sample / hour *
team
Value not found in text;
BOTE value used as
surrogate
Number of Labs
6
labs
-
Lab Throughput Samples per
Day
5-84
samples / day
-
Packaging Time per Sample
1.63
minutes / day
-
Lab Distance from Site
241.40- 1,931.21
kilometers
Values were rounded
for estimation purposes
Time of Result Transmission to
IC
24
hours
Value was estimated as
it was not found in the
text
Analysis Time per Sponge Stick
0.67
hours / sample
Based on sponge sticks
in text
Analysis Time per 37-mm
Cassette
0.77
hours / sample
Based on vacuum socks
in text
Value not found in text;
Entry Prep Time
0.6
hours / team * entry
BOTE value used as
surrogate
hours / team * entry
Value not found in text;
Personnel Decon Line Time
0.81
BOTE value used as
surrogate
Post-Entry Rest Period
0.5
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
K-3
-------
Table K-5: Additional Sample Parameters
Parameter
Distribution
Mean
Std
Dev
Units
* Sponge Sticks per Hour per Team
Normal
14.51
7.35
sample / hour *
team
**37-mm Cassettes per Hour per
Team
Normal
10.56
7.69
sample / hour *
team
Table K-6 lists the values identified from the UTR OTD report for each Decontamination
parameter in the tool.
Table K-6: Decontamination Parameters
Parameter
Value
Units
Note
Decon + Drying Days
3-5
days
-
Personnel Required (OSC)
0.3
people / team
-
Personnel Required (PL-4)
1-2
people / team
-
Personnel Required (PL-3)
3-6
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
0
people / team
-
Value estimated based
Personnel Overhead Days
0
days
on information found
in text
Teams Required
2
teams
-
Value not found in text;
Entry Duration (A)
1.18
hours / entry * team
BOTE value used as
surrogate
Value not found in text;
Entry Duration (B)
1.495
hours / entry * team
BOTE value used as
surrogate
Value not found in text;
Entry Duration (C)
1.81
hours / entry * team
BOTE value used as
surrogate
Value not found in text;
Entry Duration (D)
2.125
hours / entry * team
BOTE value used as
surrogate
Number of Respirators per
Person
1
respirators
-
Fraction PPE Required (A)
0.5
unitless
-
Fraction PPE Required (B)
0
unitless
-
Fraction PPE Required (C)
0.5
unitless
-
Fraction PPE Required (D)
0
unitless
-
K-4
-------
Parameter
Value
Units
Note
Volume of Agent Applied
(Fogging or Fumigation)
0.33
L/m3
Value estimated based
on information found
in text
Volume of Agent Applied (Non-
Fogging and Fumigation)
0.65 - 1.30
L/m2
Value estimated based
on information found
in text
Entry Prep Time
0.6
hours / team * entry
Value not found in text;
BOTE value used as
surrogate
Personnel Decon Line Time
0.81
hours / team * entry
Value not found in text;
BOTE value used as
surrogate
Post-Entry Rest Period
0.5
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
Table K-7 lists the values identified from the UTR OTD report for each Waste Sampling
parameter in the tool.
Table K-7: Waste Sampling Parameters
Parameter
Value
Units
Note
Personnel Required (OSC)
0
people / team
-
Personnel Required (PL-4)
0
people / team
-
Personnel Required (PL-3)
0
people / team
-
Personnel Required (PL-2)
0
people / team
-
Personnel Required (PL-1)
3
people / team
-
Personnel Overhead Days
0
days
Value was estimated as
it was not found in the
text
Teams Required
1
teams
-
Fraction of Waste Sampled
1
unitless
Value was estimated as
it was not found in the
text
Entry Duration (A)
0
hours / entry * team
Value was estimated as
it was not found in the
text
Entry Duration (B)
0
hours / entry * team
Value was estimated as
it was not found in the
text
Entry Duration (C)
0
hours / entry * team
Value was estimated as
it was not found in the
text
K-5
-------
Parameter
Value
Units
Note
Entry Duration (D)
0
hours / entry * team
Value was estimated as
it was not found in the
text
Number of Respirators per
Person
0
respirators
Value was estimated as
it was not found in the
text
Fraction PPE Required (A)
0
unitless
Value was estimated as
it was not found in the
text
Fraction PPE Required (B)
0
unitless
Value was estimated as
it was not found in the
text
Fraction PPE Required (C)
0
unitless
Value was estimated as
it was not found in the
text
Fraction PPE Required (D)
0
unitless
Value was estimated as
it was not found in the
text
Mass per Waste Sample
16.67
kg / sample
-
Volume per Waste Sample
200
L / sample
-
Waste Samples per Hour per
Team
5.88-12.5
sample / hour *
team
-
Number of Labs
6
labs
-
Lab Throughput Samples per
Day
5-84
samples / day
-
Packaging Time per Sample
1.63
minutes / day
-
Lab Distance from Site
241.40- 1,931.21
kilometers
Values were rounded
for estimation purposes
Time of Result Transmission to
IC
24
hours
Value was estimated as
it was not found in the
text
Analysis Time per Waste
Sample
0.79
hours / sample
-
Entry Prep Time
0
hours / team * entry
Value was estimated as
it was not found in the
text
Personnel Decon Line Time
0
hours / team * entry
Value was estimated as
it was not found in the
text
Post-Entry Rest Period
0
hours / team * entry
-
Personnel Roundtrip Days
2
days
-
Table K-8 lists the values identified from the UTR OTD report for each travel parameter in the
tool.
K-6
-------
Table K-8: Travel Parameters
Parameter
Value
Units
Note
Number of Personnel per Rental
Car
7-8
people / rental car
Value estimated based
on information found
in text
Table K-9 lists the values identified from the UTR OTD report for each Cost parameter in the
tool.
Table K-9: Cost Parameters
Parameter
Value
Units
Note
Cost of Decon Agent
1.58
$ / L
Value estimated based
on information found
in text
Cost per 37-mm Cassette Sample
Analyzed
247.27
$ / sample
-
Cost per Sponge Stick Sample
Analyzed
241.21
$ / sample
-
Cost per Solid Waste Sample
Analyzed
254.19
$ / sample
-
Cost per Liquid Waste Sample
Analyzed
254.19
$ / sample
-
Cost per One Waste Sample
20.00-29.00
$ / sample
Value estimated based
on information found
in text
Cost per One 37-mm Cassette
29.00
$ / sample
-
Cost per One Sponge Stick
20.00
$ / sample
-
37-mm Vacuum Rental per Day
15.00
$ / day
Value not found in text;
WADE value used as
surrogate
Supplies Cost per Day (IC)
1,007.08
$ / day
Value not found in text;
WADE value used as
surrogate
Entry Prep Cost
252.00-
345.00
$ / team * entry
Value not found in text;
BOTE value used as
surrogate
Personnel Decon Line Cost
697.00 -
822.00
$ / team * entry
Value not found in text;
BOTE value used as
surrogate
OSC Hourly Wage
155.00
$/hour
-
PL-4 Hourly Wage
210.00
$/hour
-
PL-3 Hourly Wage
142.00
$/hour
-
PL-2 Hourly Wage
118.00
$/hour
-
PL-1 Hourly Wage
101.00
$/hour
-
Per Diem
341.00
$ / day
-
K-7
-------
Parameter
Value
Units
Note
Rental Costs per Day (IC)
235.42
$ / day
-
Decon Material Cost per Surface
Area
1.54-2.73
$/m2
-
Rental Car Cost per Day
58.00
$ / day
-
Material Removal per Mass
0.11
$ / kg
Standard MSW
disposal fee
Roundtrip Ticket Cost per Person
518.00
$ / ticket
-
Respirator
238.00
$ / respirator
Value not found in text;
WADE value used as
surrogate
PPE Level A Cost
391.59
$ / unit
Value estimated based
on information found
in text
PPE Level B Cost
144.83
$ / unit
Value estimated based
on information found
in text
PPE Level C Cost
66.60
$ / unit
Value estimated based
on information found
in text
PPE Level D Cost
64.32
$ / unit
Value estimated based
on information found
in text
Table K-10 lists the efficacy values identified from the UTR OTD.
Table K-10: Efficacy Values
Efficacy in Log Reductions
Fogging
Liquid Spray
All Other Treatment
Methods
K-8
------- |