COUNTY AND ZIP CODE BLOOD-LEAD DA TA
FOR CHILDREN UNDER SIX YEARS OF AGE
TESTING ABOVE TENMICROGRAMS PER DECILITER
IN REGION 5 STA TES
Contributing Authors;
Thomas M. Brody, Ph.D.
Philip W. King, M.P.A.
Joy C. LeBlang
SEPTEMBER, 1999
U.S. Environmental Protection Agency
Region V
77 W. Jackson Blvd.
Chicago, Illinois
-------
County and Zip Code Blood-Lead Data For Children
Under 6 Years Of Age
Testing Above 10 Micrograms Per Deciliter (u.g/dL)
In Region 5 States.
Background
In response to U.S. EPA Administrator Carol Browner's National Agenda to Protect
Children's Health from Environmental Threats, and President Clinton's Executive Order to
Protect Children from Environmental Health Risks and Safety Risks, U.S. EPA Region 5
convened its own internal working group to address these concerns in late 1997. This
workgroup, known as the "Region 5 Environmental Actions for Children's Health," or
"REACH," was established to organize and coordinate activities within the Region and to
integrate the norm of children's health protection into the daily fabric of the Agency's culture
and process. An early objective of this workgroup has been to set Regional priorities for
children's health protection based on identified "zones of elevated contaminant
concentrations" and identified "zones of disease" that would enable geographically-targeted
outreach and education for primary prevention, and geographically-targeted investigation for
environmental intervention and hazard reduction. This effort ultimately envisions a
standardized regionwide database of children's health endpoints (including blood-lead
poisoning, asthma, cancer, etc.), that can be mapped using Geographic Information System
(GIS) tools. This database would show the number of reported cases of these childhood
diseases across the six states (IL, IN, MI, MN, OH, WI), and could include a variety of
related statistics (e.g., census data, Toxic Release Inventory data, etc.). Such a database
might enable, at a glance, one measure of where children's health may be at greater risk
across the Region, for what diseases, and the absolute numbers of children affected.
A Pilot Project
As an initial pilot project, REACH decided to focus on childhood blood-lead surveillance
data at the county and zip code level. Although no effort to collect this kind of children's
health data across the entire Region had ever been attempted before, it was felt that
childhood blood-lead surveillance data would be a logical place to begin because all six
-------
states in the Region were known to be collecting such data. If all of the State Health
Departments in the Region were found to be collecting the same data in the same manner,
i
and a uniform data set could be achieved, such a milestone might serve at least three
programmatic goals and purposes, including; (1) the identification of specific neighborhoods
for further environmental source investigation, (2) targeted multimedia
enforcement/compliance assistance aimed at reducing known and continuing environmental
sources of lead releases in these areas, and (3) the prioritization of communities for primary
health prevention activities, including public education and outreach. Beyond these
immediate benefits, the creation and maintenance of such a database would also enable the
temporal monitoring of changes in children's blood-lead levels throughout the Region and
thereby serve as a baseline against which future environmental progress could be measured.
Although the pilot project that is the subject of this report achieved neither the uniform data
set nor the program goals outlined above, it did nevertheless move Region 5 forward in
terms of understanding how to approach this task, both for elevated blood-lead and other
children's health endpoints of regionwide interest and concern.
In setting out to inquire whether a uniform regionwide children's blood-lead database would
be feasible, REACH initially contacted the U.S. Centers for Disease Control and Prevention
(CDC) to find out what statewide data this Federal Agency might already have regarding the
prevalence of elevated blood-lead in children. Unfortunately, we learned that the survey data
it collects is aggregated only at the national level, and is not available comprehensively state-
by-state. Consequently, it quickly became apparent that each of the State Health
Departments would need to be contacted individually in order to obtain this information.
After discussing our project plans with State Lead (Pb) Program Managers at a regional
forum convened in early 1998, the State programs expressed support for our proposed
efforts, pledged their cooperation, and helped us to identify the appropriate contact points
in each of their State Health Department's respectively. With this information and
encouragement, U.S. EPA Region 5 then wrote to each department in early 1998, formally
-------
requesting that they share their statewide childhood blood-lead screening data with us. Each
state was asked to provide data showing its total number of reported cases of children under
age 6 with a measured blood-lead level at or above 10 mcg/dL, broken out by county and zip
code, for calendar year 1996, if available. If possible, each agency was also asked to provide
its data in an electronic format for ease of aggregation and processing. Without full
knowledge of the data pool available, we were not able to be any more specific than this in
defining and articulating our data quality objectives going in. Fortunately, each of the six
State Agency's was willing (with minor adjustments to existing data files in a few cases) to
provide us with the requested information. As a result, by early Summer, 1998, U.S. EPA
Region 5 was in possession of a regionwide data set for elevated childhood blood-lead for
the very first time.
Data Quality Limitations
Although each of the State's was able to respond, it soon became apparent, upon examination
of the data, that there were significant differences across the six States in terms of the data
being collected and the manner in which it was being reported. Some of the States provided
us with supporting descriptive information, while others did not. As a pilot project, we
deliberately chose not to pursue metadata from those States that did not otherwise provide
it or offer to provide it, based on the reasoning that we did not want our information request
to become burdensome to the States. We also reasoned that we could always go back and
request additional explanatory information from them at a later time, as needed.
On close inspection, the data was not what we had anticipated. We had assumed that
because of the widespread availability of CDC's blood-lead surveillance guidelines, that all
State surveillance programs would be operating in the same manner. As is often the case
with seminal data collection efforts of this kind, we did encounter some surprises. First, we
observed that none of the State programs had been practicing universal or random blood-lead
screening, so we were limited to a biased sample right from the outset. Second, Illinois, as
an example, included in its data children who had initially tested above elevated levels in
-------
prior years, whereas Wisconsin and Ohio included only new cases diagnosed and reported
in 1996 (or 1997) for the first time. Third, salient data gaps in some areas of some States
•
raised our suspicions that these localities may have been recording and reporting the zip code
from where a test had been taken rather than the zip code of the child's actual place of
residence. Such disparities were also indicated by certain zip codes reportedly having tested
more than 100% of the available (under age six) childhood population. Fourth, although we
had specifically asked for calendar year 1996 screening data, Wisconsin was only able to
provide us with its fiscal year 1996/97 data, and Ohio could only provide the requested data
for calendar year 1997. Fifth, another distortion may have occurred because all of the
children under age six who were tested in 1996 (and/or 1997) were used in computing the
overall screening rates for that year even though all of these children would not normally be
tested in any one single year, but rather spread out over a six year testing period (the 1-2
year old cohort is. the primary target for most screening programs, and the numbers and/or
percentages of infants and 3-5 year olds tested in any given year might fluctuate randomly).
If we had been able to calculate the overall screening rate for the 1 - 2 year old cohort
separately, it would probably have yielded a more accurate and useful measure. Sixth,
another problem occurred when we attempted to match 1996 or 1997 screening data with
census data from 1990 in an effort to estimate screening rates. Because zip code boundaries
can change from one year to the next, children may have been counted in the 1990 census
inside zip codes completely different from where they were reported to have been screened
in 1996, and, these children would have aged over the succeeding six or seven year period
to no longer be a part of the 0 - 6 year age cohort of interest. We did attempt to compensate
for this by using the estimated population data for 1996, but it is still imprecise.
Consequently, we concluded that because of the combined influence of all of these limiting
factors, we (1) had not achieved true data comparability across the States within the
regionwide data set, (2) had not yet established a solid basis for measuring or mapping either
the incidence or prevalence of childhood lead-poisoning by county or zip code, and (3) had
not obtained a precise measurement of screening rates (particularly at the zip code level,
where the greatest distortion potentially occurred). We did decide, however, that it would
-------
nevertheless be worthwhile to render the data in a Geographic Information System (GIS)
format, and to map it by county and zip code, state by state. This would provide us with a
set of statewide maps showing the geographic distribution of the reported cases of children
with elevated blood lead. Although not reflecting actual incidence or prevalence, the GIS
maps would nevertheless provide a useful pointer for where the U.S. EPA might target its
efforts to maximize the expected program benefits. The assumption implicit to this
reasoning is quite simply that we could accomplish the greatest good by targeting those areas
with the greatest known number of lead poisoned children in absolute terms.
With the data in hand, and technical assistance being provided by a visiting Academic
Fellow from Oregon State University, a U.S. EPA Region 5 project team proceeded with the
development of a series of GIS maps depicting the relative geographic distribution of
reported cases of childhood blood-lead poisoning state by state. These maps, prepared in
ARCVIEW and copyrighted by the Fellow, are listed and presented in Appendix A. The
color scheme consistently chosen for all of the maps is intended to have lighter-to-darker
shading representing a better-to-worse situation. U.S. EPA Region 5 also then took the
additional step, based upon projections from the available 1990 U.S. Census population
estimates, of calculating the number of children living within each county and zip code so
that screening rates could be determined to gauge the relative intensity of childhood blood-
lead testing throughout the Region. This was made possible by the States having provided
us with not only the number of reported cases of elevated blood-leads, but the total number
of blood tests performed in each geographic area as well. As a result of this step, the
estimated percentage of children screened (tested) by county for the entire Region was
computed, and can be found listed in Appendix B. This data is also displayed on special
maps which have been included in Appendix A. Estimated screening rates were shown to
vary widely from one zip code to the next, ranging from a high of 86% to a low of 0%'. This
'This number excludes zip codes in Illinois where cases were found to be above 100% as referred to earlier
in this paper.
-------
information may be helpful in terms of identifying where greater screening resources and/or
efforts are needed. By aggregating all of the screening data reported by the States, we were
also able to determine that there were approximately 73,342 reported cases of elevated
blood-leads in children under the age of 6 in Region 5 in the 1996/97 timeframe. This is
perhaps the most accurate estimate acquired or developed to-date, of the actual magnitude
of the childhood lead poisoning problem within this Region, but may still understate the true
magnitude of the problem given the low screening rates that were so commonly observed.
Once the maps had been completed, copies were then distributed to the Lead Program
Managers in each of the six states for their review and comment. We specifically requested
that they check the maps for accuracy to ensure that the data had not been misrepresented in
any way. Verbal permission for the U.S. EPA Region 5 to use the data, and the maps, was
requested, and granted. For all of their many invaluable contributions, we are grateful to
each of these State Agencies for their support. As a final step before releasing this report,
U.S. EPA Region 5 also then completed an internal peer review process which resulted in
a variety of refinements and improvements to the tables and text.
Conclusion
U.S. EPA Region 5 is committed to working in partnership with the States to further reduce
the incidence of childhood lead-poisoning throughout this Region, and to provide for a lead-
safe environment. We also look forward to a continuing cooperation with the States, and the
State Health Departments in particular, as we pursue the additional goal of developing a
regionwide database for the primary children's health endpoints of concern. We consider
this report to represent an early but significant milestone along this road, and hope that it will
encourage continued efforts in this direction.
-------
Appendix A
Figure 1: Illinois Blood Lead Screening Data By County For 1996
Figure 2: Illinois Blood Lead Screening Percentage By County For 1996
Figure 3: Illinois Blood Lead Screening Data By Zip Code For 1996
Figure 4: Illinois Blood Lead Screening Percentage By Zip Code For 1996
Figure 5: Indiana Blood Lead Screening Data By County For 1996
Figure 6: Indiana Blood Lead Screening Percentage By County For 1996
Figure 7: Indiana Blood Lead Screening Data By Zip Code For 1996
Figure 8: Indiana Blood Lead Screening Percentage By Zip Code For 1996
Figure 9: Michigan Blood Lead Screening Data By County For 1996
Figure 10: Michigan Blood Lead Screening Percentage By County For 1996
Figure 11: Michigan Blood Lead Screening Data By Zip Code For 1996
Figure 12: Michigan Blood Lead Screening Percentage By Zip Code For 1996
Figure 13: Minnesota Blood Lead Screening Data By County For 1996
Figure 14: Minnesota Blood Lead Screening Percentage By County For 1996
Figure 15: Minnesota Blood Lead Screening Data By Zip Code For 1996
Figure 16: Minnesota Blood Lead Screening Percentage By Zip Code For 1996
Figure 17: Ohio Blood Lead Screening Data By County For 1997
Figure 18: Ohio Blood Lead Screening Percentage By County For 1997
Figure 19: Ohio Blood Lead Screening Data By Zip Code For 1997
Figure 20: Ohio Blood Lead Screening Percentage By Zip Code For 1997
Figure 21: Wisconsin Blood Lead Screening Data For Fiscal Year 96/97 By County
Figure 22: Wisconsin Blood Lead Screening Percentage For Fiscal Year 96/97 By
County
Figure 23: Wisconsin Blood Lead Screening Data For Fiscal Year 96/97 By Zip Code
Figure 24: Wisconsin Blood Lead Screening Percentage For Fiscal Year 96/97 By Zip
-------
Illinois
Blood Lead
Screening Data
by County
for 1996
TkrCtty of Chicago
manbm 3OJS38 by \tsdj.
Cook County including
\Ofay nmbrn 33,589
Number of Children
<6yrs screening positive
with >=10mcg/dL
I H-19
I 20 - 66
67 - 157
158 - 425
426 - 746
747-1814
1815 - 33589
Prepared far. -&EPA
e Joy C. LeBlang, Sept/98
Source: IL Dent of Health
Figure 1
-------
Illinois
Blood Lead
Screening Data
By County
For 1996
The ft*** Te*d forthe
Oty cfOaago is 37.0)6, far
aOaf>b 10.7^ and fr
ifCoA Caatyinduing
The Parentage of
CJiildmi <6yrs Tested
out of the Total Number
ofCfaldrm <6yrs
jj^ 0.8%-3.7%
I 3.8%-7.3%
7.4%-10.1%
10.2%-14.5%
[" | 14.6%-20.3%
1 20.4% -31.3%
© fay C LtBlang an Sept/98
Source: IL Dept of Health
Figure!
-------
Illinois
Blood Lead
Screening Data
by Zip Code
for 199 6
Number of Children
<6yrs screening positive
with > = 10mcg/dL
22 - 3485
No Data
Prepared for-. $EPA
©Joy C. LeBlang, Sept/98
Source: 1L Dept of Health
Figure3
-------
Illinois
Blood Lead
Screening Data
by Zip Code
for 1996
The Percentage of
Children <6yrs Tested
out of the Total Number
of Children <6yrs
IB 0.0% -4.0%
^4.1%-8.0%
B 8.1% -16.0%
If 16.1%-35.0%
r^] 35.1%-70.0%
[ "| 70.1%-700.0%
| | Not Enough Dtita
Preparedfar.
Source: ZL Dept of Health
Figure 4
-------
Indiana
Blood Lead
Screening Data
by County
for 1996
Number of Children
<6yrs screening positive
with >=10mcg/dL
0-3
4-9
10-17
18-28
\29-68
69 - 288
\289-2218
Prepared for: oEPA
%Jay C. LeBlang
Source: IN Dept of Health
Figure 5
-------
Indiana
EloodLead
Screening Data
by County
for 1996
The Percentage of
Ovlib-m <6yrs Tested
out of the Total Number
(fOaJdrm <6yrs
•102% -1.4%
15%-3.4%
5%-73%
7.6%-122%
\ \ 12.3%-20.6%
120.7% -34.5%
Smmx IN llept of Health
Figure 6
-------
Indiana
Blood Lead
Screening Data
by Zip Code
for 1996
Number of Children
<6yrs screening positive
with > = WmcgfJL
O-l
2-4
5-10
11 -2O
21-45
46-1OO
^^ 1O1 - 350
| \NoData
Prepared for:
« Joy C. Lelilang, Sept/98
Source: IN Dept of Health
Figure?
-------
Indiana
BbodLead
Screening Data
byZipCode
far 1996
The Percentage of
Otildren <6 jay Tested
out of the Tottil Number
of Children <6yrs
^^0.1%-3.0%
^H 3.1%-6.5%
6.696 -12.096
ilii 12.1% -22.0%
rn 22.1%-34.0%
I \ 34.1%-68.3%
| \ Nat Enou^t Data
SourtK INDeptqfHkalih
Figures
-------
Prepared for: &EPA
• Joy C. LcBlang, Sept/98
Source: MN Dept of Health
Michigan
Blood Lead Screening Data
by County for 1996
Number of Ch lldren
<6yrs screening positive
with >=10mcg/dL
0-2
3-10
11 -25
26-80
81 - 301
770
ik.r, 4M •«
•f rw »wl 770>r
vvv~ c.«»t».
Figure 9
-------
Prepared for:
-------
Source. MIDept of Health
Michigan
Blood Lead Screening Data
by Zip Code for 1996
Number of Ch ildrm
<6yrs screening positive
with >= lOmcg/dL
0-4
5-15
16-32
33-53
54- 91
92-190 fj*>
No Data
Figure 11
-------
Preparedfor: 6EPA
9 Joy C. LfBiting, Sept/98
Source: MI Dept tf Health
Michigan
Blood Lead Screening Data
by Zip Code for 1996
The Percentage of
Children <6yrs Tested
out of the Total Number
of Children <6yrs
0.0%-0.1%
0.2%-0.9%
1.0%-2.1%
2.2% -4.3%
I | 4.4% - 9.296
9.396-57.0%
Not Enough Data
Figure 12
-------
Minnesota
Blood Lead Screening Data
by County for 1996
Number of Children
<6yrs screening positive
0-3
4-7
8-14
15-35
36-100
101 - 1797
Pnpamdjor. <$EPA
@ }cy C. LeBlang, Sepl/98
Source: MNDept of Health
Figure 13
-------
Minnesota
BUM Lead Screening Data
by County for 1996
Number of OaJdrm
<6yrs Tested out of
the Total Number
of Children <6yrs
-2.2%
2.21% -35%
3.51% -4-5%
4.51%-65%
6.51%-13.0%
13.1%-24.5%
Source MNDeptofHetdtit
Figure 14
-------
Minnesota
Bipod Lead Screening Data
by Zip Code for 1996
Number of children
<6 yn screening positive
with >= 10 mcg/dL
I 10-4
4-22
22-53
53 -105
105 - 232
232 - 469
No Data
Prepared far: 6EPA
« Joy C. LcRlang, Sept/98
Source: MN Dept of Health
Figure 15
-------
Minnesota
Btood Lead Screening Data
by Zip Code for 1996
The Percentage of
Children <6yrs Tested
out of the Total Number
nf Children <6yrs
0.0% -2.1%
2.2%-5.2%
5.3%-10.6%
10.7%-20.3%
20.4%-38.1%
38.2%-6O.O%
| | NotEnoutfi Data
Pnparedfor
©Joy C LcBlang, Sept/98
Sourte MNDeptafttaMi
Figure 16
-------
Ohio
Blood Lead Screening Data
by County for 1997
Prepared for: 6EPA
e Jay C. LeBlang, Sept/98
Source: OH Dept of Health
Number of Children
<6yrs screening positive
with >=10mcg/dL
0-5
6-2O
21 -90
91 - 205
206-60O
3936
Figure 17
-------
Ohio
Blood Lead Screening Data
by County for 1997
V* lit? of lotah
Pnparedfor.
® Jay C.ltMang, Sept/98
Saatc OHDtpt of Health
The Percentage of
Children <6yrs Tested
out of the Total Numher
oj (hildrvn <6yrs
H 1.0% -3.7%
3.7%-6.1%
6./%-&5%
8.5% -11.7%
11.7%-18.9%
[ 118.9% -28.4%
Figure 18
-------
Ohio
Blood Lead Screening Data
by Zip Code for 1997
Source: OH Dept of Health
Number of Children
<6yrs screening positive
tvith >= 10 mcg/dL
O-6
7-23
24-55
56 - 128
129-260
261 - 499
No Data
Figure 19
-------
Ohio
Blood Lead Screening Data
by Zip Code for 1997
©Joy C LeEltng, Sept/98
Source OHDeptofHedth
The Percentage of
Oiildrai <6yrs Tested
out of the Total Number
ofOuldrm <6yrs
0.4%-4.0%
4.1%-7.0%
7.1%-11.0%
11.1%-16.0%
|TT] 16.I%-3O.O%
\~\3O.1%-86.0%
| \NatEn0ughDuta
Figure 20
-------
Wisconsin
Blood Lead Screening Data
for Fiscal Year 96/97
by County
Number of Children
<6 yrs screening positive
with >=10 mcg/dL
0-5
6-14
1C 9/1
M.J- Jl/
31 - 60
80-3OO
4267
Prepared for. oEPA
«/ C. LeBlang, Sept/98
Source: WI Dept of Health
Figure 21
-------
The Parentage of
Children <6yrs Tested
out of the Total Number
of Children <6yrs
^2.2%-6.0%
1 6.1%-85%
8.6%-115%
gj 11.6% -14.0%
rn 14.1%-20.0%
| | 20.1% -28.0%
I 145.0%
Wisconsin
Blood Lead Screening Data
far Fiscal Year 96/97
by County
Sept/W
Sounc WIXptofHeallh
Figure 22
-------
Wisconsin
Blood Lead Screening Data
for Fiscal Year 96/97
by Zip Code
Number of Children
<6yrs screening positive
with > = 10mcg/dL
0-1
2-3
4-6
7-10
11-15
16-2!
| \NoData
Prepared for. &EPA
By: fey C. LeBlang
Source: WI Dept of Health
Figure 23
-------
Wisconsin
Blood Lead Screening Data
for Fiscal Year 96/97
by Zip Code
The Percentage of
Children <6yrs Tested
out of the Total Number
of Children <6yrs
~ 0.0%-4.5%
| 4.6%-9.0%
9./%-J5.0%
15.1% -23.0%
23.1% -40.0%
I I Not Enough Data
Preparedfor:
©Jov C. LeBlang, Sept/98
Source: WI Dept of Health
Figure 24
-------
Appendix B
State
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
County Name
ADAMS
ALEXANDER
BOND
BOONE
BROWN
BUREAU
CALHOUN
CARROLL
CASS
CHAMPAIGN
CHRISTIAN
CLARK
CLAY
CLINTON
COLES
COOK
CRAWFORD
CUMBERLAND
DEKALB
DEWITT
DOUGLAS
DU PAGE
EDGAR
EDWARDS
EFFINGHAM
FAYETTE
FORD
FRANKLIN
FULTON
GALLATIN
GREENE
GRUNDY
HAMILTON
HANCOCK
HARDIN
HENDERSON
HENRY
IROQUOIS
JACKSON
JASPER
JEFFERSON
Tested
729
365
291
159
66.
230
119
131
153
1298
400
37
122
28
185
137024
136
36
539
174
119
3304
188
68
141
546
97
329
396
148
215
121
97
349
36
123
535
448
1122
70
591
Positive
208
91
51
24
15
18
24
34
19
90
37
6
13
6
28
33589
13
7
77
55
11
221
27
13
7
66
12
19
63
10
52
9
6
114
4
10
142
49
137
7
85
Percent Tested
10.9
31.3
20.3
4.8
14.2
6.5
21.9
8.6
12.3
7.8
11.7
2.5
9.3
0.8
4.5
25.6
7.4
3.1
7.8
11.3
5.8
3.7
10.9
10.1
3.6
28.2
7
9.6
12.1
26
13.7
3.6
12.9
17.7
8.5
16.7
10.8
15.2
23.9
5.9
15.4
-------
State
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
County Name
JERSEY
JO DAVIESS
JOHNSON
KANE
KANKAKEE
KENDALL
KNOX
LAKE
LA SALLE
LAWRENCE
LEE
LIVINGSTON
LOGAN
MCDONOUGH
MCHENRY
MCLEAN
MACON
MACOUPIN
MADISON
MARION
MARSHALL
MASON
MASSAC
MENARD
MERCER
MONROE
MONTGOMERY
MORGAN
MOULTRIE
OGLE
PEORIA
PERRY
PIATT
PIKE
POPE
PULASKI
PUTNAM
RANDOLPH
RICHLAND
ROCK ISLAND
ST CLAIR
SALINE
SANGAMON
Tested
240
77
74
6115
2598
99
741
6031
620
377
75
634
190
357
1600
2061
1921
518
1329
341
51
251
94
80
290
70
512
386
23
144
2169
129
108
393
20
143
27
362
124
2801
6899
625
1925
'ositive
13
5
5
1170
659
11
157
690
106
44
38
102
42
46
113
209
694
75
183
37
9
32
9
8
56
11
107
47
3
34
963
22
14
57
2
32
3
38
17
746
1814
79
418
Percent Tested
11.3
3.6
9
15.5
24.4
2.2
15
9.8
6
26.3
2.2
16.2
6.7
14.5
7.2
16.8
17
11.6
5.2
8,2
4.5
16.9
7.2
7.3
17.6
2.9
17.2
11.7
1.8
2
11.9
6.1
7.5
24.4
6.7
18
4.5
11.6
7.6
19.1
23.5
26.5
10.6
-------
State
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
County Name
SCHUYLER
SCOT?
SHELBY
STARK
STEPHENSON
TAZEWELL
UNION
VERMILION
WABASH
WARREN
WASHINGTON
WAYNE
WHITE
WMTESIDE
WILL
WILLIAMSON
WINNEBAGO
WOODFORD
ADAMS
ALLEN
BARTHOLOMEW
BENTON
BLACKFORD
BOONE
BROWN
CARROLL
CASS
CLARK
CLAY
CLINTON
CRAWFORD
DAVIESS
DEARBORN
DECATUR
DEKALB
DELAWARE
DUBOIS
ELKHART
FAYETTE
FLOYD
FOUNTAIN
FRANKLIN
FULTON
Tested
10
14
142
70
671
889
224
1143
250
178
43
388
283
821
2729
255
2652
109
59
1700
809
36
109
42
18
35
96
845
148
148
172
26
13
121
82
2089
11.7
2917
150
1252
14
44
14
Positive
4
1
23
25
305
92
34
141
51
30
4
30
44
121
425
19
697
8
4
154
27
1
8
1
0
10
12
22
6
27
9
0
1
12
2
98
8
288
16
67
3
3
0
Percent Tested
1.5
2.5
6.6
11.7
13.5
7.2
15.2
13.2
19.5
9.6
3.1
24.4
17.9
13.7
6.5
4.8
9.8
3.3
1.8
5.9
14.8
4.3
9.4
1.2
1.7
2.2
3.1
12.2
7.3
5.3
20.6
1
0.4
5.9
2.5
23.6
3.3
18.4
7.8
23.2
0.9
2.4
0.9
-------
State
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
County Name
GIBSON
GRAN.T
GREENE
HAMILTON
HANCOCK
HARRISON
HENDRICKS
HENRY
HOWARD
HUNTINGTON
JACKSON
JASPER
JAY
JEFFERSON
JENNINGS
JOHNSON
KNOX
KOSCIUSKO
LAGRANGE
LAKE
LA PORTE
LAWRENCE
MADISON
MARION
MARSHALL
MARTIN
MIAMI
MONROE
MONTGOMERY
MORGAN
NEWTON
NOBLE
OHIO
ORANGE
OWEN
PARKE
PERRY
PIKE
PORTER
POSEY
PULASKI
PUTNAM
RANDOLPH
Tested
518
502
462
70
51
259
83
146
827
42
35
8
118
99
86
56
5
760
8
2125
406
295
459
6621
203
223
157
1220
149
86
93
106
12
413
398
13
282
106
622
372
8
773
201
*ositive
13
58
13
2
3
6
3
14
68
7
0
0
9
0
7
0
0
37
0
278
40
9
40
2218
4
3
16
21
/*
z
0
4
7
1
21
12
1
«
14
23
17
1
28
22
*ercent Tested
20.2
8.7
19.5
0.6
1.4
9.8
1.3
4.1
11.8
1.3
1.1
0.4
6.5
4.2
4.1
0.7
0.2
11.8
0.2
5.1
4.6
8.5
4.5
8.8
c
25.9
4.5
17.2
5.1
1.8
7.9
2.9
2.8
26.8
27.4
1.1
19
11.4
5.9
15.6
0.7
34.8
9.3
-------
State
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
County Name
RIPLEY
RUSH,
ST JOSEPH
SCOTT
SHELBY
SPENCER
STARKE
STEUBEN
SULLIVAN
SWITZERLAND
TIPPECANOE
TIPTON
UNION
VANDERBURGH
VERMILLION
VIGO
WABASH
WARREN
WARRICK
WASHINGTON
WAYNE
WELLS
WHITE
WHITLEY
ALCONA
ALGER
ALLEGAN
ALPENA
ANTRIM
ARENAC
BARAGA
BARRY
BAY
BENZIE
BERRIEN
BRANCH
CALHOUN
CASS
CHARLEVOIX
CHEBOYGAN
CHIPPEWA
CLARE
CLINTON
Tested
18
142
2496
217
65
139
64
342
17
7
187
69
36
2566
8
197
215
12
450
495
577
141
65
130
3
54
60
173
90
25
1
177
449
6
986
625
514
136
204
100
52
82
226
Positive
1
27
267
4
4
5
5
27
0
1
7
5
3
264
1
24
3
0
7
24
115
11
8
3
0
0
1
4
0
0
0
3
2
0
150
19
5
2
0
2
0
0
1
Percent Tested
0.8
9.5
11.6
11.9
1.8
8.4
3.2
14.2
1.1
1.1
1.9
5.6
6.2
18.7
0.7
2.5
7.5
1.8
J1.8
25.5
10.1
5.8
3.4
5.2
0.5
8.3
0.7
7
5.9
2
0.2
3.9
4.7
0.6
6.9
16.1
4.2
3.2
10.3
5.6
1.9
3.7
4.3
-------
State
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
County Name
CRAWFORD
DELTA
DICKINSON
EATON
EMMET
GENESEE
GLADWIN
GOGEBIC
GRAND
TRAVERSE
GRATIOT
HILLSDALE
HOUGHTON
HURON
INGHAM
IONIA
IOSCO
IRON
ISABELLA
JACKSON
KALAMAZOO
KALKASKA
KENT
KEWEENAW
LAKE
LAPEER
LEELANAU
LENAWEE
LIVINGSTON
LUCE
MACKINAC
MACOMB
MANISTEE
MARQUETTE
MASON
MECOSTA
MENOMINEE
MIDLAND
MISSAUKEE
MONROE
MONTCALM
MONTMORENCY
MUSKEGON
Tested
3
111
31
145
245
2102
142
9
50
351
366
0
234
3047
423
17
7
157
171
1942
85
10285
1
72
43
4
302
22
105
98
588
96
109
85
483
39
65
46
373
554
14
309
Positive
0
2
1
3
0
132
3
0
1
0
6
0
4
64
7
0
0
2
4
110
6
301
0
1
0
0
16
0
4
0
40
3
8
0
5
0
1
0
16
10
0
53
Percent Tested
0.3
3.6
1.4
1.8
10.7
5.2
7.7
0.7
0.8
10.7
9.2
0
7.9
12.3
8
0.6
0.8
3.6
1.3
10
6.5
19.6
0.9
10.4
0.6
0.3
3.7
0.2
22.8
10.6
1
5.8
1.8
3.9
17.5
2
1
4
3
11.1
2.2
2
-------
State
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MI
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
County Name
NEWAYGO
OAKLAND
OCEANA
OGEMAW
ONTONAGON
OSCEOLA
OSCODA
OTSEGO
OTTAWA
PRESQUE ISLE
ROSCOMMON
SAGINAW
ST CLAIR
ST JOSEPH
SANILAC
SCHOOLCRAFT
SHIAWASSEE
TUSCOLA
VAN BUREN
WASHTENAW
WAYNE
WEXFORD
AITKIN
ANOKA
BECKER
BELTRAMI
BENTON
BIG STONE
BLUE EARTH
BROWN
CARLTON
CARVER
CASS
CHIPPEWA
CHISAGO
CLAY
CLEARWATER
COOK
COTTONWOOD
CROW WING
DAKOTA
DODGE
DOUGLAS
Tested
164
1506
98
33
0
195
14
104
274
8
81
1473
111
666
216
186
779
381
583
1351
7926
118
31
944
239
280
75
11
222
94
118
111
85
29
73
281
44
24
43
162
849
52
103
Positive
0
128
1
0
0
8
1
0
9
0
1
92
1
3
1
1
6
1
15
53
770
2
5
45
5
11
.2
0
31
6
6
2
4
4
4
63
1
0
5
8
57
6
9
Percent Tested
4.3
1.6
4.5
2.1
0
10.6
2.2
6.1
1.4
0.8
6.2
7.5
0.8
11.8
6
29.4
12.6
7.8
8.8
5.9
3.9
4.7
3.7
3.7
9.5
7.9
2.4
2.1
5.3
3.9
4.7
2
4.4
2.5
2.4
6.6
6.2
7.8
4.4
4.2
2.8
3.2
4.2
-------
State
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
County Name
FARIBAULT
FILLMORE
FREEBORN
GOODHUE
GRANT
HENNEPIN
HOUSTON
HUBBARD
ISANTI
ITASCA
JACKSON
KANABEC
KANDIYOHI
KITTSON
KOOCHICHING
LAC QUI PARLE
LAKE
LAKE OF THE
WOODS
LE SUEUR
LINCOLN
LYON
MCLEOD
MAHNOMEN
MARSHALL
MARTIN.
MEEKER
MILLE LACS
MORRISON
MOWER
MURRAY
NICOLLET
NOBLES
NORMAN
OLMSTED
OTTER TAIL
PENNINGTON
PINE
PIPESTONE
POLK
POPE
RAMSEY
RED LAKE
Tested
64
98
132
217
31
14412
112
13
83
136
46
40
19
54
32
28
26
2
84
21
90
30
106
63
90
18
95
145
100
42
60
295
42
208
92
14
69
59
147
43
6781
4
Positive
3
5
22
15
5
1797
5
1
3
19
3
4
2
11
3
3
2
0
24
6
19
4
3
6
7
1
4
8
6
1
8
10
5
25
4
0
7
9
17
7
783
0
Percent Tested
4.9
5.1
4.7
5.8
6.5
15.7
6.3
1
3.3
4.1
4.7
3.4
0.5
11.1
2.5
3.8
3.4
0.5
3.7
4.6
4.2
0.9
24.5
6.8
4.6
0.9
5.4
4.7
3.3
5.2
2.4
17.5
7.1
1.9
2.2
1.3
3.9
6.1
<
4.6
14.6
1
-------
State
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
CountyJ^ame
REDWOOD
RENV.ILLE
RICE
ROCK
ROSEAU
ST LOUIS
SCOTT
SHERBURNE
SIBLEY
STEARNS
STEELE
STEVENS
SWIFT
TODD
TRAVERSE
WABASHA
WADENA
WASECA
WASHINGTON
WATONWAN
WILKIN
WINONA
WRIGHT
YELLOW
MEDICINE
ADAMS
ALLEN
ASHLAND
ASHTABULA
ATHENS
AUGLAIZE
BELMONT
BROWN
BUTLER
CARROLL
CHAMPAIGN
CLARK
CLERMONT
CLINTON
COLUMBIANA
COSHOCTON
CRAWFORD
CUYAHOGA
Tested
63
108
152
12
13
1240
115
191
50
198
271
20
18
105
13
39
202
66
389
118
80
214
184
15
258
879
175
656
671
119
678
225
1137
129
288
2344
751
131
684
111
184
30879
Positive
0
15
22
1
2
63
2
12
8
8
34
0
2
6
1
3
19
5
6
19
2
19
10
0
9
35
3
32
4
2
33
4
12
6
6
201
10
4
47
5
2
3936
Percent Tested
4
6.6
3.6
1.4
0.8
8.3
1.7
4.3
3.9
1.8
9.2
2.6
2.1
5.1
3.5
2.1
17.2
4.1
2.6
10.6
11.5
5.5
2.4
1.5
11.7
8.8
4.3
7.5
17.2
2.7
13.3
7.1
4.4
5.8
9.5
18.9
4.9
4.3
7.5
3.5
4.4
25.7
-------
State
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
County Name
DARKE
DEFIANCE
DELAWARE
ERIE
FAIRFIELD
FAYETTE
FRANKLIN
FULTON
GALLIA
GEAUGA
GREENE
GUERNSEY
HAMILTON
HANCOCK
HARDIN
HARRISON
HENRY
HIGHLAND
HOCKING
HOLMES
HURON
JACKSON
JEFFERSON
KNOX
LAKE
LAWRENCE
LICKING
LOGAN
LORAIN
LUCAS
MADISON
MAHONING
MARION
MEDINA
MEIGS
MERCER
MIAMI
MONROE r
MONTGOMERY
MORGAN
MORROW
MUSKINGUM
NOBLE
Tested
229
281
285
272
447
231
12168
115
353
196
1018
518
10685
262
194
95
146
235
289
64
620
371
904
214
1291
537
948
184
3687
5822
261
3118
526
750
323
40
515
83
4045
186
76
1679
68
'ositive
5
1
4
14
3
7
490
1
0
3
10
10
372
5
5
6
1
6
3
4
7
3
42
4
15
5
30
5
109
563
4
324
9
10
4
0
32
3
108
6
1
41
3
'ercent Tested
4.9
7.7
4.6
4.2
5.2
10.1
13.9
3.2
13.6
2.6
9.2
15.2
13.1
4.4
7.7
8.2
5.3
7.4
13.4
1.5
11.3
14.4
16.2
5.8
7.2
10.4
8.5
4.9
15.3
13.5
8.5
14.7
9.1
6.9
17.2
1.0
6.5
7.1
8.0
14.8
3.1
23.3
6.4
-------
State
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
County Name
OTTAWA
PAULDING
PERRY
PICKAWAY
PIKE
PORTAGE
PREBLE
PUTNAM
RICHLAND
ROSS
SANDUSKY
SCIOTO
SENECA
SHELBY
STARK
SUMMIT
TRUMBULL
TUSCARAWAS
UNION
VANWERT
VINTON
WARREN
WASHINGTON
WAYNE
WILLIAMS
WOOD
WYANDOT
ADAMS
ASHLAND
BARRON
BAYFIELD
BROWN
BUFFALO
BURNETT
CALUMET
CfflPPEWA
CLARK
COLUMBIA
CRAWFORD
DANE
DODGE
DOOR
DOUGLAS
Tested
212
94
583
362
113
798
129
63
783
595
558
456
529
227
3443
6922
1383
360
170
135
262
570
802
578
289
778
144
115
239
854
147
1313
83
221
223
693
220
462
123
Till
437
137
463
Positive
1
4
9
4
4
5
5
2
41
18
12
11
19
3
97
180
38
9
3
0
3
5
30
8
6
20
5
5
3
23
10
88
7
6
5
20
1
25
8
55
20
3
7
Percent Tested
7.1
4.8
20.3
9.2
5.4
7.0
3.7
1.8
7.3
11.1
9.8
7.0
10.1
5.1
11.3
16.0
7.3
5.1
6.1
5.0
28.4
5.4
16.4
6.0
8.2
8.8
7.3
10.8
16.6
23.7
12.1
7.2
7.0
22.6
6.4
13.8
7.5
11.6
8.2
9.0
6.5
6.5
13.6
-------
State
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
County Name
DUNN
EAU QLAIRE
FLORENCE
FOND DU LAC
FOREST
GRANT
GREEN
GREEN LAKE
IOWA
IRON
JACKSON
JEFFERSON
JUNEAU
KENOSHA
KEWAUNEE
LA CROSSE
LAFAYETTE
LANGLADE
LINCOLN
MANITOWOC
MARATHON
MARINETTE
MARQUETTE
MENOMINEE
MILWAUKEE
MONROE
OCONTO
ONEIDA
OUTAGAMIE
OZAUKEE
PEPIN
PIERCE
POLK
PORTAGE
PRICE
RACINE
RICHLAND
ROCK
RUSK
ST CROIX
SAUK
SAWYER
SHAWANO
Tested
418
829
9
791
124
868
427
217
206
169
73
1183
388
1736
78
849
200
202
192
694
1250
452
143
54
21505
316
227
200
1808
388
103
243
454
329
340
3658
235
1898
108
293
414
130
244
Positive
14
26
0
50
3
29
48
8
12
3
1
47
10
137
4
89
11
3
7
37
99
13
7
0
4267
23
15
3
52
9
4
12
10
9
12
287
10
134
3
11
22
3
11
Percent Tested
14.5
11.4
2.2
10.2
15.6
21.0
16.2
14.9
10.8
44.7
5.2
20.6
20.6
14.3
4.5
10.1
13.4
12.1
8.7
10.0
11.6
13.2
16.0
9.1
23.8
8.9
8.6
8.1
13.1
5.9
16.5
8.4
14.3
6.3
26.8
22.1
14.8
14.6
8.3
5.8
9.7
10.8
7.7
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State
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
WI
County Name
SHEBOYGAN
TAYLOR
TREMPEALEAU
VERNON
VILAS
WALWORTH
WASHBURN
WASHINGTON
WAUKESHA
WAUPACA
WAUSHARA
WINNEBAGO
WOOD
Tested
924
148
293
265
60
744
153
876
2507
269
269
1405
574
Positive
96
1
14
8
0
47
1
16
54
17
20
56
16
Percent Tested
10.3
8.0
13.8
11.6
4.6
12.2
13.3
10.0
9.2
6.8
17.2
11.8
8.5
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