United States
             Environmental Protection
             Agency
             Policy, Planning,
             And Evaluation
             (PM-221)
EPA-230-05-89-057
June 1989
&EPA
The Potential  Effects
Of Global Climate Change
On The United States
Appendix G
Health
                                          Printed on Recycled Paper

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THE POTENTIAL EFFECTS OF GLOBAL CLIMATE CHANGE
     \x         ON THE UNITED STATES:

               APPENDIX G  HEALTH
             Editors: Joel B. Smith and Dennis A. Tirpak
         OFFICE OF POLICY, PLANNING AND EVALUATION
           VS. ENVIRONMENTAL PROTECTION AGENCY
                  WASHINGTON, DC 20460

                      MAY 1989

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                             TABLE OF CONTENTS
APPENDIX G: HEALTH


PREFACE	iii

THE IMPACT OF CO2 AND TRACE GAS-INDUCED CLIMATE CHANGES
      UPON HUMAN MORTALITY	1-1
      Laurence S. Kalkstein

COMPUTER SDVfULATON OF THE EFFECTS OF CHANGES IN WEATHER
      PATTERNS ON VECTOR-BORNE DISEASE TRANSMISSION	2-1
      D.G. Haile

THE POTENTIAL IMPACT OF CLIMATE CHANGE ON PATTERNS OF
      INFECTIOUS DISEASE IN THE UNITED STATES 	3-1
      Janice Longstreth and Joseph Wiseman
                                     11

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                                             PREFACE


The ecological and economic implications of the greenhouse effect have been the subject of discussion within
the scientific community for the past three decades.  In recent years, members of Congress have held hearings
on the greenhouse effect and  have begun to examine its implications for public  policy.  This interest was
accentuated during a series of hearings held in June  1986 by the Subcommittee on Pollution of the Senate
Environment and Public Works Committee.  Following the hearings, committee members sent a formal request
to the EPA Administrator, asking the Agency to undertake two studies on climate change due to the greenhouse
effect

        One of the studies we are requesting should examine the potential health and environmental
        effects of climate change. This study should include, but not be limited to, the potential impacts
        on agriculture, forests, wetlands, human health, rivers, lakes, and estuaries, as weU as other
        ecosystems and societal impacts. This study should be designed to include original analyses, to
        identify  and fill  in  where important research gaps  exist,  and to solicit the opinions  of
        knowledgeable people throughout the country through a process of public  hearings and
        meetings.

To meet this request, EPA produced the report entitled The Potential Effects of Global Climate Change on the
United States. For that report, EPA commissioned fifty-five studies by academic and government scientists on
the potential effects of global climate change.  Each study was reviewed by at least two peer reviewers. The
Effects Report summarizes the results of all of those studies.  The complete results of each study are contained
in Appendices A through J.


                              Appendix                       Subject

                                 A                           Water Resources
                                 B                           Sea Level Rise
                                 C                           Agriculture
                                 D                           Forests
                                 E                          Aquatic Resources
                                 F                          Air Quality
                                 G                           Health
                                 H                           Infrastructure
                                 I                            Variability
                                 J                            Policy
GOAL

The goal of the Effects Report was to try to give a sense of the possible direction of changes from a global
wanning as well as a sense of the magnitude. Specifically, we examined the following issues:


        o  sensitivities of systems to changes in climate (since we cannot predict regional climate change, we
           can only identify sensitivities to changes in climate factors)

        o  the range of effects under different warming scenarios

        o  regional differences among effects

        o  interactions among effects  on a regional level


                                                iii

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        o  national effects

        o  uncertainties

        o  policy implications

        o  research needs

The four regions chosen for the studies were California, the Great Lakes, the Southeast, and the Great Plains.
Many studies focused on impacts in a single region, while others examined potential impacts on a national scale.


SCENARIOS USED FOR THE EFFECTS REPORT STUDIES

The Effects Report studies used several scenarios to examine the sensitivities of various systems to changes in
climate. The scenarios used are plausible sets of circumstances although none of them should be considered to
be predictions of regional climate change.  The most common scenario used was the  doubled CO2 scenario
(2XCO2), which examined the effects of climate under a doubling of atmospheric carbon  dioxide concentrations.
This doubling is  estimated to raise average global temperatures by 1.5 to 4.5C by the latter half of the 21st
century. Transient scenarios, which estimate how climate may change over tune in response to a steady increase
in greenhouse gases, were also used. In addition, analog scenarios of past warm periods,  such as the 1930s, were
used.

The  scenarios combined average monthly climate change estimates  for regional grid boxes  from General
Circulation Models (GCMs) with 1951-80 climate observations from sites in the respective grid boxes.  GCMs
are dynamic models that simulate the physical processes of the atmosphere and oceans to  estimate global climate
under different conditions,  such as increasing concentrations of greenhouse gases  (e.g.,  2XCCO-

The scenarios and GCMs used in the studies have certain limitations.  The scenarios used for the studies assume
that temporal and spatial variability do not change from current conditions.  The first of two major limitations
related to the GCMs is their low spatial resolution.  GCMs use rather large grid boxes where climate is averaged
for the whole grid box, while in fact climate may be quite variable within a grid box.  The second limitation is
the simplified way that GCMs treat physical factors such as clouds, oceans, albedo, and land surface hydrology.
Because of these limitations, GCMs often disagree with each other on estimates of regional climate change (as
well as the magnitude of global changes) and should not be considered to be predictions.

To obtain a range of scenarios, EPA asked the researchers to use output from the following GCMs:

        o  Goddard Institute for Space Studies (GISS)

        o  Geophysical Fluid Dynamics Laboratory (GFDL)

        o  Oregon State University (OSU)

Figure 1 shows the temperature change from current climate  to a climate with a doubling of CO2 levels, as
modeled by  the  three GCMs.  The figure includes the GCM estimates for the four  regions.  Precipitation
changes are  shown in Figure 2.  Note the disagreement in the GCM estimates concerning the direction of
change of regional and seasonal precipitation and the agreement concerning increasing temperatures.
                                                                          i
Two transient scenarios from the GISS model were also used, and the average decadal temperature changes
are shown in Figure 3.
                                                 IV

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                    FIGURE 1.  TEMPERATURE SCENARIOS
                GCM Estimated Change in Temperature from 1xCO2 to 2xCO2
Great  Southeast Great California United
Lakes         Plains        States*
Great  Southeast Great California United
Lakes         Plains        States*
Great  Southeast Great California United
Lakes         Plains        States*
                                         GISS

                                         GFDL

                                         OSU
                                                                             * Lower 48 States

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                           FIGURE 2.  PRECIPITATION SCENARIOS
                      GCM Estimated Change in Precipitation from 1xCO2 to 2xCO2
<
Q

LU
ID
l.U
0.8-
0.6-
0.4
0.2
o.o-
-0.2-
-0.4-
.nfi

ANNUAL


m P ^ n
ffl*T~\ w(r-\ isa> WL K&m \
%%
i

       Great  Southeast Great California  United
       Lakes         Plains        States*
 1.0
 0.8
 0.6
 0.4
 0.2
 0.0
-0.2
-0.4
-0.6
                                                           WINTER
     Great  Southeast Great California  United
     Lakes         Plains        States*
 1.0
 0.8
 0.6
 0.4
 0.2
 0.0
-0.2
-0.4
-0.6
  No
Change
  I
               SUMMER
    Great Southeast Great California  United
    Lakes         Plains        States*
                                                       GISS
                                                       GFDL
                                                       OSU
                                                                                    * Lower 48 States

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        4
       3.5
    0   3
       2.5
    UJ
    iu
    O
  1
0.5
  0

  4
3.5
  3
2.5
    5   2
    oc
    UJ  4 .
    CL  1.5
    UJ
        1
       0.5
        0
                                        3.72
                                               2.99
                                   2.47
                                    1.72
                               1.36
                    0.70
                         0.88
              0.30
             YZA
             1980s 1990s 2000s 2010s 2020s 2030s 2040s 2050s
                          TRANSIENT SCENARIO A
                                             1.26
                                           1.02
                           0.59
         0.18
                  0.35
       \/
               1980s     1990s     2000s     2010s
                          TRANSIENT SCENARIO B
                                            2020s
FIGURE 3.
          GISS  TRANSIENTS  "A" AND  "B" AVERAGE
          TEMPERATURE CHANGE FOR LOWER 48 STATES
          GRID  POINTS.
                                vu

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EPA specified that researchers were to use three doubled CO, scenarios, two transient scenarios, and an analog
scenario in then- studies. Many researchers, however, did not nave sufficient tune or resources to use all of the
scenarios.  EPA asked the researchers to run the scenarios in the following order, going as far through the list
as time and resources allowed:

        1. GISS doubled CO2

        2. GFDL doubled CO2

        3. GISS transient A

        4. OSU doubled CO2

        5. Analog (1930 to 1939)

        6. GISS transient B


ABOUT THESE APPENDICES

The studies contained in these appendices appear in the form that the researchers submitted them to EPA.
These reports do not necessarily reflect the official position of the U.S. Environmental Protection Agency.
Mention of trade names does not constitute an endorsement
                                               viii

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THE IMPACT OF CO, AND TRACE GAS-INDUCED
CLIMATE CHANGE^UPON HUMAN MORTALITY
                    by
             Laurence S. Kalkstein
          Center for Climatic Research
             University of Delaware
              Newark, DE 19716
           Contract No. CR81430101

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                                   CONTENTS
FINDINGS  	   1-1

CHAPTER 1: INTRODUCTION	   1-3

CHAPTER 2: PROCEDURE	   1-6
      MORTALITY DATA 	   1-6
      DETERMINATION OF WEATHER/MORTALITY RELATIONSHIPS	   1-6
            Threshold temperatures	   1-9
            Statistical manipulation 	   1-9
            Applying algorithms to weather scenarios	  1-13
            Selection of analog cities	  1-13

CHAPTER 3: RESULTS AND DISCUSSION	  1-18
      HISTORICAL RELATIONSHIPS	  1-18
      SUMMER PREDICTIONS	  1-20
      WINTER PREDICTIONS	  1-26

CHAPTER 4: CONCLUSIONS	  1-32

REFERENCES	  1-34
                                       11

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                                                                                            Kalkstein
                                             FINDINGS1
        The objective of this study is to estimate changes in human mortality attributed to potential changes in
climate.  The major result is an estimation of the number of deaths attributed to the increased incidence of
extreme weather episodes predicted by numerous climate change models.

        The evaluation covers IS cities around the country, and daily mortality data for 11 summer and winter
seasons were extracted and standardized in a manner that facilitates intercity comparisons. The mortality totals
were divided into total and elderly categories, and separate evaluations were developed for all causes of death
and those causes considered to be "weather-related."

        A summary of the results follows:

        1.  Predictions of weather-induced mortality presently occurring during summer were attempted for
            the 15 cities exhibiting significant weather /mortality relationships. It is estimated that 1150 weather-
            induced deaths presently occur during an average summer season in the metropolitan areas of the
            15 cities (these deaths  are standardized totals, adjusted to the demography of a "standard city1).
            St. Louis, New york City,  and Philadelphia rank first, second, and third, respectively, and each city
            presently averages over 100 standard city deaths per summer. The seven highest ranking cities are
            all found in the Midwest or Northeast. Four of the five lowest ranking cities are found in the South,
            with New Orleans and Oklahoma City experiencing virtually  no deaths attributed to weather in
            summer.

        2.  Predicted future weather-induced mortality in summer rises rapidly as the scenarios become warmer
            and if people fail to acclimatize to the increased heat. The total weather-induced mortality estimate
            exceeds 7200 standard city deaths attributed to weather during an average summer under 2XCO2
            conditions and assuming no acclimatization by the population. The magnitude of the increase varies
            significantly between cities.  St. Louis exhibits the  greatest number  of deaths  throughout all the
            wanning scenarios.  Other cities with predicted rapid rises in mortality with future warming are Los
            Angeles, Memphis, Philadelphia, and New York.  New Orleans and Oklahoma City are cities least
            affected by predicted warming.

        3.  Predicted future weather-induced mortality in summer might actually decline in about half of the
            15-city sample if the population fully acclimatizes  to the increasing heat. Nevertheless, a moderate
            rise in mortality is predicted for the 15-city sample if full  acclimatization occurs, and weather-
            induced mortality is predicted to double over present levels even if acclimatization is complete.
            Acclimatized mortality estimates for the 65+ age category are very similar to  the total mortality
            estimates.  By the design of the model, the comparatively modest rise in acclimatized mortality (as
            compared to unacclimatized predictions) parallels the response of people today  who reside in
            southern cities with hot climates.  Southern cities represent analogs of expected climate in northern
            cities, and these warmer cities exhibit fewer numbers of weather-induced deaths in summer. Thus,
            if people in northern cities fully acclimatize to the increased warmth, the rise in weather-induced
            mortality is  predicted  to be more modest.  Estimates of  future mortality assuming partial
            acclimatization (values  midway between full and no acclimatization) indicate sizable increases in
            mortality as the weather became warmer.
        'Although the information in this report has been funded wholly or partly by the U.S. Environmental
Protection Agency under cooperative agreement number CR81430101 at the Center for Climatic Research,
University of Delaware, it does not necessarily reflect the Agency's views, and no official endorsement should
be inferred from it.

                                                1-1

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Kalkstein

        4.   Present-day estimates  of winter mortality indicate that weather-induced deaths are much less
            important in winter than in summer. The results differ from those uncovered in summer regarding
            the relative impact of weather.  Most of the estimated winter deaths occur in regions with relatively
            severe winter climates, while the smallest number of deaths are found in mild weather cities.
            Conversely, in the summer, estimated weather-induced deaths are low in areas with severe summer
            climates.

        5.   Winter unacclimatized, partially acclimatized, and acclimatized predictions indicate that sharp drops
            in mortality are expected if the weather becomes warmer. The unacclimatized results differ from
            those uncovered in summer, when dramatic rises in mortality are predicted. The unacclimatized
            drop in winter may be  related  to fewer numbers of days below the threshold temperature.

        Global warming could have an enormous impact upon human mortality through the 21st century. If the
population does not fully acclimatize, over 7000 deaths attributed to the increasingly harsh weather can occur
in the metropolitan areas of our 15-city sample. This figure is more startling when it is considered that these
numbers correspond to average summer conditions. An analog of the very hot summer of 1980 occurring in the
21st century will no doubt increase weather-induced mortality to a much higher number than 7000.

        Although fully acclimatized predictions are more modest, some general increases are still expected even
under these  conditions. If it is assumed that people partially acclimatize (possibly the most realistic scenario),
the  increases in mortality are larger,  and weather-related deaths may increase by four to five times over present
levels during the summer.
                                                 1-2

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                                                                                             Kalkstein
                                            CHAPTER 1

                                          INTRODUCTION


        The impact of inadvertent climatic changes upon the human population has long been the subject of
speculation.  Although a large  body of literature is devoted to the impact of variable  climate upon the
socioeconomic sector, very little has been done to estimate how predicted changes in climate might affect the
health of the general population.

        The objective of this study is to estimate changes in human mortality attributed to predicted changes in
climate due to increased concentrations of CO2 and other trace gases in the atmosphere. The result will be an
estimation of the number of deaths attributed to the increased incidence of extreme weather episodes predicted
by various climate change models.

        The research presented here addresses two important priorities in climate/health  studies.  First, an
assessment of CO2/trace gas-induced climatic changes upon humans represents a timely and necessary aspect
of air pollution-health  analyses.   The  additional  evaluation of climatic impact,  rather than air pollution
concentration alone, represents an important addition to any pollution/health research.  Second,  it is imperative
that government agencies understand the implications of long-term climatic change  in an attempt to  develop
mitigation policies.  If the environmental impacts of inadvertent climatic change are quantified, regulatory action
may be implemented with greater efficiency.

        The following is a specific list of items addressed by this research:

        1. Fifteen cities will be evaluated (Table 1), and present-day analogs that duplicate their predicted future
climate regimes will be developed.

        2. Weather /mortality relationships for the elderly (greater than 65 years of age) and the total population
will be determined.

        3. Estimates of future mortality assuming climatic warming will be presented. These estimates will be
based on future weather scenarios as predicted by three Goddard Institute For Space Sciences  (GISS) Global
Circulation Models (GCMs).

        There are several unavoidable  limitations to this study. First, this evaluation concentrates on urban
mortality variations. The scarcity of rural  mortality data will  curtail our development of  an  accurate rural
mortality assessment procedure. Unforeseen future population changes and/or regional population shifts might
represent a second limitation. Third, analog cities, used to approximate the future climate of our target cities,
may be very different from the target cities in terms of architectural or structural makeup. Thus the microclimate
within the dwellings of analog and associated target cities may vary.  Fourth, the numerous  interrelationships
between weather, pollution, social factors, morbidity, and mortality are tremendously complex, leading to sharp
disagreements among scholars  involving the  differential impacts of  weather on human health.  This  has
historically discouraged the development of deterministic weather/mortality models, which leads to increased
difficulty with interpretation of results.

        Although no previous study has  attempted to predict the impact of future weather changes on mortality,
considerable work relating to present climate/mortality relationships has been reported (White and Hertz-
Picciotto, 1985; Munn, 1986; Kalkstein and Valimont,  1987).  For example, studies at the Centers for  Disease
Control (CDC) have identified a number of factors that may inhibit the onset of heat stroke, including the
increased use of ah* conditioning, consumption of fluids, and living in well-shaded residences (Kilbourne et al.,
                                                 1-3

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Kalkstein


                            Table 1.  Fifteen Cities Evaluated in This Study
1. Atlanta, GA
2. Chicago, IL
3. Cincinnati, OH
4. Dallas, TX
5. Detroit, MI
6. Kansas City, MO
7. Los Angeles, CA
8. Memphis, TN
9. Minneapolis, MN
10. New Orleans, LA
11. New York, NY
12. Oklahoma City, OK
13. Philadelphia, PA
14. St. Louis, MO
15. San Francisco, CA
1982).  Some researchers have found that many causes of deaths other than heat stroke increase during extreme
weather (Applegate et al., 1981; Jones et al., 1982).  In addition, mortality attributed to weather seems to vary
considerably with age, sex, and race, although there is disagreement among researchers in defining the most
susceptible population group (Oechsli and Buechley, 1970; Bridger et al., 1976; Lye and Kamal, 1977).

        The impact of cold weather is less dramatic than that of hot weather, although mortality increases have
been noted during extreme cold waves (CDC, 1982; Fitzgerald and Jessop, 1982; Callow et al., 1984; Kalkstein,
1984).  Hypothermia is a major contributor to weather-related mortality in winter, but many other causes of
death also increase including influenza, pneumonia, accidents,  carbon monoxide poisoning, and house fires
(National Center for  Health Statistics, 1978).

        A frequent criticism of these studies points to  certain cultural adjustments through time that may have
an impact on weather/mortality relationships, such as the lessened exposure of people to extreme weather owing
to the increased use of air conditioning. Surprisingly, several studies indicate that these cultural adjustments may
have a minimal impact. Ellis and Nelson (1978) have noted that during the past 30 years, mortality during heat
waves in New York City has not changed significantly despite the increased use of air conditioning.  Analysis by
Marmot (197S) supports this finding, and his study covering a 22-year period implied that air conditioning may
be decreasing  excess mortality during initial summer  hot spells only.  Thus it is possible that  people  do not
require direct exposure to hostile external environments to be negatively affected by these environments. The
knowledge that external unpleasant conditions exist might be sufficient to contribute to negative reactions (Ulrich,
1984).

        One of the major questions that must be addressed when evaluating the impact of long-term changes
in weather on human health involves the importance of acclimatization, which represents the increased ability
of humans to withstand  stressful conditions with  repeated  exposure.  Several  studies have evaluated
acclimatization as a factor contributing to heat-related deaths.  Cover (1938) reported that excess mortality
during a second heat wave in any year will be slight in comparison to excess mortality during the first, even if
the second heat wave is unusually extreme. Two possible explanations for this phenomenon are provided. First,
the weak and susceptible members of the population die in the early heat waves of summer, thus lowering the
population of susceptible people who would have died during subsequent heat waves. Second, those who survive
early heat waves become physiologically or behaviorally acclimatized and hence deal more effectively with later
heat waves  (Marmor, 1975).   Findings at the  recent Williamsburg Conference on  Susceptibility to Inhaled
Pollutants support the second idea Reactive subjects responded only at the beginning of the ozone season each
year (spring and summer), and were generally not affected by exposure later in the year (fall).  Rotton (1983)
suggests that geographical acclimatization is also significant, and people moving from a cool to a subtropical
climate will adapt rather quickly, often within two weeks.  However, the population must still make behavioral
and cultural adjustments (Ellis, 1972).  Further support for geographical acclimatization is provided by Kalkstein


                                                1-4

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                                                                                              Kalkstein

et al. (1986), who noted that mortality increased dramatically during heat waves in northern cities, but no
mortality increase was observed in southern cities even under the hottest conditions.

        This report will describe the methodology used in the development of weather-related  mortality
predictions into the future. In addition, results of the empirical evaluation will be presented and interpreted, and
an evaluation of the potential socioeconomic implications will be attempted.
                                                 1-5

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Kalkstein

                                           CHAPTER 2

                                          PROCEDURE


MORTALITY DATA

        A very detailed mortality data base is presently available from the National Center for Health Statistics
(NCHS), which contains records for every person who has died in this country from 1964 to the present (NCHS,
1978).  The data contain information such as cause of death, place of death, age, date of death, sex, and race.
These data were  extracted for the standard metropolitan statistical areas (SMSAs) of all the cities incorporated
in this study for 11 years: 1964-66,1972-78, and 1980 (during intervening years, a sizable amount of information
was missing from many records). The number of deaths each day for each SMSA  was tabulated and divided
into total deaths  and elderly deaths. Thus, the relative sensitivities for both categories could be determined, as
weather probably exerts a differential influence upon mortality between categories.

        Certain causes of death, deemed "weather-related," were factored out and evaluated separately using two
procedures (Table 2). First, weather-related causes of death were subjectively identified after consultation with
Dr. Melvyn Tockman, an epidemiologist from Johns Hopkins University, and Dr. Steven Parnes, head, Division
of Otolaryngology, Albany Medical College. The medical experts examined a listing containing approximately
10,000  causes of death (Department of  Health and Human Services, 1980) and  identified the causes they
considered to be directly or indirectly influenced by weather.  Second, a more objective  method to isolate
weather-related causes was attempted by correlating annual fluctuations for every cause of death for the entire
nation with population-weighted values of monthly mean temperature and precipitation. The population-weighted
procedure for developing weather variables is  used commonly by the National Oceanic and Atmospheric
Administration (NOAA) to estimate national impacts of weather on society; refer to  Warren and LeDuc (1981)
for computational details.

        There is conflicting evidence in the literature about the validity of factoring out weather-related causes
of death.  Many researchers continue to utilize total mortality figures in their analyses,  as  deaths from a
surprisingly large number of causes appear to escalate with more extreme weather (Applegate et al., 1981; Jones
et al., 1982). In an attempt to circumvent this apparent disagreement among researchers, weather-related and
all causes categories were evaluated separately in this study for the total and elderly mortality categories.

        Although they are probably less meaningful for inter-regional comparison than standardized values,
unstandardized mortality values provide a better estimate of the total magnitude of weather's  influence upon
mortality.  The unstandardized values are computed for each city by multiplying the  death rate by the true
population of the city's SMSA (using 1980 census data).


DETERMINATION OF WEATHER/MORTALITY RELATIONSHIPS

        The procedural framework used in this study  for developing and  interpreting  climate/mortality
relationships is outlined in Figure 1, which should supplement the discussion in this subchapter.  Prior to an
evaluation of the effects of future warming on mortality, it is necessary to define the historical relationships
between weather and mortality. This section first describes the procedure to develop historical relationships, and
then outlines the procedure to evaluate future climate/mortality relationships.
                                                1-6

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                                                                                       Kalkstein

               Table 2.  Causes of Death Considered to be Weather Related
 1. Active rheumatic fever
 2. Adverse effect of medicinal agents
 3. Cerebrovascular disease
 4. Complications of medical care
 5. Complications of pregnancy, childbirth, and the puerperium
 6. Contusion and crushing with intact skin surface
 7. Diseases of the arteries, arterioles, and capaillaries
 8. Diseases of the blood and blood-forming organs
 9. Diseases of the digestive system
10. Diseases of the musculoskeletal system and connective tissue
11. Diseases of the nervous system and sense organs
12. Diseases of the skin and subcutaneous tissue
13. Diseases of the veins and lymphatics
14. Effects of foreign body, entering through orifice
IS. Endocrine, nutritional, and metabolic diseases
16. Fractures of the skull, spine, trunk, and limbs
17. Hypertensive disease
18. Influenza
19. Injury to nerves and spinal cord
20. Intracranial injury
21. Ischemic heart disease
22. Neoplasms: benign
23. Neoplasms: malignant
24. Superficial injury
25. Toxic effect of substances of chiefly non-medical source
                                          1-7

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Kalkstein
                         CRUDE DAILY
                          MORTAUTY
                            DATA
                             _W
                       STANDARDIZATION
                    STANDARD CITY DEATHS'
                                         TSS PROCEDURE'
                                          THRESHOLD
                                          TEMPERATURES
                REMOVAL OF DAYS
               WHERE TEMPERATURE
                 DOESNT EXCEED
                   THRESHOLD
RETAIN DAYS WHERE
   TEMPERATURE
EXCEEDS THRESHOLD
                                                  \f
                                        \/
                                            HISTORICAL WEATHER/
                                             MORTALITY MODEL
                                             WITH ASSOCIATED
                                           PREDICTIVE ALGORITHMS
                                  WEATHER
                                  SCENARIOS
                                  (1.2.4,5.7'F
                                ABOVE PRESENT
                                 CONDITIONS)
                                                      ESTIMATES OF
                                                     UNACCUMATIZED
                                                        FUTURE
                                                       MORTAUTY
                                                                                \/
                                                                          DETERMINATION
                                                                               OF
                                                                          ANALOG CITIES
                                              \/
                                             ESTIMATES OF
                                             ACCLIMATIZED
                                               FUTURE
                                              MORTAUTY
                     Figure 1. Procedural framework for climate/mortality analysis.
                                                 1-8

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                                                                                            Kalkstein

Threshold temperatures

        Weather has been demonstrated to have some impact on daily mortality (Figure 2).  During the heat
wave of late July 1980 in New York City,  deaths rose to over 50 percent above normal on the day with the
highest maximum temperature (Kalkstein et al., 1986).  Deaths among the elderly showed similar increases. In
this study, daily changes in mortality were compared to 12 different weather elements which might have some
influence on death rates (Table 3).  One of these elements, a "time" variable (TIME), was also incorporated,
which evaluated the intra-seasonal timing of the weather event. For example, it is hypothesized that a heat wave
in August might have less of an influence than a similar heat wave in June, as the population would be
unaccustomed to the June event. Thus, TIME simply assigns each day a number (e.g., June 1 is 1, June 2 is 2,
July 1 is 31) representing its position in the summer (or winter) season.

        Initial observations of daily deaths versus maximum temperature  suggest that, in summer, weather has
an impact on only the  warmest 10-20 percent of the days; however, the relationship  on those very warm days is
impressive (Figure 3).  Somewhat similar findings were uncovered for whiter, and for certain SMSAs, the coldest
10 percent of days exhibited good weather/mortality relationships.  Data were analyzed for the total and elderly
mortality categories for each SMSA  during summer and winter to compare the maximum temperature on the
day of the deaths, as well as one, two, and three days prior to the day of  the deaths to determine if a lag time
exists between weather and the mortality response.

        A unique aspect of this study involves the determination of a "threshold temperature," which represents
that temperature beyond which mortality significantly increases (Kalkstein and Davis, 1985).  The threshold
temperature is calculated objectively by measuring the dissimilarity of mortality rates above and below a given
temperature (refer to Kalkstein, in press, for a more detailed discussion).  The threshold temperature for total
deaths in New York City, for example, is 92F (Figure 3), and mortality increases dramatically at temperatures
above this level.  This procedure can be repeated for whiter, where the threshold temperature represents the
temperature below which mortality increases.

Statistical manipulation

        Once the threshold has been established, a procedure named "all regression" is used to determine which
combination of weather elements (listed in Table 3) produces the best models ("best" is defined as possessing
the highest R2 value) for days beyond the threshold temperature (Draper and Smith, 1981).  The next step
involves choosing which regression model  (for each combination of weather elements) best represents  the
historical relationships for that city. Complete multiple linear regressions were run for each model, which
included regression diagnostics such as residuals plots and variance inflation factors (VIF) (SAS Institute, 1985).
A high VIF indicates that two or more collinear independent  variables are included in the model. When this
is the case, one of the collinear variables is omitted from the model; the remaining variable explains a greater
amount of the variance in mortality than the omitted variable. Because of this collinearity problem, CDH and
maximum temperature are virtually never included in the same regression.  The final selected model must meet
the following criteria:

        1. All included independent variables must be significant at the 0.05 level or better;

        2. The VIF for all independent  variables must be less than 5.00    (SAS Institute, 1985);

        3. The residuals plots must indicate randomly distributed residuals;

        4. The R2 value of the final  model must exceed 0.100.

An "adjusted" R2 statistic was used in this study, which accounts for degrees of freedom in the regression model
(Draper and Smith, 1981). Regression models possessing low degrees of freedom often exhibit inflated R2
                                                1-9

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Kalkstein

                    Table 3. Weather Variables Used in the Mortality Study



                          MAXIMUM TEMPERATURE (MAXT)

                           MINIMUM TEMPERATURE (MINT)

                            MAXIMUM DEWPOINT (MAXTD)

                            MINIMUM DEWPOINT (MINTD)

                   COOLING DEGREE HOURS (CDH): SUMMER ONLY*

                   HEATING DEGREE HOURS (HDH): WINTER ONLY**

                               3AM VISIBILITY (VISAM)

                               3PM VISIBILITY (VISPM)

                              3AM WIND SPEED (WNDAM)

                              3PM WIND SPEED (WNDPM)

                                 CLOUD COVER  (CLD)

                                     TIME (TIME)


*  CDH represents a measure of the day's warmth, and is calculated as follows:

                                     N
                              CDH = E (T-90), where T > 90
                                     i=l

   T represents the hourly temperature and N represents total hours with temperature above 90.

** HDH represents a measure of the day's coldness, and is  calculated as follows: .

                                     M
                              HDH = E (32-T), where T < 32
                                     i=l

   T represents the hourly temperature and M represents total hours with the temperature below 32F.
                                         1-10

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                                                        Kalkstein

    190



    170



    150



    130
     90



     70
     50
                                                   100
                           90
                               -j
                               m
                           80  5
                           70
                                                       m
                                o
                               n
                           60  ^
                                                  50
       10 11 12  13  14 15 16 17 18 19 20 21 22 23 24


                     DATE (JULY  1980)
 TOTAL MORTALITY
-ELDERLY MORTALITY	TEMPERATURE
 Figure 2. Mortality during a 1980 heat wave in Ne* York City (Kalkstein et al., 1986).



                           Ml

-------
Kalkstein
   J  250


   DC  225
   O
   ^.  200


   H  175
   O

   Q  150
   DC
   |  125


   <  100


   fe   75
            15      20     25     30      35

               MAXIMUM TEMPERATURE (C)
    Figure 3. Daily summer-season standardized mortality vs. maximum temperature: New York City.



                             1-12

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                                                                                             Kalkstein


values, and the use of an adjusted R2 statistic minimizes this problem. These guidelines insured some degree
of quality control in the regression modeling, as thousands of regressions were computed to determine the best
models.

Applying algorithms to weather scenarios

    With historical relationships established, the next step is an attempt to estimate changes in mortality which
might occur with  predicted climatic warming.   This  study utilizes three GCM transient runs provided by
NCAR/EPA (Jenne, 1987), and future predictions of climate have been developed for the cities in this study.
The three runs are GISS transient A1 (covering a 17-year period 30 years after the base period), GISS transient
Aj (covering a 17-year period 60 years after the base period), and GISS 2XCO2.

    As described earlier, the base period for mortality includes a 17-year period extending from 1964 to 1980
(note that only 11 years  of mortality data were available through this period).  Thus the GISS transient A1
scenario will estimate mortality for the period 1994-2010. The GISS transient Ag scenario will estimate mortality
for the period 2024-2040. The GISS 2XCO,  scenario will assume double CO, conditions occurring during the
base period 1964-1980.  New mortality estimates for  each city were created for each scenario by using  the
algorithms developed from  the historical data

    When measuring  the impact of  warming on future mortality, the question of acclimatization must be
considered.  Will people within each  city respond to heat as they do today? Or will their reactions be similar
to those of people who presently live in hotter climates?  There is much disagreement in the literature concerning
human acclimatization to changing weather.  Some research indicates that acclimatization responses are very
rapid (Marmor, 1975; Rotton, 1983), others think it is a much slower process (Kalkstein and Davis, 1985; Ellis,
1972), and a few imply that virtually no acclimatization occurs at all (Steadman, 1979). It is obvious that the full
range of possibilities must be examined. First, the historical algorithms for each city that were developed from
the previously  described multiple regression procedure were applied to the three future weather scenarios. The
mortality increases estimated from this procedure imply no acclimatization, as an assumption is made that people
will respond to heat in the future in much the same way that they do  today.  Second, analog cities were
established for each city evaluated to  account for full acclimatization. For example, the use of one of the GISS
scenarios to predict future weather in New York City will produce a regime which will approximate another city's
present  weather in the U.S. Thus using the GISS transient Ag scenario to predict New York City's summer
weather for the period 2024-2040 yields a weather regime approximating that of Kansas City, MO, today. Since
Kansas City residents are fully acclimatized to this regime, the weather/mortality algorithm developed for Kansas
City can be utilized for New York City to account for full acclimatization if New York's weather approximates
that predicted  by GISS transient A2.

    One potential problem  that arises from the utilization of weather analogs involves the possible difference
in racial and socioeconomic composition between the evaluated city and its analog. The utilization of standard
city death totals minimizes this problem.

Selection of analog cities

    Present-day analogs to  account for full acclimatization  were selected for  each city evaluated in this study
for the three GISS transient scenarios for summer and winter, and mortality models were created for them using
the procedure  described earlier. Each analog was selected  from a pool of almost 50 cities  around the country
(Table 4), representing virtually every weather regime found in the continental United States. This large sample
size of cities permits an inter-regional evaluation of human  weather/mortality responses on a scale larger than
ever before.

    The analog cities for summer were determined by comparing three weather variables (mean maximum
temperatures,  mean minimum temperatures,  and the mean number of days with maximum temperatures over
                                                 1-13

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Kalkstein
                       Table 4. Cities Used as Potential Analogs
         1. ALBUQUERQUE, MM
         2. AMARILLO/LUBBOCK, TX
         3. ATLANTA, GA
         4. BILLINGS/GREAT FALLS, MT
         5. BIRMINGHAM, AL
         6. BOISE, ID
         7. BOSTON, MA
         8. CASPER, WY
         9. CHARLOTTE, NC
        10. CHICAGO, IL
        11. CINCINNATI, OH
        12. CLEVELAND, OH
        13. DALLAS, TX
        14. DENVER, CO
        15. DESMOINES, IA
        16. DETROIT, MI
        17. EL PASO, TX
        18. FARGO, ND
        19. INDIANAPOLIS, IN
        20. JACKSON, MS
        21. JACKSONVILLE, FL
        22. KANSAS CITY, MO, KS
        23. LAS VEGAS, NV
        24. LITTLE ROCK, AR
25. LOS ANGELES, CA
26. LOUISVILLE, KY
27. MEMPHIS, TN
28. MIAMI, FL
29. MILWAUKEE, WI
30. MINNEAPOLIS, MN
31. NASHVILLE, TN
32. NEW ORLEANS, LA
33. NEW YORK, NY
34. NORFOLK, VA
35. OKLAHOMA CITY, OK
36. PHILADELPHIA, PA
37. PHOENIX, AZ
38. PITTSBURGH, PA
39. PORTLAND, OR
40. ROCHESTER, NY
41. ST. LOUIS, MO
42, SALT LAKE CITY, UT
43. SAN ANTONIO, TX
44. SAN DIEGO, CA
45. SAN FRANCISCO, CA
46. SEATTLE, WA
47. SPOKANE, WA
48. WICHITA, KS
                                     1-14

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                                                                                              Kalkstein


90F) for the three summer months (June, July, and August) . This process was repeated using mean maximum
temperatures, mean minimum temperatures, and the mean number of days with maximum temperatures below
32F for the three winter months (December, January, and February) to determine winter analog cities . The
statistical procedures used to determine the closest analog are described in detail within another manuscript
(Kalkstein, in press), and these techniques produced  analogs which were very close to the estimated future
climate of the target cities.

    Figure 4 illustrates the hypothetical differences expected in mortality with full, partial, and no acclimatization.
It is probable that the acclimatized models (based on warmer city analogs) will show smaller increases in
mortality than the unacclimatized models since residents have already adapted to the increased warmth. Thus,
for warming scenarios of seven or more degrees, the differences in predicted deaths  between full and no
acclimatization situations may be very large (area hatched between lines 1 and 2).  It is obviously necessary to
consider a  situation where partial  acclimatization will be a likely result.  It is possible  that people will fully
acclimatize to the increased warmth, but even if the population is capable of full behavioral acclimatization, it
will take many years for the physical structure of the city to  conform  to the hotter climate  (eg. total air
conditioning of dwellings, construction of new structures with heating/cooling systems capable of meeting the
demands of the new climate).  It is improbable that people will not acclimatize at all to the increased warmth,
as a majority of previous research rejects the notion that the population cannot acclimatize at least partially to
changing weather conditions.  For example, although it appears probable that people might adapt very well to
the predicted warming, the urban structures will not be changed within the next 70 years to reflect the  type of
architecture best suited for the warmer climate. Today most poor inner city southerners  reside in small single
family dwellings  which have adequate ventilation  and often reflective aluminum roofs.   However, their
counterparts in large northeastern and midwestern cities live in row homes constructed of brick and possessing
black roofs which readily absorb solar radiation. These structures become much hotter during extreme weather,
and it is doubtful that the architectural makeup of these northern urban areas will change quickly enough to
adapt to the predicted increasing warmth.  Thus, a third estimate reflecting partial acclimatization (reflecting
full acclimatization among the population but little change in the urban infrastructure) is included in Figure 4,
with values intermediate between the full and no acclimatization possibilities.

    In certain cases, it is possible that no extra deaths will be predicted for full acclimatization, as residents are
conditioned to hot weather. For example, in Jacksonville, Florida, heat waves appear to produce no extra deaths
(Figure 5);  the relationship is so poor that it is virtually impossible to determine a threshold temperature.
                                                 1-15

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Kalkstein
                                                                  LINE!
                                                                  LINE 3
                                                                  LINE 2
                              WARMING SCENARIO
                           (degrees above the baseline)

     LINE 1:  PREDICTED DEATHS WITH NO ACCLIMATIZATION
     LINE 2:  PREDICTED DEATHS WITH FULL ACCLIMATIZATION
     LINE 3:  PREDICTED DEATHS WITH PARTIAL ACCLIMATIZATION
          l\  :  RANGE OF PREDICTED DEATHS
      Figure 4. Expected increases in mortality in the target city for different warming scenarios.
                                    1-16

-------
                                                          Kalkstein
   >-
   h-

   I

   o
   Q
   uu
   M


   Q
   CXL
  CO
175



150


125



100



 75


 50


 25
              70        80        90        100

              MAXIMUM  TEMPERATURE (F)
Figure 5. Daily summer-season standardized mortality vs. maximum temperature: Jacksonville.
                            1-17

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Kalkstein

                                            CHAPTERS

                                    RESULTS AND DISCUSSION


HISTORICAL RELATIONSHIPS

    Threshold temperatures were established for each of the 15 cities for total deaths and deaths among the
elderly for the summer and winter seasons (Table 5). The threshold temperatures varied predictably between
cities, and in the summer the southern and southwestern cities demonstrated the highest threshold temperatures.
Similar  findings were uncovered for threshold temperatures in the winter.  Although there was considerable
variation in threshold temperatures between cities, very little variation was detected between the two death
categories within cities. For example, the summer threshold temperature in Atlanta was 94F for the total and
elderly death categories.  It does not appear that any particular age group exhibits a distinctively high or low
threshold temperature.

        Very little lag time was noted between the weather mechanism and associated mortality response for
all  cities in summer  (Table 5).  In most cases, the  mortality response occurred  on the same  day as the
responsible weather mechanism (lag time = 0 days), although one-day lag responses were detected in some of
the models. In winter, however, longer lag times were often noted, and for some cities the mortality response
occurred three days after the responsible weather mechanism.

     Once the threshold temperatures were established, the "all regression" procedure was performed for days
above the threshold to determine the weather elements having the greatest impact on present-day mortality in
each city.  A large number of statistically significant models were  uncovered for both seasons and for  both
death categories.  Many of the relationships were more impressive than expected, with R2 values frequently
exceeding 0.250, especially in summer.  During the warm season the most important weather variables proved
to be CDH and TIME, which were directly and inversely related to mortality, respectively.  The inverse TIME
relationship suggests that the timing of the weather event is often as important as the magnitude. Hot weather
occurring early in the season appears to have a more devastating impact  than similar weather occurring in
August, implying  that acclimatization to hot weather might occur rapidly within a season.  The importance of
CDH and relative insignificance of maximum temperature are also noteworthy. This suggests that the intensity
of the heat event  might be of lesser importance than the duration of the event. Winter relationships appear to
be substantially weaker than those in summer, and thermal variables (MAXT, MINT, HDH) appear to be much
less important. Refer to Kalkstein, in press, for a more complete explanation.

    Although similar numbers of statistically significant models were found for "all causes" and "weather-related"
causes of death, the level of significance varied considerably between the two in both seasons.  The proportion
of statistically significant models with R2 values exceeding 0.250 was much higher for the all causes category in
summer.  When significant all causes and weather-related models were uncovered for the same category within
a city, the all causes model usually possessed the higher R  value.  This is consistent with the findings of past
studies  on summer mortality as described previously,  and  the results of the all causes, rather than weather-
related, models will be use,d exclusively here for .the summer season.  The winter season  produced opposite
results, and the "weather-related" category normally possessed a higher R2 value than its "all causes" counterpart;
thus the former will be emphasized here for the winter season.

    The historical evaluation of mortality produced very interesting geographical distributions, indicating that
the impact of weather on mortality varies considerably on an inter-regional level. For example, people living in
the northern part  of the country appear much more susceptible to heat-related mortality than those in the South.
For a full discussion of these inter-regional variations, refer to Kalkstein (in press).

    The algorithms developed through the regression analyses were employed to estimate the number of deaths
attributed to the  weather for each of the 15 evaluated cities.  In addition, the use of future weather scenarios
assuming long-term climatic warming permitted application of the algorithms to predict future trends in mortality.
Both unacclimatized  (using the historical algorithm for a city to predict  future mortality in that city) and
acclimatized (using the algorithms for analog cities to predict future mortality) estimates will be presented,

                                                 1-18

-------
                                                                                   Kalkstein
Table 5.  Threshold Temperatures and Lag Times For the Fifteen Cities in Summer and Winter3
                       Summer
Winter
Total Deaths
City Threshold Lag
Atlanta 94F 0
Chicago 91 0
Cincinnati 92 0
Dallas 103 0
Detroit 90 0
Kansas City 99 0
Los Angeles 81 0
Memphis 99 0
Minneapolis 93 1
New Orleans
New York 92 1
Oklahoma City
Philadelphia 92 1
St. Louis 96 1
San Francisco 84 1
a If no value exists, the model was not
b Only "weather-related" models were
"all causes" counterparts.
Elderly Deaths
Threshold Lag
94F 0
91 0
93 1
103 0
90 1
99 0
82 0
99 0
93 0

93 1
104 1
92 1
98 1
81 1
statistically significant
Total Deaths0
Threshold Lag
36F 3
15 0
18 3
34 0
16 2
19 1

29 3
1 1

27 0

24 1
22 3
48 0
at the 0.05 level.
utilized for winter since these provided better


Elderly Deaths0
Threshold Lag

15 0
18 3
39 1

22 0
57 2
29 3
4 3

24 2

24 1

48 0

relationships than their

                                        1-19

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Kalkstein


using the GISS warming scenarios described earlier. A statistically significant model at the 0.05 level or better
was required if any estimate was attempted. If no statistically significant model was uncovered, it was assumed
that weather has no impact on mortality, and a value of 0 deaths was assigned.

   Analog cities were developed for summer and winter for  each city to develop acclimatized predictions
(Tables 6-7). In certain cases, the change in climate was so small (i.e., the GISS Transient A1 run) that a city
could be an analog of itself (refer to the Dallas summer analog).


SUMMER PREDICTIONS

   Initially, an estimate of present-day mortality attributed to weather was attempted by utilizing the created
regressions to develop historical algorithms for the 15 cities (Table 8).  Using the algorithms, mortality was
estimated  for every day having temperatures above the  threshold in the 11-year  sample.   These mortality
estimates were compared to the 11-year mean mortality for the month, and the difference between the estimate
derived from the algorithm and the long-term monthly mean was considered to be  the day's weather-induced
mortality.  For example, assume that June 1,1980, experienced temperatures above the threshold in Cincinnati.
The historical algorithm estimated that 130 deaths occurred in Cincinnati on that day. The 11-year June mean
mortality for Cincinnati is 115 deaths.  Thus, 15 deaths were attributed to weather in Cincinnati on June 1.

   The deaths attributed to weather were summed daily for all  days above the threshold temperature for each
month over the 11-year period. The average monthly mortality was extracted to represent the expected mortality
attributed to weather during an average month in the evaluated  city. Seasonal averages were derived from the
monthly values.

   For total deaths, it appears that New York experiences the greatest mortality totals, amounting to 320 deaths
from all causes during an average summer attributed to weather. Chicago and Philadelphia ranked second and
third, respectively, both averaging well over  100 standard city deaths during an average summer. Lowest values
were found  in New Orleans and Oklahoma City, where 0 deaths  were attributed to the weather.   During an
average summer season over 1150 standard city deaths attributed to weather are  estimated to occur in the
SMSAs of the 15 cities. Of course this figure is much higher during extremely hot summers.

    July is by far the most significant month, accounting for approximately two-thirds of all mortality in summer
attributed to weather.  Although August is generally much warmer than June in most of the cities, mortality for
both months is quite similar, and in some cases, June's predicted mortality exceeds that of August. This  reflects
the importance of within-season acclimatization (Kalkstein, in press), indicating that early-season (June) heat
waves generally exert a greater impact than late-season (August) heat waves of similar magnitude.

    The evaluation of predicted future unacclimatized,  acclimatized, and partially acclimatized mortality in
summer based on the warming scenarios yielded interesting results (Table 9). Virtually all cities exhibited an
increase  in mortality as the scenarios became  warmer for both  total and elderly deaths,  and the total
unacclimatized mortality estimate exceeded 7400 attributed to weather during an average summer under 2XCO2
conditions.  This is almost seven times higher than the number of deaths attributed to weather under average
summer conditions today.  However, the magnitude of the increase varied significantly between cities.  New York
continued to be the city with the greatest number of deaths through most of the warming scenarios, with over
1700 deaths attributed to  weather during  an average summer under 2XCO- conditions.  Other cities with
predicted rapid rises in mortality with future warming were Los Angeles, Memphis, Philadelphia, and New York.
New Orleans and Oklahoma City, with statistically non-significant mortality models, will probably not be affected
significantly by future wanning.

    Estimates of future acclimatized mortality indicate  that predicted warming might lessen  weather-induced
mortality in certain cities if acclimatization proceeds rapidly. In Atlanta, Detroit,  Los Angeles, Memphis, New
                                                1-20

-------
                                                                               Kalkstein
Table 6.  Summer Analogs for the Fifteen Cities Using the Three Warming Scenarios
Target City
1. Atlanta
2. Chicago
3. Cincinnati
4. Dallas
5. Detroit
6. Kansas City
7. Los Angeles
8. Memphis
9. Minneapolis
10. New Orleans
11. New York
12. Oklahoma City
13. Philadelphia
14. St. Louis
15. San Francisco

GISS Trans A1
Kansas City
Des Moines
Philadelphia
Dallas
Minneapolis
Omaha
San Diego
Nashville
Des Moines
New Orleans
Norfolk
Dallas
Norfolk
Wichita
Seattle
Analog Cities
GISS Trans Ag
Wichita
St. Louis
Nashville
Phoenix
Omaha
Memphis
Pittsburgh
New Orleans
Nashville
San Antonio
Kansas City
Dallas
Kansas City
Memphis
Seattle

GISS 2XCO2
New Orleans
St. Louis
Birmingham
Phoenix
Omaha
Memphis
Norfolk
San Antonio
St. Louis
San Antonio
Kansas City
Dallas
Birmingham
Jacksonville
Pittsburgh
Table 7. Winter Analogs for the Fifteen Cities Using the Three Wanning Scenarios
Target City
1. Atlanta
2. Chicago
3. Cincinnati
4. Dallas
5. Detroit
6. Kansas City
7. Los Angeles
8. Memphis
9. Minneapolis
10. New Orleans
11. New York
12. Oklahoma City
13. Philadelphia
14. St. Louis
15. San Francisco

GISS Trans A,
Atlanta
Rochester
Cincinnati
Dallas
Cleveland
Indianapolis
Los Angeles
Memphis
Minneapolis
New Orleans
New York
Little Rock
New York
Philadelphia
San Francisco
Analog: Cities
GISS Trans A%
Dallas
Indianapolis
Louisville
Houston
Pittsburgh
Louisville
Los Angeles
Dallas
Milwaukee
San Diego
Washington, DC
Birmingham
Washington, DC
Louisville
San Francisco

GISS 2XCO2
Dallas
Philadelphia
Louisville
New Orleans
New York
Oklahoma City
Miami
New Orleans
Chicago
Los Angeles
Norfolk
Jackson
Norfolk
Memphis
San Diego
                                    1-21

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Kalkstein
Table 8. Estimates of Total Present-Day Mortality Attributed to Weather During an Average Summer Season
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
City
New York
Chicago
Philadelphia
Detroit
St. Louis
Los Angeles
Minneapolis
Cincinnati
Kansas City
San Francisco
Memphis
Dallas
Atlanta
New Orleans
Oklahoma City

June
45
44
35
21
1
19
9
9
0
12
0
6
8
0
0

July
217
98
59
67
80
30
27
21
28
10
18
8
10
0
0
Mortality
August
58
31
51
30
32
35
10
12
3
5
2
5
0
0
0

Total
320
173
145
118
113
84
46
42
31
27
20
19
18
0
0
                                               1-22

-------
TABLE 9.       ESTIMATES OF FUTURE MORTALITY IN SUMMER ATTRIBUTED
                                   TO WEATHER
Present GISS
Non-
City Total Aoclim
Atlanta
Elderly 9 < 25
Total 18 45
Chicago
Elderly 104 173
Total 173 2^95
Cincinnati
Elderly 28 62
Total 42 93
Dallas
Elderly 9 33
Total 19 61
Detroit
Elderly 70 120
Total 116 201
Kansas City
Elderly 20 20
Total 31 33
Los Angeles
Elderly 53 94
Total 84 153
TRANS
Partial
Aoclim

13
23

86
145

52
83

33
61

91
152

24 -
40

50
81
A1
Full
Acclira

0
0

0
0

45
72

33
61

0
104

27
48

7
11
GISS
Non-
Aoolim

63
118

300
511

127
195

109
197

301
512

41
66

194
313
TRANS
Partial
Acclim

32
59

408
725

63
97

68
213

151
254

16
68

132
205
A* 1 GISS
Full
Accllm

0
0

520
940

0
0

28
67

0
0

49
71

71
116
Non-
Accllm

85
159

240
412

150
226

172
309

349
592

38
60

1026
1654
2x
Partial
Accllm

43
79

347
622

123
195

153
244

174
295

66
100

513
824
CO?
Full
Acclim

0
0

458
835

69
116

74
179

0
0

18
138

0
0
Change:
Non-
Accllm

76
141

136
239

122
184

163
290

279
471

93
29

973
1570
Present
Partial
Accllm

31
61

243
449

95
153

144
225

104
177

46
69

160
710
to 2 x C02
Full
Acclim

-9
-18

351
662

11
71

65
160

-70
-118

73
107

-53
-81
F

-------
Table 9. (page 2)
Present

City
Memphis
Elderly
Total
Minneapolis
Elderly
Total
New Orleans
Elderly
Total
New York
Elderly
Total
Oklahoma City
Elderly
Total
Philadelphia
Elderly
Total

St. Louis
Elderly
Total

Total

13
20

30
16

0
0

212
320

0
0

91
115


71
113
GISS
Non-
Acclim

18
28

65
96

0
0

511
777

0
0

182
288


203
325
TRANS
Partial
Acclim

9
11

32
17

0
0

257
386

1
6

89
112


102
162
A1
Full
Acclim

0
0

0
0

0
0

0
0

8
12

0
0


0
0
GISS
Non-
Accllm

17
78

118
175

0
0

897
1375

0
0

189
778


171
751
TRANS
Partial
Acclim

21
39

59
87

0
0

118
689

9
19

211
388


373
561 '
A*
Full
Acclim

0
0

0
0

0
0

6
8

19
29

0
0


278
375
GISS
Non-
Accllm

106
177

95
112

0
0

1139
1713

0
0

590
938


159
' 711
-2x
Partial
Acclim

52
88

110
186

0
0

580
080

16
23

590
TOO
I

226
372
.CO?
Full
Acclim

0
0

126
235

0
0

17
23

31
17

285
166


0
0
Change: Present to 2. x CC-2
Son-4 Partial Full
Acclim Acclim Acclim

93 39 -13
157 68  -20

65 80 96
96 110 189

000
000'

927 368 -195
1123 560 -297 
,
0 16 31
,0 23 '17
1
199 199 191
793 555 321


388 155 -71 '"
631 259 -113 '
' 1

-------
Table 9. (page 3)
Present

City,
San Francisco
Elderly
Total
Total
Elderly
Total

Total

17
27

727
1156
OISS
Non-
Accllm

28
11-

1537
2139
*
TRANS.
Partial
Aoclim

11
23

856
1365
A'
Full
Acclim

2
3

122
311
GISS
Non-
Accllm

15
71

3202
5113
TRANS
Partial
Acclim

23
38

2050
3115
A*
Full
Acclim

1
7

975
1613
GISS
Non-
Acclim

156
216

1605
7102
2x
Partial
Acclim

129
202

3122
1810
C02
Full
Acclim

103
159

1256
2198
Change: Present to 2 x CO 2
Won- Partial Full
Acclim Acclim Acclim

139 112 86
219 175 132

3878 2395 529
6216 3651 1012

-------
Kalkstein


Orleans, and St. Louis virtually no weather-induced deaths were predicted if the residents of these cities
acclimatize. This is particularly surprising for St. Louis, where unacclimatized future mortality estimates and
historical estimates were very high. In approximately half of the cities mortality totals declined as the scenarios
became warmer, and in cities where increases did occur, they were much smaller than those uncovered under
no acclimatization. The 15-city acclimatized totals showed a significant drop in mortality under conditions
predicted in the early 21st century (GISS Transient AA followed by a relatively modest rise (when compared
to unacclimatized results) for the mid 21st century (GISS Transient Ag). A more significant rise in acclimatized
mortality is noted under 2XCO2 conditions, with values approximately double today's weather-induced mortality.

    Estimates  of future total  mortality assuming partial acclimatization were  calculated  by computing the
mortality totals exactly halfway between full and no acclimatization values.  With partial acclimatization about
3800 standard city deaths are predicted for  the  15-city sample under 2XCO2 conditions.  This represents a
substantial increase over present-day mortality estimates attributed to weather, and although these values should
be viewed cautiously, indications are that mortality will increase substantially if partial acclimatization takes place.

    Mortality estimates for the 65 and  older category were very similar to  the total mortality estimates.
Substantial increases in unacclimatized mortality were noted in virtually  all cities.  Partial acclimatized values
were less than unacclimatized, but a substantial increase of almost 2400 deaths  above present conditions was
noted for the 15-city sample under 2XCO2 conditions.  Much like the results from the total death category,
acclimatized mortality predictions for the 65 and older group were much smaller than the unacclimatized values.

    The great disparity between acclimatized and unacclimatized predictions is troubling but not surprising.  If
people do not acclimatize to predicted warming, weather-induced mortality will rise at a very rapid rate because
(1) the number of days exceeding the threshold temperature will increase, providing a larger group of total days
when weather-induced mortality will be a factor; and (2) since CDH and maximum temperature are  directly
related to mortality in almost all the summer models, mortality will necessarily increase as the magnitudes of
these weather variables increase. If acclimatization is complete, increasing warmth will produce a much smaller
rise in mortality, which parallels the response of people today who reside in hot  climates. In almost all of the
southern cities in our 15-city sample, present-day weather-induced mortality was estimated to be lower than in
the northern cities. These southern cities represent analogs of expected climate in the northern cities,  and the
lower present-day mortality rates indicate that southerners have indeed acclimatized to the frequent hot weather
episodes that occur.


WINTER PREDICTIONS

    The following winter mortality predictions are for weather-related causes of death only. Mortality predictions
were also constructed for all causes of death, but these models generally possessed lower R2 values than their
weather-related counterparts. Thus a decision was made to use the weather-related predictions to ensure a more
accurate result.

    Present-day estimates of winter mortality indicate that weather-induced deaths are much less important in
winter than in summer (Table 10).  The city with the greatest predicted  number of winter deaths, New York,
averages only 56 standard city deaths per season. About half of the cities in the 15-city  sample produce 10 or
less weather-induced winter deaths during an average season. In some cases, statistically significant models were
developed for winter for these cities, but the relationships were relatively weak, yielding mortality predictions that
approached 0.

    For total deaths, the four top ranking cities are all northern or midwestern locations. New York, St. Louis,
Chicago, and Kansas City account for 170 of the 296 total weather-induced deaths which occur in the 15-city
sample during a typical winter.  The occasional severe cold waves encountered here obviously have a significant
impact  Surprisingly, Minneapolis mortality totals are quite low compared to Midwestern cities located farther
south. It is possible that residents of Minneapolis are so conditioned to winter cold that they are


                                                 1-26

-------
                                                                                          Kalkstein
Table 10.  Estimates of Total Present-Day Mortality Attributed to Weather During an Average Winter Season
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
City
New York
St. Louis
Chicago
Kansas City
Dallas
Detroit
Cincinnati
San Francisco
Philadephia
Minneapolis
Atlanta
Los Angeles
Memphis
New Orleans
Oklahoma City

January
38
15
16
5
3
2
3
8
10
2
0
0
0
0-
0

February
10
20
25
12
10
8
8
1
0
2
0
0
0
0
0
Mortality
December
8
12
5
4
3
16
3
1
0
1
2
0
0
0
0

Total
56
47
46
21
16
16
14
10
10
5
2
0
0
0
0
                                               1-27

-------
Kalkstein


behaviorally adapted and take the proper precautionary steps to avoid cold weather impacts.  The five cities
which record the lowest number of weather-induced winter deaths are located in milder climates. In a previous
study Los Angeles and San Francisco never exhibited winter conditions severe enough to produce weather-
induced deaths (Kalkstein  and Davis, 1985).  However, the  other southern cities recording  few deaths do
experience occasional cold waves, especially Atlanta, Memphis, and Oklahoma City. Perhaps the cold episodes
are of too short a duration  or are not extreme enough to create problems.

    The sensitivity of the elderly to whiter-induced mortality is surprisingly low, and only 157 elderly deaths
attributed to weather are predicted during an average winter.  Once again, the cities with the greatest predicted
elderly mortality are located in northern or midwestern locations, while a majority of the low ranking cities are
found in milder climates.

    These results seem to counter some of the findings hi the summer models regarding the relative impact of
weather. During summer, many of the cities exhibiting the highest weather-induced mortality totals were located
in the northern United States, where extreme heat occurs less often.  There was a clear suggestion that people
react to weather in a relative, rather than absolute, fashion in summer, as cities with low mortality estimates were
found in some of the  hottest  regions in the country.  During winter, the findings suggest that this relative
response is less pronounced, as many of the cities with the highest winter mortality totals are located hi regions
with relatively severe whiter climates, such as Chicago, Kansas City, New York, and St. Louis. Thus, the impact
of weather on mortality hi whiter appears to be more absolute.

    In both the total and elderly predictions for whiter, February exhibits a surprisingly low number of whiter
weather-induced deaths.  This occurs although February is normally colder than December; once again, an
element of within-season acclimatization appears to be present and people are more sensitive to early cold waves
than to later cold waves of similar (or greater) magnitude.  Nevertheless, the TIME variable is less important
in whiter than hi summer, and within-season acclimatization is less pronounced hi winter.

    Estimates of  future whiter mortality based  on  the wanning scenarios  were developed,  producing
unacclimatized, partially acclimatized, and acclimatized values for total deaths and elderly deaths.  The results
were very different than those uncovered hi summer (Table 11). For total deaths assuming no acclimatization,
a decline in weather-induced mortality was noted for most of the cities hi the 15-city sample as the scenarios
became wanner. Of the 15 cities, 10 registered five deaths or less under 2XCO2 conditions.  These results differ
markedly from summer, where unacclimatized total mortality showed a dramatic rise as the scenarios became
warmer. The whiter results suggest that a warmer climate will correspond with a lesser number of days below
the threshold temperature,  and the potential for weather-induced mortality will decrease correspondingly.

    If full acclimatization is assumed, the impact of future warming on mortality  also creates a pronounced
drop. The lack of acclimatized mortality with increased warmth is consistent with previous whiter findings, and
mortality hi many of the southern cities (which constitute the analogs for the warmer weather scenarios) is not
significantly affected by whiter weather.   Values for partial acclimatization are similar to those  for  full
acclimatization, and very few deaths are  predicted under 2XCO2 conditions.  Elderly response with climatic
warming is very similar to the  total population response.
                                                 1-28

-------
TABLE 11      ESTIMATES  OF  FUTURE MORTALITY  IN WINTER ATTRIBUTED
                                 TO WEATHER
Present GISS
Non-
City Total Accllm
Atlanta
Elderly 1 2
Total 2 3

Chicago
Elderly 30 15
Total 16 20
Cincinnati
Elderly 9 5
Total 1 1 7
Dallas
Elderly 10 8
Total 16 11
Detroit
Elderly 10 3
Total 1 6 5
Kansas City
Elderly It 15
Total 21 20
Los Angeles
Elderly 0 0
Total 0 0
TRANS
Partial
Acclim

1
2


5
9

5
7

8
11

1
2

7
10

0
0
A1
Full
Accllm

2
2


0
0

5
7

8
1

0
0

0
0

0
0
GISS
Non-
Acclim

1
2


5
7

3
ij

1
H

1
2

9
13

0
0
TRANS
Partial
Acclim

0
1


2
2

2
2

0
1

0
0

H
6

0
0
A2
Full
Accllm

0
0


0
0

0
0

0
0

0
0

0
0

0
0
GISS
Non-
Acclim

2
2


0
2

1
6

0
1

2
2

4
5

0
0
2x
Partial
Acclim

0
0


27
48

2
3

0
0

8
18

1
2

0
0
C02
Full 1
Acclim'

0 i
0
i

56
96

0
0

0
0

18
37

0
0

0
0
Change:
Non-
Accllm

1
0


-30
-HI

-5
-8

-10
-15

-8
-1H

-10
-16

0
0
Present
Partial
Acclim

-1
-2


-3
2

-7
-11

-10
-16

-2
2

-13
-19

0
0
to 2 x CO?
Full
Accllm

-1
-2


26
50

-9
-in

-10
-16

8
21

-11
-21

0
0

-------
Table 11. (page 2)
Preaen

City
Memphis
Elderly
Total
Minneapolis
Elderly
Total
New Orleans
Elderly
Total
New York
Elderly
Total
Oklahoma City
Elderly
Total
Philadelphia
Elderly
Total
St. Louis
Elderly
Total

Total

0
0

2
5

0
0

37
56

0
0

6
10

31
17
GISS
Non-
Accllm

0
0

0
2

0
0

28
16

0
0

8
12

21
30
TRANS
Partial
Acclim

0
0

0
2

0
0

28
16

0
0

11
25

12
18
A1
Full
Acclim

0
0

0
2

0
0

28
46

0
0

21
36

3
5
GISS
Non-
Aocllm

0
1

0
1

0
0

34
46

0
0

1
1

9
13
TRANS
Partial
Acclim

1
1

1
3

0
0

14
21

1
1

0
0

4
6
A2 GISS
Full Non-
Accllm Acclim

1 0
2 0

3 0
6 1

0 0
0 0

0 11
0 18

1 0
3 0

0 1
0 1

0 5
0 7
2x
Partial
Acclim

0
0

0
0

0
0

14
21

0
0

0
0

2
3
CO? Change:
Full Noh-
Accllto Acclim

0 0
0 0
I
0 -2
0 -4

0 0
0 0
1
23 -26
25 -38

0 II 
 II 

1 -5
1 -9
i ?
0 J -26
0 1 -40
Present
Partial
Acclim

0
0

-2
-5

0
0

-23
-35

0
0

-6
-10

-29
-44
to 2 X- COp
Full
Acclim

0
0

-2
-5

0
0
<
-14
-31

0
0

-5
-9
-
-31
-47

-------
Table 11. (page 3)
Pr*e^ent

City^
San Francisco
Elderly
Total
Total 
Elderly
Total

Total

7
10

157
213
GISS
Non-
Acclim

6
8

111
167
TRANS
Partial
Acclim
. i
6
8

87
113
A1
Full
Acclim

6
10

73
122
GJSS
Non-
Acollm

7
9

71
103
TRANS
Partial
Acclim

7
9

36
53
A2
Full
Acclim

7
10

12
21
GISS
Non-
Accllm

5
7

31
52
2x
Partial
Acclim

2
2

56
97
COp
Full
Acclim

0
0

98
159
Change: Present to 2 x CC>2
Non- Partial Full
Acclim Acclim Acclim

-2 -5 -7
-3 -8 -10

-123 -101 -59
-191 -116 -81

-------
Kalkstein
                                            CHAPTER 4

                                          CONCLUSIONS


    The objective of this study was to estimate changes in human mortality attributed to predicted changes in
climate due to increased concentrations of COL and other trace gases in the atmosphere. The major result was
an estimation of the number of deaths attributed to the increased  incidence of extreme weather episodes
predicted by numerous climate change models.    ,    -

    The evaluation covered 15 cities around the country, and daily mortality data for 11 summer  and winter
seasons were extracted. The mortality totals were divided into total and elderly mortality categories, and separate
evaluations were developed for all causes of death and those causes considered to be "weather-related."

    A summary of the results follows.              .

    1.   Predictions of weather-induced mortality occurring during summer were attempted for the 15  cities
        exhibiting significant weather/mortality relationships.  It is estimated that approximately 1150 deaths
        occur during an average summer season in the SMSAs of the 15 cities. New York City, Chicago, and
        Philadelphia ranked first, second, and third, respectively, and each city averaged well over 100 standard
        city deaths per summer. The five highest ranking cities were all found in the Midwest or Northeast.
        The  five lowest  ranking  cities  were  found in the South,  with New Orleans and Oklahoma City
        experiencing virtually no deaths attributed to weather in summer.

        2.   Predicted future unacclimatized mortality in summer rose rapidly as the scenarios become warmer.
            The total mortality estimate exceeded 7400 deaths attributed to weather during an average summer
            under 2XCO2 conditions. The magnitude of the increase varied significantly between cities.  New
            York exhibited the greatest number of deaths throughout all the warming scenarios. Other cities
            with predicted rapid rises in mortality with future warming were Los Angeles, Philadelphia, and St.
            Louis. New Orleans and Oklahoma City were cities least affected by predicted warming.

        3.   Predicted future acclimatized mortality in summer indicated that warming might lessen weather-
            induced mortality in about half of the 15-city sample if acclimatization is complete. A more modest
            rise in mortality is predicted for the 15-city sample if full acclimatization occurs; however, weather-
            induced  mortality is  predicted to double  over  present levels  if acclimatization is complete.
            Acclimatized mortality estimates for the 65+ age category were very similar to the total mortality
            estimates. By the design of the model, the relatively small rise in acclimatized mortality paralleled
            the response of people today who reside in hot climates. Southern cities represented analogs of
            expected climate in northern cities, and these cities exhibited fewer numbers of weather-induced
            deaths in summer. Estimates of future mortality assuming partial acclimatization (values  midway
            between full and no acclimatization) were also developed, and these indicated sizable increases in
            mortality as the weather became warmer.

        4.   Present-day estimates of winter mortality indicated that weather-induced deaths were much less
            important in winter  than in summer.  The results differed from those uncovered in summer
            regarding the relative impact of weather.  Most of the estimated winter deaths occurred in regions
            with relatively severe winter climates, while the smallest numbers of deaths  were found  in mild
            weather cities.  It appeared that the impact of weather in winter is more absolute, while the impact
            of weather in summer tends to be relative.

        5.   Winter unacclimatized, partially acclimatized, and acclimatized predictions indicated that sharp
             drops in mortality are expected if the weather becomes warmer. The unacclimatized results differed
                                                1-32

-------
                                                                                            Kalkstein


            from those uncovered in summer, when dramatic rises in mortality were predicted.  The
            unacclimatized drop in winter may be related to fewer numbers of days below the threshold.


        It is quite obvious that predicted warming could have an enormous impact upon human health through
the 21st century. If the population does not acclimatize, over 7000 deaths attributable to the increasingly harsh
weather can be expected in the metropolitan areas of our 15-tity sample. This figure is more startling when it
is considered that these numbers correspond to average summer conditions. An analog of the very hot summer
of 1980 occurring in the 21st century will no doubt increase weather-induced mortality to a much higher number
than 7000.

        Although fully acclimatized predictions are more modest, some general increases are still expected even
under these conditions.  If it is assumed that people will partially  acclimatize  (possibly  the most realistic
scenario), the increases in mortality are more impressive, and weather-related deaths will increase by four to
five times over present levels. Thus it appears that specific policy decisions are necessary to prepare for a
significant rise hi human mortality if the warming scenarios come to pass.
                                               1-33

-------
Kalkstein
                                          REFERENCES

Applegate, W.B., Runyan, J.W., Jr., Brasfield, L., Williams, M.L., Konigsberg, C., and Fouche, C. Analysis of
the 1980 heat wave in Memphis. Journal of the American Geriatrics Society. 29:337-342,1981.

Bridget, CA., Ellis, F.P., and Taylor, H.L.  Mortality in St. Louis, Missouri, during heat waves in 1936, 1953,
1954,1955, and 1966. Environmental Research. 12:38-48,1976.

Centers for  Disease Control.  Exposure related hypothermia deaths-District of Columbia 1972-1982.  In:
Morbidity and Mortality Weekly Report.  December, 1982. pp. 31-50.

Department of Health and Human Services. The International Classification of Diseases. 9th Revision. Clinical
Modification. Volume 3: Procedures.  Second edition, US. Dept. of Health and Human Services, September,
1980.

Draper, N., and Smith, H.  Applied Regression Analysis. Second Edition.  John Wiley and Sons, 1981. 673 pp.

Ellis, F.P.  Mortality from heat illness and heat-aggravated illness in the United States. Environmental Research.
5:1-58,1972.

Ellis, F.P., and  Nelson, F.  Mortality in the elderly in a heat wave  in New  York City,  August,  1975.
Environmental Research. 15:504-512,1978.

Fitzgerald, F.T., and Jessop, C.  Accidental hypothermia: A report of 22 cases and review of the literature.
Advanced Internal Medicine. 27:127-150,1982.

Gallow, D., Graham, T.E., and Pfeiffer, S.  Comparative thermo-regulatory responses to acute cold in women
of Asian or European descent.  Human Biology. 56:19-34, 1984.

Cover, M. Mortality during periods of excessive temperatures.  Public Health Reports. 53:112-1143,1938.

Jenne, R.  "GISS Transient Runs."  NCAR/EPA Doc. 4, U.S. Environmental Protection Agency, Washington,
DC, 1987, 3 pp.

Jones, TJS., Liang, Kilbourne, E.M., Griffin, M.R., Patriarca, PA., Wassilak, G.G., Mullan,R.F., Herricck, R.F.,
Donnel, H.D., Jr., Choi,  K., and Thacker, S.B. Morbidity and mortality associated with the July 1980 heat wave
in St. Louis  and Kansas  City. Journal of the American Medical Associations. 247:3327-3330,1982.

Kalkstein, LJS.  The impact of winter weather on human mortality.  In:  Climate Impact Assessment: United
States.  VS. Department of Commerce.  December, 1984. pp. 21-23.

Kalkstein, L.S.  The impact of CO2 and trace gas-induced climate changes upon human mortality. UJS. EPA
Office of Research and Development Report, in press.

Kalkstein, LJS., and Davis, R.E.   The development of a weather/mortality model for environmental impact
assessment.  In: Proceedings of the 7th Conference of Biometeorology and Aerobiology. 1985. pp. 334-336.

Kalkstein, LJS., Davis, R.E., Skindlov, J A., and K.M. Valimont. The impact of human-induced climatic warming
upon human mortality:  A New York City case  study.  Effects of Changes in Stratospheric Ozone and Global
Climate. Volume 3: Climate Change.  UJS. Environmental Protection Agency, October, 1986.

Kilbourne, E.M., Choi,  K., Jones, TJS., Thacker, S.B., and the Field Investigation Team.  Risk factors for
heatstroke: A case-control study. Journal of the American Medical  Association. 247:3332-3336,1982.


                                               1-34

-------
                                                                                           Kalkstein

Lilienfeld, A.M., and Lilienfeld, D.E. Chapter 4: Mortality statistics.  Foundations of Epidemiology.  Oxford
University Press, 1980. pp. 51-65.

Lye, M., and Kamal, A. The effects of heat wave on mortality rates in elderly patients. The Lancet. 1:529-531,
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Manner, M. Heat wave mortality in New York City, 1949 to 1970. Archives of Environmental Health. 30:131-
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Mausner, J.S., and Bahn, A.K. Chapter 7: Measures of morbidity and mortality. Epidemiology: An Introductory
Text. W.B. Sanders Co., 1974.

Munn, R.E.  The value of climatological information in assessments of the state of human health. Leningrad,
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National Center for Health Statistics.  Standardized Micro-Data Tape Transcripts. U.S. Department of Health,
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Oechsli, F.W.,  and Buechley, R.W.  Excess mortality associated with three Los Angeles September hot spells.
Environmental Research. 3:277-284,1970.

Rotton, J. Angry, sad, happy? Blame the weather. U.S. News and World Report. 95:52-53, 1983.

SAS Institute Inc.  SAS User's Guide: Statistics: Version 5 Edition. SAS Institute Inc., 1985. 956 pp.

Steadham, R.G. The assessment of sultriness: Part I: A temperature-humidity index based on human physiology
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Ulrich, R.S.  View through a window may  influence recovery from surgery.  Science. 224:420-421,1984.

Warren, H.E.,  and LeDuc, S.K.  Impact of climate on energy sector in economic analysis.  NOAA/Center for
Environmental Assessment Services. Environmental Data and Information Service: United States. 1981. pp. 1431-
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White, M.R., and Hertz-Picciotto, I. Human health: Analysis of climate related to health. In:  Characterization
of Information Requirements for Studies of COu Effects: Water Resources. Agriculture. Fisheries. Forests, and
Human Health. M.R. White, ed., DOE/ER-02&, CO2 Res. Div., U.S. Dept. of Energy, Washington, DC, 1985,
pp.  172-205.

Willmot, C.F., Ackleson, S.G., Davis, R.E.,  Feddema, J J., Klink, K.M., Legates, D.R., O'Donnell, J., and Rowe,
C.M. Statistics for the evaluation and comparison of models. Journal of Geophysical Research. 90:8995-9005,
1985.
                                               1-35

-------
    COMPUTER SIMULATION OF THE EFFECTS OF CHANGES IN
WEATHER PATTERNS ON VECTOR-BORNE DISEASE TRANSMISSION
                              by
                          D. G. Halle
         Insects Affecting Man and Animals Research Laboratory
                   Agricultural Research Service
                  U. S. Department of Agriculture
                       Gainesville, FL 32604
                   Project No. DW12932662-OM

-------
                                  CONTENTS
FINDINGS 	  2-1

CHAPTER 1: INTRODUCTION	  2-2

CHAPTER 2: METHODOLOGY	  2-3
      THE AMERICAN DOG TICK MODEL	  2-3
      THE MALARIA MODEL	  2-3

CHAPTER 3: RESULTS 	  2-5
      ADTSIM RESULTS 	  2-5
            ADTSIM - Richmond, Virginia 1950-80	  2-5
            ADTSIM Results at Various Locations	  2-5
      RESULTS WITH MALSIM	  2-5
      INTERPRETATION AND IMPLICATIONS OF RESULTS

REFERENCES	  2=12  3-- V\
                                      11

-------
                                                                                               Haile


                                            FINDINGS1


        Two weather-based models for simulation of the population dynamics of disease vectors were used to
assess the possible effects of climate change due to increased levels of CO, m tne atmosphere on vector-borne
disease transmission in the United States.  The first model (ADTSIM) simulates population dynamics of the
American dog tick (ADT), Dermacentor variabilis. which is the primary vector of Rocky Mountain Spotted Fever
(RMSF) in the eastern U. S. This model included the effects of temperature and atmospheric moisture on the
life processes of the tick. The density of adult ticks was used as an indicator of RMSF transmission potential
because this is the stage normally involved in transmission of human cases.  The second model (MALSIM)
simulates the population  dynamics of Anopheline mosquitoes and the transmission of  malaria between
mosquitoes and  humans.  This model simulates direct incidence  of malaria,  assuming that the  disease is
reintroduced  into a human population that  is continuously  exposed to  mosquito bites.  The  effects  of
temperature,  atmospheric moisture, and rainfall are included in MALSIM.  The malaria vector considered in
these simulations is Anopheles quadrimaculatus. which presently exists in many areas of the eastern half of the
U. S. and was the primary vector of malaria in the south and east when the disease was endemic.

        The ADTSIM results indicate that with the proposed climatic change  scenarios at certain southern
locations (Jacksonville, FL, and San Antonio, TX) ADT populations will disappear owing to adverse effects of
high temperatures and low humidity, while  at certain northern locations (Missoula, MT, North Bay, Ont., and
Halifax, N.S.) populations  will increase because  of wanning with adequate moisture.  For most other U. S.
locations, tick densities either declined moderately or remained the same with various weather scenarios.  These
results suggest that overall in the U. S. the  problem of RMSF will decrease in certain areas, while others will
remain  unchanged.

        The  results of simulations of malaria transmission (assuming the disease is reintroduced into an
unprotected population) show that  there is little change in the transmission potential with modified weather
scenarios. Areas in Florida with high transmission potential normally will remain high; very little increase was
predicted for  other areas.

        Only the direct  effects of weather  on the disease vector were considered in these  simulations.  No
consideration of the effects of weather on host densities or habitat were included. Consideration of these effects,
along with other model refinements, would be necessary to improve confidence in the overall results. Also, much
additional research on the biology, ecology,  and modeling of these and other vector/disease complexes will be
required for a more complete analysis of the impact of weather change on vector-borne diseases.
        'Although the information in this report has been funded wholly or partly by the ILS. Environmental
Protection Agency under Project Number DW12932662-01-1, it does not necessarily reflect the Agency's views,
and no official endorsement should be inferred from it.

                                                2-1

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Haile

                                           CHAPTER 1

                                         INTRODUCTION


        This study addresses the impact of climate change on vector-borne disease transmission in the United
States as part of an overall study by the U. S. Environmental Protection Agency (EPA) the effects of climatic
change resulting from the "greenhouse effect". Although at present there are no vector-borne diseases that are
continuously transmitted to the human population in the United States, numerous arthropod vectors are present
in the environment and the potential for major outbreaks exists in various regions as a result of increases in
vector populations or prevalence of a disease.

        Certain diseases are present in animal hosts,  and others may be introduced from endemic areas by
human immigrants or travelers. The arthropods most commonly involved in disease transmission in the United
States involve various tick and mosquito species. The importance of weather variables on vector population
dynamics and disease transmission has long been recognized (Harwood and James,  1979; Warren and Mahoud,
1984; Russell  et  aL, 1963).  Increases in temperature, up to an optimum  level,  normally increases the
development and survival rate of vector and parasite life stages. Adequate atmospheric or soil moisture levels
are important  for survival of various vector stages and, in the case of mosquitoes, adequate levels  of aquatic
habitat are necessary for immature development.

        Models have been used as a tool for understanding various aspects of vector population dynamics and
disease transmission. In particular, the transmission of malaria has been studied extensively with mathematical
models (Ross, 1911; MacDonald, 1957; Deitz et al., 1984; Moiineaux and Grammiccia, 1980).  Some efforts have
been made to study mosquito and tick population dynamics using a computerized life history approach (Haile
and Weidhaas, 1977; Fine  et al., 1979; Sutherst et al.,  1978; Sonenshine, 1975), but none  of these efforts
attempted to comprehensively model the effects of weather variables required for a quantitative assessment of
climatic change. More recently, however, a comprehensive computer simulation model for population dynamics
of the lone star tick, Amblvomma americanum.  was developed, which included the  direct effects of weather
variables (Haile and Mount, 1987). This study was extended to develop a similar model for population dynamics
of the American dog tick, Dermacentor variabilis. which is the principal vector of Rocky Mountain Spotted Fever
(RMSF) in the U. S. (Mount and Haile,-in press).  In addition, the model for Anopheles albimanus by Haile
and Weidhaas (1977) has been expanded to include the direct effects of weather variables and to allow simulation
of malaria transmission to and from a human population  with a variety of vector species (unpublished). These
weather-sensitive models were used as the basis for the study on the impact of climatic change reported here.
This report will describe the methodology used to simulate the effects of climatic change and an analysis of the
implications of the results.
                                                2-2

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                                                                                              Haile

                                           CHAPTER 2

                                        METHODOLOGY


THE AMERICAN DOG TICK MODEL

        The development and validation of the American dog tick model (ADTSIM) is reported in Mount and
Haile (in press).  Briefly, this model uses a dynamic life history approach with weekly age classes and time steps.
Environmental variables used in the model include temperature, saturation deficit, daylength, host density, and
habitat  type.  Relationships between environmental and  biological  variables  include the  following:  (1)
temperature-dependent development rates for eggs and engorged larvae, nymphs, and females; (2) the influence
of temperature on fecundity; (3) the influence of habitat type,  temperature, and saturation deficit on survival
rates of free-living ticks; (4) the  effect of host density, temperature, and daylength on host-finding rates; and (5)
density-dependent survival of parasitic ticks during engorgement.

        ADTSIM was developed to reflect the effects of average weekly weather data. These data may be actual
values for a particular year or historical average data (values averaged over a period of years). As such the
model was not designed to reflect the influence of extreme conditions on a diurnal or daily basis.

        The effect of climate  change in  ADTSIM will indicate the direct effects of changes in ambient
temperature and moisture on the tick life cycle with all other variables remaining constant. Any effect of climate
change on habitat type and host densities are not simulated.  An average of the number of adult  ADT on hosts
each week was used as an index to summarize each year of simulation.  This index can also  be used as an
indicator of the transmission potential of RMSF because the adult tick is most often involved in transmission of
the disease to humans.

        Weather scenarios based on the results  of three climate change models  (GISS, GFDL, and  OSU)
that simulated the effects of doubling the level of CO, in the atmosphere, were used in the vector population
models.  Only simulations representing a step change in weather were used in this study.  Actual data for the
base period  1951-1980 were used for only one location (Richmond, VA) with ADTSIM. Historical average
weather data for Richmond and other locations were used as the basis for evaluating the effect of the weather
change models at each location. In this case the weekly weather data (normal or modified) were used  in the
population model each year until equilibrium was  reached (usually ca. 15 years).  A comparison of the
equilibrium population with the  population resulting from use of modified weather gave a direct measure of the
impact of climate change.


THE MALARIA MODEL

        A comprehensive model (MALSIM) to simulate the effects of environmental variables  on population
dynamics of Anopheline mosquitoes and on transmission of Falciparum malaria  to a human population is
currently being developed.  Although this model is not fully validated, it contains the necessary relationships to
provide a preliminary evaluation of the impact of climate change scenarios on this important disease.

        Anopheles quadrimaculatus is the only malaria vector simulated in these studies.  This  species  is still
present  in many areas of the eastern half of the United States and was the primary vector of malaria  in the
Southeast when the disease was endemic.

        The following environmental  relationships are  included in MALSIM  at  present: (1) the effect of
temperature on developmental rates of each vector stage and the parasite  in the mosquito; (2) the effect of
temperature on survival of immature stages; (3) the effect of temperature and saturation deficit on adult survival;
(4) the relationship between rainfall, available area of aquatic habitat, immature density, and immature survival;
and (5)  temperature-induced hibernation of mated, nonblooded females.


                                               2-3

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Haile
        Historical average weather data for a number of locations were used as the basis for simulations to
compare the malaria transmission potential for normal vs. modified weather resulting from three climate change
models (GISS, GFDL, and OSU). Although malaria is unlikely to become endemic in the United States, these
simulations assume an introduction of 100 cases in an unprotected population of 10,000 along with initiation of
mosquito population with 100,000 female adults. The level of transmission (incidence) in the 10,000 unprotected
population after 3 years of simulation is used as an indication of transmission potential for comparative purposes.
                                                2-4

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                                                                                              Haile

                                           CHAPTERS

                                             RESULTS


ADTSIM RESULTS

ADTSIM - Richmond Virginia 1950-80

        The simulated adult tick densities for the period 1950-1980 at Richmond with normal yearly weather
data shows considerable variation between years  as a result of weather alone (Figure 1).  Cases of RMSF in
Virginia and the United States (CDC data) are plotted in Figure 1 to show the  correlation between simulated
tick density and actual disease incidence. Figure 2 shows the comparison between the simulations with normal
weather and the three models with modified weather. All modified weather scenarios produce a decrease in tick
density for all years in the 30-year period. The OSU and GISS models show very similar results while the GFDL
model produced a greater reduction. Comparisons of the average  density with yearly data to the equilibrium
density with historical average weather data showed that the results are very similar. Therefore, the equilibrium
density method was used for evaluation of the impact of the modified weather scenarios at other locations.

ADTSIM Results at Various Locations

        The equilibrium density of ADT adults on hosts at various U.S. locations and two Canadian locations
with normal weather compared to the modified weather scenarios is shown in Figure 3. The results indicate a
very clear shift in tick densities from south to north.  The tick population was eliminated at the most southerly
locations (Jacksonville and San Antonio) for all three modified weather scenarios.  Simulations at Albuquerque
showed no population with the normal dry weather and no change with any of the scenarios. Robust increases
in tick density were indicated at the most northerly locations (Missoula, North Bay, and Halifax) for all scenarios.
Missoula and  North Bay had no tick population with normal weather and  Halifax had only a low-level
population. Simulations at U.S. locations where the normal tick density is relatively high produced a variety of
results for the different scenario models. At some locations the three models produced similar results showing
essentially no change in density at Los Angeles, Boston, and Medford or a moderate decrease at Richmond, New
York, and Columbus. The results at Tulsa and Nashville indicated a decline in populations, with the OSU and
GISS models predicting moderate declines and the GFDL model predicting population elimination. Simulation
at Minneapolis gave the most mixed results between the different scenarios, with a population increase for GISS,
no change for OSU, and population elimination for GFDL.  In general, for locations where simulation indicated
a moderate decline in population, the GFDL model showed the greatest decline.


RESULTS WITH MALSIM

        Simulated levels of malaria transmission potential at various locations in the United States with normal
weather and the three modified weather scenarios are presented in Figure 4.  These results show that for the
locations with the highest normal malaria transmission potential (Miami, Key West, and Orlando) there is very
little change for any of the modified weather scenarios. For Jacksonville, which has a medium transmission level
with normal weather, the results of the scenario models were mixed, with the GFDL model showing an increase,
no change for GISS, and a decrease for OSU. As a practical matter, the changes at Jacksonville appear to be
of little importance. At other locations with normally low transmission potential, only the GISS model appeared
to result in significant increases in transmission potential. The GISS model produced increases at San Antonio,
Atlanta, Nashville, and Richmond, with the largest increase at Atlanta. Simulations at Tulsa, Dallas, Baltimore,
Indianapolis, and Boston indicated extremely low normal  transmission with no significant change with any
modified weather patterns.  Overall, these simulations suggest that the proposed climatic changes will have little
if any impact on transmission potential of malaria in the United States.
                                                2-5

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         CO
         >
         CO
         a
         o
         c.
         o
               340
                         Rocky  Mountain   Spotted  Fever

                                Tick Density VS HMSF Cases  in VA fi US
                  50 Si 52 53 54 55 56 57 58 59 60 6162 63 64 65 66 67 68 69 70 7172 73 74 75 76 77 78 79 80
              Adult ADT-VA.tfiO
          Year
-i-  RHSF Cases-Virginia
o  RMSF Cases-USA/100
   Figure 1. Graphs showing the yearly variation in simulated American dog tick density and the number of Rocky Mountain spotted fever
35         cases in Virginia and in the U. S. with normal weather from 1950 to 1983.

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                                   Richmond,   VA
     g
     {2
     3
34
32
30
28
26
24
22
20
IB
16
14
12
10
 8
 6
 4
 2
              50515253545556575859606162636465666768697071727374757677787980
                    NORMAL
                                Year
                        +   6FDL         o   QSU
6ISS
Figure 2. Graphs showing the yearly variation in simulated American dog tick density at Richmond, VA, from 1950 to 1980 with normal
       GFDL, GISS and OSU weather scenarios.

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          SIMULATED  AMERICAN  DOG  TICK DENSITY AT VARIOUS LOCATIONS
          Los Angeles, CA
           Richmond. VA
           New York, NY
              Boston, MA
           Columbus, OH
          Jacksonville, FL
             Medford, OR
            Nashville, TN
               Tulsa, OK
          Minneapolis, MN
          San Antonio, TX
             Halifax, N.S.
             Missoula, MT
          North Bay, Ont.
         Albuquerque, NM
I,i jjuu,,my, iHp KI^mUii>MUi  JJW*

                                m
                                                ^ osu
                                                DD GFDL
                                                m GISS
                                                 NORMAL
X
                        0       5      10      15      20      25      30      35      40
                             DENSITY  (ADULT TICKS  ON  HOSTS/HECTARE)

   Figure 3. Simulated equilibrium density (after 15 years of simulation with constant weather) of American dog ticks at different locations
          with average, normal weather data and modified weather data for each climate change scenario.

-------
           SIMULATED  INCIDENCE  OF MALARIA  AT VARIOUS  LOCATIONS
          Miami, FL

       Key West, FL

        Orlando, FL

     Jacksonville, FL

    San Antonio, TX

        Atlanta, GA

       Nashville, TN

          Tulsa, OK

          Dallas, TX

      Richmond, VA

      Baltimore, MD

     Indianapolis,  IN

         Boston. MA

              TVW>>YlW>YhY>>Y^>>Y\Y>>>Yiy TVYf^ '>Yi^>Tnvy TV^>>>Yl^>TTiW>y
-------
Haile


INTERPRETATION AND IMPLICATIONS OF RESULTS

        These results suggest that potential problems associated with transmission of RMSF and malaria in the
United States will be little worse with projected climatic change than they are today.  However, these are only
two of many vector-borne diseases that are a potential problem in the United States.  Other modeling efforts
would be required to address other tick or mosquito-borne diseases.

        The results in this report are based  on computer models, which, although complex and useful from a
research standpoint, have serious limitations for projecting the effects of climatic change. The limitations involve
development of the models with average weather data and the lack of consideration of the climatic effects on
host densities and  habitat.  Additional research  on .biology, ecology, and modeling of these and other
vector/disease systems will be required for a more complete analysis of the potential effects of climate change.
                                                2-10

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                                                                                           Haile


                                         REFERENCES


Dietz, K., L. Molineaux, and A. Thomas. A malaria model tested in the African savannah. Bull. WHO. (50):347
57,1984.

Fine, P.E.M., M.M. Milbey, and W.C. Reeves. A general simulation model for genetic control of mosquito
species that fluctuate markedly in population size.  J. Med. Entomol. (16):189-199,1979.

Haile, D.G. and D.W. Weidhaas.  Computer simulation of mosquito populations (Anopheles albimanus) for
comparing the effectiveness of control techniques.  J. Med. Entomol.. (13):553-567,1977.

Haile, D.G. and GA. Mount.  Computer simulation of population dynamics of the lone star tick, Amblyomma
americanum (Acari: Ixodidae). J. Med. Entomol. (24):356-369,1987.

Harwood, R.F. and M.T. James. Entomology in Human and Animal Health. MacMillan Publishing Co. Inc.,
New York.  1979.

MacDonald, G.  The Epidemiology and Control of Malaria. Oxford University Press, London. 1957. 201 pp.

Molineaux, L. and G. Grammiccia. The Garki Project:  Research on the epidemiology and control of malaria
in the Sudan savanna of West Africa.  World Health Organization, Geneva, Switzerland. 1980.

Mount,  GA. and D.G. Haile.  Computer simulation of population dynamics of the American  dog  tick,
Dermacentor variabilis (Acari: Ixodidae). J. Med. Entomol. (in press)

Ross, R. The Prevention of Malaria (2nd edition). London: Murray. 1911.

Russell, P.F., L.S. West, R.D. Manwell, and G. MacDonald.  Practical Malariology. (2nd edition).  Oxford
Univeristy Press, London 1963.

Sonenshine, D.E.  Influence of  host-parasite interactions on the population dynamics of ticks.   Misc. Pub.
Entomol. Soc. Am. (9):243-249,1975.

Sutherst, R.W., R.H. Wharton, and K.B.W. Utech. Guide to studies on tick ecology, CSIRO Aust. Div. Entomol.
Tech. Pap. 14.1978.

Warren, FCS. and AA.F. Mahmoud. 1984. Tropical and Geographical Medicine. McGraw-Hill Book Company,
New York, 1984.
                                             2-11

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THE POTENTIAL IMPACT OF CLIMATE CHANGE ON PATTERNS OF
         INFECTIOUS DISEASE IN THE UNITED STATES
                            by
                       Janice Longstreth
                       Joseph Wiseman
                  ICF/Clement Associates, Inc.
                       9300 Lee Highway
                     Fairfax, VA 22031-1207
                    Contract No. 68-01-7289

-------
                                 CONTENTS
FINDINGS 	   3-1

CHAPTER 1:  INTRODUCTION	   3-2

CHAPTER 2:  VECTOR-BORNE DISEASES	   3-6
      LYME DISEASE 	   3-6
      ROCKY MOUNTAIN SPOTTED FEVER 	   3-8
      MALARIA 	  3-10
      DENGUE FEVER 	  3-12
      ARBOVIRUS-RELATED ENCEPHALITIS 	'	  3-16

CHAPTERS:  ELEMENTS OF INFECTIOUS DISEASE	  3-22
      THE AGENT	  3-22
            Agents Not Currently Present in the US	  3-22
            Agents Currently Found in the US	  3-23
      THE VECTOR/ANIMAL HOST 	  3-24
      DEFINITIVE HOST	  3-26
      ADDITIONAL DISEASES 	  3-27

CHAPTER 4:  POLICY IMPLICATIONS 	  3-30

CHAPTER 5:  SUMMARY AND CONCLUSIONS	  3-31
      ADDITIONAL RESEARCH NEEDED ..l.	  3-31
                                       i
GLOSSARY  	  3-32

REFERENCES	*/..-	  3-36

APPENDIX	  3-42

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                                                                                           Longstreth

                                             FINDINGS1


        The climate of the United States is expected to change as a result of the increased concentration of a
number of "greenhouse gases."  Although there will be an overall net global warming, the distribution of this
warming will not be the same throughout all regions.  Changes in temperature, rainfall, and other climatic
elements will vary considerably by region.

        The United States Environmental Protection Agency (EPA) is concerned that these climatic changes
will increase the morbidity and mortality of infectious disease in the United States. A two-day workshop was
convened to address the questions relating to this issue, including the following: Which infectious diseases will
become a greater health problem; what public health measures can be taken to lessen the potential impact of
these diseases; and what research agenda should be established in regard to these issues.

        The workshop decided that given the present levels of sanitation, immunization, and nutrition in the
United States, malaria, dengue, yellow fever, and several skin diseases pose the greatest threat of increased
morbidity and mortality.

        The workshop also concluded that the decrease in the support of public health programs, particularly
those in disease surveillance and vector abatement, create the greatest threat to effectively combating increased
morbidity and  mortality  caused by  climate change.   It  was also  concluded that  the development  of
multidisciplinary teams including experts from the fields of behavioral science, entomology, and epidemiology,
need to be established in order to develop programs to effectively meet the changes in infectious disease patterns
caused by climate change.
        'Although the information in this report has been funded wholly or partly by the U.S. Environmental
Protection Agency under Contract No. 68-01-7289, it does not necessarily reflect the Agency's views, and no
official endorsement should be inferred from it

                                                3-1

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Longstreth

                                            CHAPTER 1

                                          INTRODUCTION


        The climate of the United States is expected to change due to an overall net global wanning, which has
been predicted to result from the increased global concentration of a number of "greenhouse gases" such as
methane, carbon dioxide, and chlorofluorocarbons (CFCs) (EPA/UNEP, 1986; MAS, 1983).  These gases are
called greenhouse gases because they allow incoming solar radiation to pass through the earth's atmosphere but
absorb outgoing infrared radiation thus resulting in warming within the confines of the atmosphere much  as is
seen within a greenhouse.  Within the United States, it is expected that changes in temperature and rainfall will
vary considerably by region, with some regions becoming colder and others warmer, as well as wetter or drier.
Figure 1 presents one set  of changes in temperature  and rainfall, those predicted by the General Circulation
Model (GCM) developed by NASA's Goddard Institute for Space Studies. Other GCM model predictions differ
significantly from NASA's. While the quantitative and qualitative degree of regional climate change varies from
model to model, it is relatively certain that  temperature will increase by three to five degrees on average  with
a doubling in CO,. This paper attempts to discuss, based on available data, how infectious disease may vary with
normal changes in climatic factors.

        EPA has been requested to prepare a report for  Congress on the potential adverse effects that might
be seen in the United States due to the global warming. One of EPA's concerns is that, associated with changes
in climate throughout various regions of the United States, there will be changes in the morbidity or mortality
of infectious diseases , both those endemic in the United States and those which may be introduced from other
locations. This report addresses EPA's concerns with regard to the infectious diseases that currently occur in
the U.S. or that plausibly might be imported; the worldwide impact of climate change on infectious diseases is
beyond the  scope  of  this  report.  The document has two  goals. One goal is to attempt to determine the
likelihood (with attendant uncertainties) that increased morbidity and mortality from particular infectious diseases
will occur in the U.S.  owing to changes in climate, and the second goal is to identify the information necessary
to reduce the uncertainty in these conclusions.

        It has been many decades since infectious diseases were the  major causes of mortality in  the United
States, as they are now in large parts of the world.  Figure 2 compares the  10 leading causes of death in the
United States for 1900 and 1981.  The leading causes of mortality at the turn of the century were (Mauser and
Kramer, 1985) pneumonia and influenza, with tuberculosis  second. By 1980, pneumonia and influenza were
significantly reduced in importance  and  tuberculosis was not one of the ten leading causes of death.  The
differences in the leading causes of death in the United States between 1900 and 1980 are principally  due to
improved sanitation, housing, nutrition, immunization programs, and treatment. It seems unlikely that climate
change will cause a return of these diseases as important  causes of mortality.

        Nevertheless, certain infectious diseases are not necessarily mitigated by improvements in sanitation,
nutrition, immunization and treatment. These diseases present the greatest public health threat either because
there are no vaccines or treatments currently available, because the infectious agents are not  significantly
    throughout this report, the terms 'climate' or 'climatic change' are used generically.  Unless otherwise
 defined, use of the terms includes changes in temperature, rainfall, humidity, length of day, average daily solar
 radiation, and/or storm patterns, as well as changes in the frequency of rare events such as floods or droughts.

    3This report addresses climatic changes likely to be induced by increases in the amount of greenhouse gases,
 with the exception of the probable impacts of increased UV-B brought about by stratospheric ozone depletion
 by CFCs. For an evaluation of that impact see Longstreth et al. (1987).

                                                  3-2

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                                                                                            Longstreth
Figure 1.     (a) Global patterns of surface temperature and (b) global changes in moisture patterns.



Source: Peters and Darling (1986).
                                                  3-3

-------
 Longstreth
1900
) 100 200 C
Influence ond pnufl*onM|

TuDercutoM,aU forms)

Gastroenteritis 1

On. of heart I

Jvwcutar lesions of ens.
[Chronic nephritis
|A1I Occidents
iMoliqnont neoplosms
fCertoin diseases of eorly
	 infancy
IPiphtherKi
1981
) 100 ZOO 300 4O
Oiseoies of the heart |

MoUgnont neopkMJra)

ICerebrovoKular diseous

' |Accident and adverse effects

""Jchronic obstructive pulmonary diseases
] Pneumonia and influenza
^Diabetes mellitus
jChronic liver disease and cirrhosis
] Atherosclerosis
| Suicide
Figure 2.     Death ratio for the ten leading causes of death in the United States 1900 and 1981.
Source: Mauser and Kramer (1985).
                                                 3-4

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                                                                                             Longstreth

impacted by sanitation or nutrition, and/or because there may be significant portions of the United States
population who have substandard access to such controlling factors.  For the most part, diseases with these
characteristics appear to be those that are vector-borne4. Thus this report focuses on this subset of infectious
diseases in order to evaluate whether these diseases are likely to show changes of incidence within the United
States following changes in climate. This evaluation will be based principally on information derived from five
examples of vector-borne diseases, some of which currently exist in the United States and some of which either
once existed in the VS. and/or exist in locations near its borders. This subset of infectious diseases was chosen
because a significant amount of information suggests that the prevalence and distribution of the vectors of these
diseases can be  affected by climatic variables, which in turn suggests that changes in  climatic  variables could
change  the prevalence and distribution not only of vectors but, most importantly, of the agents they cany.

        There are at least two ways in which climatic change may impact vector-borne diseases. One mechanism
of change is brought about by the direct impact of climatic change on the agent, vector, or host. For instance,
changes in  temperature, rainfall, humidity,  or storm patterns  that directly impact the  multiplication or
differentiation rate of the vector or the agent, increase the biting rate of the vector, or increase the amount of
time that the host is exposed to the vector, would be considered direct impacts of climate change. A second
mechanism of change is brought about by the indirect impacts of climate.  In this category, climate influences
some parameter that is important to vector spread or survival, such as the type of agriculture or the species of
trees in a forest; this, in turn, changes the relationship between the parasite,  vector, and  host.  Both types of
impacts are considered in this report; clearly, however, the direct impacts are easier to evaluate than the indirect
ones.

        The report5 first evaluates what is known about the impact of climatic factors on  five vector-borne
diseases:  Lyme  disease, Rocky Mountain spotted fever, malaria,  dengue fever,  and viral encephalitis.  A
discussion of several additional diseases determined by the workshop  participants to be important is then
presented. The information from these sections is analyzed for what can be genetically stated about the effects
of climate on agents, vectors and hosts.  The final section presents the summary and policy implications.
    4Vector-borne infectious diseases are those diseases in which the infectious agent is transmitted to the human
host via an agent - the vector.  The vectors for most of the diseases likely to be observed in the U.S. are
arthropods, e.g., fleas, ticks, and mosquitoes.

     Notable examples of vector-borne diseases include malaria, which is transmitted to humans via mosquitoes,
and bubonic plague, which is transmitted via infected fleas. (Plague is also transmitted directly from animals to
animals, including humans, as a respiratory disease.)

    *This report is limited to those diseases afflicting humans. Animal diseases, whether veterinary or of wildlife,
will also be impacted by climatic change, and are the subject of a separate report.

                                                 3-5

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Longstreth

                                            CHAPTER 2

                                    VECTOR-BORNE DISEASES


LYME DISEASE

        Lyme disease, initially recognized in Lyme, Connecticut, in 1975, is caused by a spirochete, Borrelia
buredorferi. and is transmitted by ticks  of the Ixodes  ricinus  complex.6   It is an  inflammatory  disease,
characterized by a distinctive skin lesion, erythema chronicum migran (ECM), systemic symptoms (profound
fatigue,  fever, chills, headache,  and backache), polyarthritis,  and cardiac and neurologic abnormalities which
occur in varying combinations  (Habicht et al.,  1987).  Symptoms are acute, lasting several weeks for most
patients. Treatment with antibiotics is available and eventually complete recovery ensues (Braunwald et al.,
1988).

        The life cycle of the tick vector normally spans two years. Eggs are laid in the spring to hatch a month
later into the larval form.  During the first summer, the larva feed once on the blood of the host, then enter a
resting stage with the onset of cold weather. The next spring, the larvae molts to become a nymph, which again
attaches itself to an animal host.  The  nymph stage is primarily responsible for disease transmission  (Steere,
1979).  At the end of the summer, the nymphs molt into adults.  They can be found in brush about one meter
above the ground, where they easily attach to larger mammals (Habicht et al., 1987). Lyme disease is usually
contracted between May 1 and November 30.  The majority of cases are acquired in June and July  (Steere,
1983b).  This time frame corresponds with the peak questing period of Ixodes dammini. which for nymphs is May
through July.

        The  principal hosts for juvenile and  mature forms  of I.  dammini  are  the white-footed mouse
(Peromvscus leucopus) and the white-tailed deer (Odocoileus virginianus). respectively.  In addition,  approx-
imately 80 species of birds, mammals, and lizards have been identified as hosts of I. pacificus.  It appears that
lizards and Columbian black-tailed deer are the most important host of immature and adult I. pacificus. respec-
tively (Westrom et al., 1985; Lane and Burgdorfer, 1986).  The major importance of migrating birds as hosts is
that they facilitate the  movement  of infected vectors over a large geographic radius, thereby substantially
enlarging the geographic range  of the vector and the agent (Hoogstraal et al., 1963; Spielman et al., 1985).  In
areas on the North Atlantic coastline, 80-90% of Ixodes ticks have B. burgdorferi in their gastrointestinal tracts.
This rate contrasts with only a 3% rate of infection of I. pacificus on the West Coast. These rates correlate with
the relative prevalence of the disease in the two areas.

        Although Lyme disease has been reported from  over 25 states, it has four major foci in the United
States (Figure 3).  It has also been reported in Germany,  Switzerland, France, and Austria. In 1975, 59 cases
were recorded in Connecticut; in 1985, the number had climbed to 863 cases (Habicht et al.,  1987).   Similar
statistics are reported from New Jersey, with incidence increasing from 14 cases in 1980 to 39 in 1981 to 56 in
1982 (Bowen et al., 1984).  Age-specific attack rates show that the risk of contracting Lyme disease is about equal
in all age groups through age 50. After age 50, the risk lessens, probably because  older persons are less likely
to be present in tick-infested areas (Steere, 1983a). Better  reporting may contribute to the increase in incidence
statistics.

        Lyme disease appears to occur wherever the vector is abundant. The presence of the vector in the
northeast seems to depend  on the  presence of the white-tailed deer (Main et al., 1982).  The range of the
northeastern subspecies (Q.y. borealis) is the known range of the vector I. dammini (Spielman et al.,  1985),
    6I. dammini in the northeastern and midwestern parts of the United States, I. pacificus in the western United
States, and I. ricinus in Europe (Burgdorfer et al., 1985). It is also believed that other species of ticks, such as
Dennacentor variabilis. Haemapnvsalis leporispalustris. and Amblvomma americanum. serve as secondary vectors
(Burgdorfer et al., 1985; Schulze et al., 1984; Schulze et al., 1986).

                                                 3-6

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                                                                Longstreth
Figure 3.  Geographic Distribution of Lyme Disease.
                       3-7

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although formal proof of a cause and effect relationship is lacking (Spielman et aL, 1984).  Tick abundance
mayalso  depend upon environmental  factors  such as temperature, humidity, vegetation, and physiographic
features  of the environment (Spielman et al, 1985).  Previous attempts to determine the abundance of L
dammini solely by climate (McEnroe,  1977) failed in that it ignored the distribution of the deer host and the
presence of the tick in Wisconsin, which is a different climatic region (Spielman et al., 1985).


ROCKY MOUNTAIN SPOTTED FEVER

        Rocky Mountain spotted fever7 (RMSF)  (also  known  as tick-typhus) is caused by the small, gram-
negative, coccobacillus Rickettsiae rickettsii. The disease is characterized by fever, chills, headache and rash.
Antibiotics are available for treatment, and vaccinations are available for those at greatest risk for developing
the disease (Braunwald et al., 1988).

        The two principal vectors of RMSF are the dog tick, Dermacentor variabilis. the distribution of which
is shown in Figure 4; the wood tick Dermacentor andersoni. which is found mainly in the Rocky Mountain states;
and Dermacentor occidentals which is found in parts of the western United States. Infection is maintained in
ticks by transovarial transmission and by infectious feeding.  The opportunity for  a tick to acquire  infectious
rickettsiae is limited to the short period (3-4 days) in the life of a susceptible animal when the level of circulating
R. rickettsii in the blood of the host is high enough for the tick to receive an infective dose8 (McDade and
Newhouse, 1986).

        No data  were found concerning  the  impact of environmental temperatures on the infectivity of R.
rickettsii: however, data on R. mooseri. the agent for murine typhus, indicates that ambient temperature has a
profound effect upon rickettsial growth in  fleas,  as well as the survival of fleas themselves.  At  18C, the
rickettsial content of .the fleas was below detectable levels for at least ten days and remained low throughout,
whereas at 24 or 30 C, the rickettsial titer was consistently two or three times greater. In addition, if, after six
days, the fleas were transferred from an environment of 18C  to one  of 24 or 30C,  the rickettsial growth
increased by two or three logs within one week (Farhang and Traub, 1985). The coccobacillus is heat tolerant.

        Infection occurs in a large number of animal hosts.  For example, in Maryland and Virginia, antibodies
were found in 15 different mammals  and 18  different types of birds (Bozeman et al., 1967; Sonenshine and
Clifford, 1973). This large spectrum of animaHreservoirs, the fact that several tick species are naturally infected
with R. rickettsii (McDade and Newhouse, -1986), and man's role as an incidental host in the natural cycle makes
eradication of RMSF unlikely.  This is especially true since the United States has no tick control  programs
(Dr. Dan Haile, USDA; personal communication).

         Climatic, ecologic, and geophysical variables influence the timing of outbreaks.  RMSF is a seasonal
disease occurring in the warm periods that coincide with increased tick activity.  In the west, the peak time is
usually the spring and in the east the peak is from May through September.

         Data for the United States population as a whole for 1970-1980 showed more than a doubling in
incidence for the first half of this decade, going from less than 0.2 per 100,000 in 1970 to greater than 0.5 per
    7RMSF is serologically related to R. conori. which causes Marseilles fever, Kenya tick typhus, and India
 tick typhus; to R. siberica. which causes North Asian tick-borne rickettsiosis; and to R. australis. which causes
 Queensland tick typhus.  None of these diseases presently poses a problem in the United States.
        order for a tick to receive an infective dose, the number of organisms has to be sufficient to overwhelm
 the so-called "gut barrier," allowing the organisms to invade the gut epithelium (McDade and Newhouse, 1986).

        is conclusion is also true for Lyme disease, as weU as for other infectious tick-borne diseases.

                                                 3-8

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                                                            Longstreth
Figure 4. Distribution of DejBacgQtfic
                    3-9

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100,000 in 1977 (CDC, 1986Q.  The higher rate was maintained until about 1983, falling to about 0.4 in 1984.
Whether these changes were due to patterns of land use, microenvironmental changes, or other factors could not
be determined from the available data.

        Although the highest incidence of the disease is in children aged 5-9,10 the highest mortality rates occur
in the 40-59 age group11 (D'Angelo et al., 1982).  The fatality rate is about 15 to 20% in the absence of specific
therapy; with prompt recognition and treatment, death is uncommon, yet between 4 and 6% of cases reported
in the United States during recent years have died (APHA, 1980). Figure 5 shows the geographic distribution
of the disease for 1982.

        Prevalence of RMSF has been linked to natural vegetation, which reflects regional climatic conditions.
The density of the principal tick vector also varies with the natural vegetation of the area. The highest incidence
of RMSF has been associated with oak-hickory-pine forests.  Within this general range, highest incidence is
associated with drier, mesic forest types (Sonenshine et al., 1972).12


MALARIA

        Malaria affects a large geographic area.  Over  the past 10-15 years, the prevalance and geographic
distribution of malaria worldwide has increased slowly but steadily, sometimes in small foci, and sometimes over
whole sub-continents.  Its recent worldwide increase is due mainly to mosquito resistance to pesticides, break-
down of control efforts, migration of the vectors, and irrigation.  However, its spread is also environmentally
related.  Man's activities, including agriculture  and road building, have created better habitats (e.g., more still
water) and thus contribute to the spread of malaria into several areas where it was not previously present (De
Zulueta, 1980).

        Four protozoan agents, potentially cause malaria in humans: Plasmodium vivax. P. malariae. P. ovale.
and P. falcipanim.  The most serious form of  malaria is induced by P. falciparum and presents a very varied
clinical picture including fever, chills, sweats, and headache. It may progress to liver damage, coagulation defects,
shock, renal and liver failure, acute encephalitis and coma.   Case fatality among untreated children and
nonimmune adults exceeds 10%. Malaria induced by the other Plasmodium sj>. is generally not life threatening
except in the very young, the very old, or those with concurrent disease.  The less severe forms  of malaria are
characterized by an initial feeling of malaise, usually accompanied by headache and nausea and ending with
profuse sweating. This pattern of symptoms occurs in cycles which appear daily, every other day, or every third
day. Treatment of acute attack can be accomplished with quinine or chloroquinine (Braunwald et al., 1988).

        Plasmodia are transmitted to humans via the bite of anopheline mosquitoes. In the mosquito, plasmodia
go through a complicated life cycle involving a number of differentiation stages. P. vivax and P. malariae require
environmental  temperatures of at least 15C for their  development within the anopheline  mosquito.  P.
falciparum requires temperatures of at least 17 or 18* C for its development to take place (Macdonald, 1957).
With gradual increases in global temperatures since the last ice age (+8.0-9.5) transmission has  migrated from
Africa to southern Europe.
    10In the 5-9 age group, the incidence of RMSF is from 5.4 to 8.5 per 100,000 population in endemic areas.
 For the 10-19 age group, the incidence is from 2.5 to 4.0, and for the group 20 and older, the incidence is from
 1.0 to 2.8 (D'Angelo, 1982).

    11 Approximately 10-12%.

    12The effect of climatic change on forest .growth has been modeled.  See Solomon and West (1984); Botkin
 etal. (1972).

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Figure S. Distribution of Rocky Mountain Spotted Fever for 1982.
                            3-11

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        A number of different anopheline mosquitoes can serve as vectors for the malaria agents. In the
United States, these include Anopheles quadrimaculatus and A., freebornei. In addition,  Plasmodium species
and isolates are known to adapt in order to be able to develop in particular Anopheles species or subspecies
(WHO, 1987).

        Malaria was once a significant health problem in the southern and western United States (Faust, 1938).
Figure 6 illustrates mortality due to malaria in the south for the period 1925-35.  With the realization of the
role played by the mosquito in malaria transmission, breeding of the mosquito was controlled by better drainage
and ambient spraying (Williams, 1938; Williams, 1937). Resistance of the vector to pesticides can make present-
day control programs more difficult.  Both P. falcipanim and P. vivax were present in the United States.

        Indigenous transmission of malaria within the United States, although  rare, is still possible.  Some or
all of the 27 reported case of P. vivax that occurred in San Diego County in June-September 1986  occurred
through indigenous transmission.  A competent vector, Anopheles freeborni. is found in the southern California.
In addition, there have been reports of local transmission among Punjabi immigrants in the Sacramento Valley.
This represent the largest outbreak of malaria in the United  States since 1952 (Brunetti et al., 1954; CDC,
1986a,f).

        With a large influx of immigrants, sufficiently large amounts of the malaria parasite could be introduced
into the United States in the presence of competent vectors. These vectors include An. freeborni in California
and the states that border Mexico, as well as A. quadrimaculatus13 in the entire Southeast during the warmer
months (CDC, 1986a).  As the climate becomes warmer, it may be expected that these vectors will increase in
their geographic range throughout the entire Southeast during the warmer months (CDC, 1986a), and that An.
quadrimaculatus will be present for a larger part of each year. In addition, raising the ambient temperature
could provide conditions more favorable to the replication of the various Plasmodium sj>. within a competent
vector.  If more irrigation is required in areas with increasing  temperature  and adequate drainage is not
concurrently supplied, more mosquitoes  could breed (Gratz, 1973).  Longer seasons for exposure of the host
human to infected vectors could also result.


DENGUE FEVER

        Dengue is  a mosquito-borne virus with four serotypes (Dengue 1-4).  It is classified as a Group B
arbovirus and is antigenically related to St. Louis encephalitis, yellow fever, Japanese B encephalitis, and other
viruses.  Classic dengue fever, which usually  is not fatal,  is characterized by  the abrupt onset of fever and
generalized body aching as well as severe headache and retro-orbital pain. Dengue fever can be complicated by
dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS), both of which can be fatal, particularly
hi young children.

        The principal vector for dengue is the Aedes aeevpti mosquito, whose distribution in the United States
is shown in Figure 7. A potential vector, Aedes triseriatus.:is found throughout the eastern half of the United
States.  In addition, Aedes albopictus. a vector for dengue, originally of northern Asiatic origin, and resistant to
whiter freezing temperatures, has now been found in the United States.  Aedes  albopictus   has both rural and
urban habitats and  is a competent vector for dengue (Anon., 1987a). The distribution of A. albopictus in the
US. is shown in Figure 8.
    13A. quadrimaculatus is highly susceptible to both P. vivax and P. falciparum.


    14A.- albopictus has been shown experimentally to transmit dengue transovarially.

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                                                                                             Longstreth
      i
      c
      1
                                                                                       l3*
                                                                                              18 J.I
Figure 6.     Malaria mortality in the southern states, 1925-1935.

Source: Dauer and Faust (1937).

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                           BREEDING SEASON  OF AEDES  AECYPTI
                           ZONE z  YCA* AftouND
                           ZONC S MIO-JANUARY  TNftOUaH MID- OCCCMMft
                           ZONC SZ MIO-MAIICM THHOU9H MIO-NOVCMBttt
                           ZOMC IT LATE AMIU  TH*OUH  MIO'OCTOBCM
 Figure 7.    Confirmed Dengue cases imported1 into th&United States in 1984 and Aedes aegypti distributioa

 Source:  CDC (1986e).

                                          3-14

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Figure 8. -.   .Counties with confirmed Aedes albopictus infestation in the United States.



Source: CDC (1987).





                                                3-15

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        Dengue is not presently endemic in the continental United States.  However, epidemics have occurred
in the past.   The last such large epidemic occurred in Texas in 1945 (Anon., 1987a). Nine cases of indigenous
transmission of dengue within the United States were reported from Texas in 1986 (Reiter, 1988).

        Although dengue  is not currently indigenously transmitted in the continental United States, it is a
problem in Puerto Rico and also several localities that provide large numbers of immigrants to the United
States.  For example, 2371 cases of dengue (DEN-1, 2 and 4) were reported from Puerto Rico in 1985 (Anon.,
1987b). In addition, dengue had not been reported in Cuba for 30 years, when a DEN-1 epidemic occurred in
1977. This was followed in 1981 by an epidemic of DHF caused by DEN-2, which resulted in at least 158 deaths
(CDC, 1981).  Similarly, in 1978, Mexico reported its first cases of dengue in many years.  The disease became
endemic in most coastal areas of Mexico, and in 1984 cases of DHF were reported (CDC, 1986e). The spread
of dengue and DHF in these countries is following a pattern similar to that found in Southeast Asia, where DHF
is presently a leading cause of hospitalization and death of children.

        Dengue is frequently introduced into the United States by people who have traveled abroad, who return
to areas containing a competent vector for dengue (illustrated in Table 1 for 1982). Although travelers importing
dengue virus into the United States have not introduced a large amount of the virus into a small geographic area,
large numbers of immigrants from dengue endemic areas tend to settle in small geographic areas.  A competent
vector for dengue may be present in these areas.

        Specific experiments have been conducted on the effect of temperature16 on the ability of Aedes aegvpti
to transmit DEN-2 virus.  These experiments showed that the DEN-2 virus was transmitted by A. aegvpti only
if the mosquitoes were kept at 30C. The required extrinsic incubation period was shortened if the temperature
was increased to 32C and 35C (Watts et al., 1987). This pattern of temperature and vector efficiency parallels
the climatic pattern of DHF outbreaks  in Bangkok, Thailand, where case rates rise during the hot season (with
daily mean temperatures of 28-30C ) and decrease during the cool season (with daily mean temperatures of
25-28C) (Watts  et al., 1987).


ARBOVIRUS-RELATED ENCEPHALITIS

        Arthropod-borne viruses (arboviruses) are associated with several major clinical syndromes,  including
encephalitis.  Arbovirus infections were responsible for 65% of diagnosed encephalitis cases reported to CDC
between 1969 and 1979 (Shope, 1980). At least 18 arboviruses cause encephalitis; of these, at least 7 are present
in the United States, including western equine encephalitis (WEE), St. Louis encephalitis (SLE), eastern equine
encephalitis (EEE), California encephalitis (CE), La Crosse encephalitis, Powassan encephalitis, and Venezuelan
equine encephalitis (VEE).
    15Previous large epidemics include:  Pensacola, Charleston, Savannah, and New Orleans (1827-1828); New
Orleans, Mobile, Charleston, Augusta, and Savannah (1850); New Orleans, Savannah, Charleston, and Augusta
(1879-1880); Augusta and Galveston (1885-1886); Texas (1897); Houston, Galveston, and Brownsville (1907 and
1918); Texas, Louisiana, Florida,  and Georgia (1922); Miami, Florida, and Georgia (1934).  Many smaller
outbreaks have also occurred.  For a complete history, see Ehrenkranz et al. (1971). Outbreaks also occurred
in Hawaii in 1913-1915 and in 1943 (Usinger, 1944).

    1sTemperatures required to maintain maximum  vector efficiency  may vary depending on  the specific
disease/vector system.

    17These include encephalitis, yellow fever, hemorrhagic fevers, hepatitis, arthritis, rash, and undifferentiated
tropical fevers.


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             Table 1.  Reported Cases of Dengue-Like Illness in the United States in 1982
State
Alabama*
Arizona
Arkansas*
California

Colorado
Connecticut
D. C.
Florida*
Georgia*
Hawaii*
Idaho
Illinois
Indiana
Maryland
Massachusetts

Michigan
Minnesota
Mississippi*
Missouri
Nebraska
New Jersey
New York
Ohio
Oklahoma
North Dakota
Pennsylvania
Texas*

Virginia
Vermont
Total
Number of
cases reported
7
2
2
3

1
2
2
2
11
2
1
1 1
3
2
16

2
3
1
6
1
5
31
4
1
: 1
7
12

2
1
144
Number of
cases confirmed*



3

-
2

(
2


2


5

1
; ' . .
,-

1
2
11
3
1
L
5
> 5
.
2

45
Travel history for patients with
confirmed cases



South America. Jamaica
Philippines

Jamaica. Puerto Rico


French Guiana. Kenya


Dominican Republic India


Burma. China. Jamaica
El Salvador. Sn Lanka
Puerto Rico

. 

Thailand
Puerto Rico
Suriname. Puerto Rico. India
Puerto Rico. Sn Lanka



Suriname. Michoacan. Mexico
Tamaulipas. Mexico
Venezuela. India


      'Confirmed either seroiogicallv or virologically
      * States with Aeaes legypti dunng much of the year
Source:  Gubler (1983).
                                                3-17

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        The effects of infections with these viruses range from a mild influenza-like syndrome to central nervous
system (CMS) disease, which can be fatal.  Encephalitis is characterized by acute febrile illness (oral temperature
2.100?), with signs of brain parenchymal inflammation that include one or more signs of decreased level of
consciousness (confusion, disorientation, delirium, lethargy, stupor, coma) and/or objective signs of neurologic
dysfunction (convulsion, cranial nerve palsy, dysarthria, rigidity, paresis, paralysis, abnormal  reflexes, tremor,
etc.). Meningeal irritation is often seen in encephalitis patients; symptoms may include aseptic meningitis (acute
febrile illness and signs of meningitis, such as stiff neck) and febrile headache (Monath, 1980). Delayed or latent
CMS sequelae in children who have had encephalitis is also a severe complication (Finley and Longshore, 1958).

        Outbreaks of encephalitis caused by the different viruses are  normally limited to specific geographic
locations and seasons, including seasons in  which arthropod breeding and  feeding  occur.  Most cases of
encephalitis occur in late summer/early fall when mosquitoes, the primary vectors, are prevalent. In addition,
infection depends on certain variables, including the species of mosquitoes that  are susceptible to a specific
virus, and the viral concentration in the susceptible vertebrate host's blood. More than 100,000 infectious units
per milliliter are usually required in order for virulent strains to infect mosquitoes.  An extrinsic incubation (El)
period, i.e., the interval between ingestion of the virus and subsequent transmission through biting, of 4 days to
2 weeks at summer temperatures is normally required, before the virus is fully multiplied and can be transmitted
to a new host.

        Many of these variables are affected by climatic change.  For example, environmental temperature
affects the El (the species discussed here are active at temperatures of 13-35C). Increased temperature can
decrease the El, thereby quickening the transmission process and promoting epidemic disease. Moisture, present
as rainfall  or irrigation, affects  the growth of plant life  for feeding of host animals, and the presence of insect
breeding sites.  Changes in these environmental conditions affect the ability of the vectors  to transmit the virus
effectively. Finally, viruses  carried by the same vectors appear to occur in the same  climatic conditions  and
geographical distributions.  It would follow, then, that the effective spread of the viruses, and usual subsequent
epidemic disease, is dependent upon optimal environmental conditions in which the vectors may breed, feed, and
transmit the viruses. Those conditions, wet or dry, mild or warm climates, vary with the  particular species of
mosquito vector.

        WEE is transmitted in a mosquito-bird cycle18 by the vector Culex  tarsalis.  C. tarsalis mosquitoes
breed in groundwater ponds and abound in irrigated areas of California, Texas, and other parts of south-central
and southwestern United States, where SLE  occurs endemically (Shope, 1980). SLE  accounts for  occasional
small outbreaks each year in humans and for  periodic large epidemics. Warm weather is required to complete
the extrinsic  incubation of the  virus in the mosquito.  As the C. tarsalis naturally feeds on large vertebrates,
equine and human cases occur annually.  WEE, which can be severe but is not normally fatal, is seen primarily
in children under 2 years of age, causing retardation, seizures and spasticity (Johnson,  1977).

        Rainfall19 strongly affects the numbers of infected individuals, since C. tarsalis breed mainly in ground
pools and irrigated ponds.  Environmental temperature also affects the activity of the arbovirus. The maximum
temperature  permissible for the WEE vector to transmit the virus effectively was <, 25C. Above 32C, virus
transmission rates rapidly decreased (Hardy et aL, 1980; Kramer et al., 1983).  A study of El temperatures of
. tarsalis showed decreased vector competence after two to three weeks of El at 32C as compared with vector
    18WEE has an alternative cycle in jackrabbits and A. melanimon.

    19A method used to predict Murray Valley Encephalitis (MVE) in southeast Australia involves the use of
 the Southern Oscillation (SO), which is a mode of climatic fluctuations in the area and is used to predict rainfall.
 Clinical cases of MVE  have tended to occur in summers and autumns following periods of above-average
 rainfall. Darwin atmospheric pressure, an index of the SO, had been below average in the seasons preceding
 epidemics of MVE. This correlation can be used to predict outbreaks of MVE, therefore serving as an early
 warning system (Nicholls, 1986).

                                                 3-18

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                                                                                            Longstreth

competence after El at 18 or 25C. The high temperature did not, however, affect preexisting infection (Kramer
et al., 1983).  Studies  also demonstrate lower effectiveness in WEE virus transmission to humans at higher
ambient temperatures  (Hardy et al.,  1980; Kramer et al., 1983).  The cooler temperatures at which the WEE
virus is better able to replicate allow for epidemic disease much earlier in the summer, and eventually much
farther north in cooler climates later in the season (Shope, 1980).

        SLE is the most geographically widespread arbovirus in the United States and the most common cause
of epidemic arbovirus encephalitis in humans (Johnson, 1977).  The C_. tarsalis mosquito transmits the  virus in
the western United States and C. nigripalpus in Florida in the same manner in which WEE is transmitted.  The
two viruses carried by these vectors are therefore affected in the same way by climatic change. Thus, the vector
and the infection are prevalent in areas and seasons of cooler climate and high precipitation.

        SLE20 in humans has  been reported throughout most of the United States; however, the first reported
Canadian case in humans occurred in 1975 (Spence et al., 1977). During that same year, a widespread epidemic
occurred, with over 2,000 reported cases and 171 deaths, predominantly throughout the eastern two-thirds of the
United States. The epidemic was primarily between late June and October. During that year, precipitation was
below the long-term (1941-1970) average in June  and July,  and temperatures exceeded the normal in May.
Figure 9 shows the percentage of cases of arboviral encephalitis by month of onset and the etiology reported to
the CDC between 1955 and 1971. SLE encephalitis occurred mainly in the late summer and tended to follow
those due to CE  and WEE, but tended to precede cases of EEE (Monath, 1980).  Nearly all epidemics have
shown that the incidence of SLE is 5-40 times higher in persons over 60 years than those in the 0-9 age group
(Monath, 1980).

        Mosquitoes belonging to the  Culex pipiens complex (C.g.  pipiens.  C_.j>. quinquefasciatus.  and C_.
nigripalpus) are the principal vectors for SLE in urban areas.  These species breed in polluted water  of high
organic content; therefore, these species are suited to urban and suburban  areas (Monath, 1980; Shope, 1980),
unlike the primarily rural . tarsalis.  In contrast to the effect of rainfall on  C_. tarsalis. .  pipiens epidemics
occur more often in times of drought and high temperatures.  The lack of rainfall results in poorly draining and
stagnant water, providing increased breeding grounds for the vector (Monath, 1980; Shope, 1980; Johnson, 1977).
The year of the first major epidemic in the United States, 1933, was the driest year recorded since 1837 (Shope,
1980).

        High temperatures favor virus transmission for C. pipiens and C. tarsalis by decreasing the El time, as
well as the time required for larval maturation and development of viral infectivity (Monath, 1980).  Studies of
the relationships between incubation  time of SLE virus in C. pipiens and  mean temperature found that daily
exposures to increased temperatures from a constant of 25C decreased incubation time, thereby increasing
effectiveness of viral transmission (Hardy et al., 1980).  In addition, a review of all the arbovirus encephalitis
cases found in the United States snowed that most WEE outbreaks have occurred  at or above the 70  F June
isotherm, whereas most SLE cases have occurred in warmer latitudes at or below the June isotherm  (Hess,
1963).

        Eastern equine encephalitis (EEE) is transmitted in a mosquito-bird cycle by Cuiseta  melanura.  and
is present in the  freshwater marshes along the Gulf and Atlantic coasts, including the Great Lakes  region
(Johnson, 1977; Shope, 1980).  The vector mosquitoes do not feed on large vertebrates; therefore, infection in
humans is very rare.  However, climatic changes altering the conditions of the wetlands, such as rainfall, could
introduce changes in mosquito breeding or types of susceptible birds. The virus might then spill over to a species
of mammal-feeding mosquitoes, most likely Aedes  or other Coque tidia. via infected birds (Shope, 1980). This
    ^n Florida, the primary urban, as well as rural vector is . nigripalpus. occurring more frequently in rural
areas.  Eight species of SLE-carrying mosquitoes in Florida were studied and found to transmit vertically, with
A. taeniorhvnchus transmitting venereally, although there is no evidence that this occurs in nature. Transstadial
transmission by this species was observed at larval rearing at 18C but not at 27C.  This is a possible over-
wintering host for the virus in Florida because of the abundance  and high transmission rate.

                                                3-19

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          50-1
       UJ
       %
       o
       Ul


       UJ
       Q.
          3CH
          2CH
          10H
SLE
WEE
CE
               JAN FEB MAR'APR'MW^uuN\iui7AU6 'SEP'OCT'NOV'DEC
 Figure 9. Percentage of cases of Arboviral Encephalitis ty month of onset, 1955-1977.


 Source: Monath (1980).
                                     3-20

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is the only route of epidemic transmission of EEE to horses and to humans, in whom infection is rare, but fatal
hi 60% of the cases (Johnson, 1977). EEE affects primarily children, and death usually occurs in the first 2-5
days after onset, characterized by periorbital edema during the acute disease (Johnson, 1977).

        The La Crosse strain of California encephalitis virus causes mild to severe cases of encephalitis in
children ranging from a benign aseptic meningitis to a severe, but rarely fatal, form of encephalitis (Johnson,
1977). There is little information on the effect of climate on the occurrence of the disease. The virus is widely
distributed in the Midwest and the middle Atlantic and Appalachian states (Shope, 1980), and is transmitted by
Aedes triseriatus mosquitoes, which reside in woodland treeholes and feed on small woodland mammals.  A.
triseriatus transmits the virus transovarially,   (Shope, 1980) as well as venereally through infected seminal fluid
(Thompson, 1978), and thus the adult progeny can then transmit the infection by bite upon adult emergence
(Shope, 1980).  This vertical transmission cycle allows for human La Crosse infection during early summer, and
is amplified by infection and viremia in small mammals. The mosquito has a very limited flight range, so humans
are infected only when exposed to the woods or to old discarded tires, which serve as "synthetic treeholes"
(Johnson, 1977).
    _ -            *                             
     In a study of transovarial transmission of CE viral strains in A. dorsalis and A. melanunon. no consistent
transmission rates were found relating to the time of year or location of collection (Turell, 1982).

                                                3-21

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                                            CHAPTERS

                               ELEMENTS OF INFECTIOUS DISEASE


        In the attempt to predict what the potential impacts of climate change might be on infectious diseases,
we decided that the analysis would be facilitated through the development of a conceptual model that looked
at the interrelationship between climate and the elements necessary for a vector-borne disease  to  occur.
Accordingly, given below are brief summaries of information drawn from the five diseases discussed above, which
apply to the three elements of a vector-borne disease: the agent, the vector,  and the host (or hosts).


THE AGENT

        The agent in a vector-borne disease may be a virus, protozoa, bacteria, or helminth.  Infectious agents
are transmitted to their hosts by vectors. The role of the vector may not only be one of transport, but may also
be required for completion of the lifecycle of the agent.  As indicated above, there are two potential concerns
regarding the impact of climate change on disease agents: one is that climate change will allow the establishment
of new agents in the United States; the other is that agents that are presently endemic will flourish, thereby
favoring either enlargement of the geographic area where they are found or greater infectivity in the current
geographic area

Agents Not Currently Present in the UJS.

        Malaria  and dengue are two vector-borne  diseases not currently established in the United States,
although they are introduced regularly and have been established in the United States in the past. Two questions
must be considered in evaluating whether the establishment   of new infectious diseases in the United States is
possible.  The first  is whether  the agent is  currently present or is likely  to become present (by virtue of
immigration, etc) within the geographic range of a competent vector; the second  is whether conditions  are or
will  become  favorable to the development and  spread  of the agent. The minimum amount of agent  in a
geographic area needed to assure transmission of the disease varies with each specific disease.

        Although from time to time infectious diseases may be introduced into the United States by the  return
of travelers, generally the geographic distribution of these individuals is sufficiently broad  that the critical mass
of the agent necessary for establishment is unlikely to occur.  For malaria, climatic conditions do not favor the
differentiation of the agent within the vectors which are present.

        Currently, the two most likely sources of introduction of a disease23 into the United States are via legal
immigrants and refugees (principally from Asia) and via migrant workers and illegal immigrants. Between 1975
and 1981,0.5 million Asian refugees settled in the United States. Roughly one third of that population lives in
California; one third lives in the states of Texas, Washington, Pennsylvania, Illinois, Minnesota, Virginia and
Oregon; and one third have settled throughout the remaining states (Cantanzaro, 1982). If immigrants continue
to congregate in nearby areas, a critical mass could be approached.  In addition to these refugees, between 1977
and 1985, the largest number of immigrants admitted to the United States have been from Asia (INS,  1985).
Of the 50 metropolitan statistical areas specifically listed by the Immigration and Naturalization Service as areas
where immigrants intended to reside, 14 are areas presently known to be infested with Aedes aegypti (INS,
    ^Establishment is used here to mean the indigenous transmission of the disease by local vectors to sizable
population.

    23In addition to the diseases discussed elsewhere, the introduction of JBE from Asia, Ross River fever from
Australia,  Chikungunya virus from Asia, and Rift Valley fever from Africa should be considered possible
candidates.

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1985; CDC, 1986e,f).  The fact that a second vector, Aedes albopictus. has become established in northern, as
well as southern states (CDC, 1986b,d), broadens the area in which a dengue virus could become established
given appropriate conditions.

        Another source for the introduction of new infectious agents into the U.S. is via migrant workers (border
commuters) and illegal immigration.  It is estimated that between 4.5 and 12 million illegal aliens reside in the
United States (Bos, 1984), as well as another 1.3 million seasonal workers and border commuters (Corwin, 1982).
It is assumed that these individuals carry the parasites commonly found in their home countries. In addition to
dengue and malaria, large percentages of immigrants and refugees are infected with intestinal parasites (15%
to 78%), positive tuberculin test (49% to 55%) (Arfaa, 1981), and hepatitis B (12% to 36%) (CDC, 1979a,b;
1980c,e; Barry, 1983; McGlynn, 1985; Cantanzaro, 1982; Jones et al., 1980).

        Medical screening of immigrants and refugees does not include testing for arbovirus, malaria, or most
parasitic diseases. The CDC guidelines for medical examination of non-United States citizens seeking entry into
the United States do not include such diseases as one of the "dangerous contagious diseases."24  Nevertheless,
it is estimated that within a single refugee detention center, several cases of dengue are identified each year, with
an occasional large outbreak. There are also confirmed cases of malaria each year.

        This section has  illustrated that sufficiently large amounts of parasites are introduced into the country,
making outbreaks of diseases not previously endemic to the United States possible.  Although other factors also
need to be present, the first element of the infectious disease  relationship is presence of the parasite.

Agents Currently Found  in the U.S.

        For agents of diseases such as RMSF, Lyme, arbovirus-transmitted encephalitis, plague, and other
endemic agents, the critical question is whether changes in climate will either enlarge the area in which they are
present or increase the number of cases seen in the endemic areas. With regard to the role of the agent, is it
likely that replication of the agent in vectors (or hosts) will be more favored under new climatic conditions?  If
the answer to this question is yes, then this could result either in larger amounts of agent per vector, a shorter
time for the agents to reach infectivity within the vector, or a wider geographic area that supports development
of infectious agents in the vector.  Given below are brief summaries of what was found in the literature relevant
to assessing these questions.  Clearly, much is not known.  (A discussion of additional data needs is presented
in the Conclusions and Recommendations  section.)

        Lyme disease currently has four major foci in the United States.  The climatic conditions within the foci
are dissimilar and the transmission of the disease seems to be more dependent on the presence of infected ticks
and their principal hosts, the white-footed mouse and the white-tailed deer, than on the competence of the agent
within the vector.  No data were found to address whether climatic factors can affect the reproductive and/or
developmental  processes of this spirochete within its tick vector.  However, the incidence of the disease is
increasing.

        The incidence of Rocky Mountain Spotted Fever in the United States doubled in the decade of 1970 to
1980, from less than 0.2 per 100,000 to more than 0.5 per 100,000; however, by 1984 the rate was 0.4 per 100,000.
These are nationwide statistics and it  is unclear what they reflect in terms of the agent.  Clearly the agent is
present; however, very little information was found upon which to base an assessment  of how climate change
could affect its distribution or infectivity. If R. rickettsia. the agent for RMSF, behaves like R. mooseri. the agent
for tick typhus, then  one would expect to see  increased rickettsial liters in ticks under warmer  conditions;
however, as discussed below, warmer temperatures could disrupt diapause in  the vector life cycle, which could
adversely affect tick survival or rickettsial cycles.
    24"Dangerous contagious diseases" include AIDS, tuberculosis, VD, and leprosy.

                                                 3-23

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THE VECTOR/ANIMAL HOST

        Vector-borne diseases were selected for study in this review principally because the greatest amount of
information found about the relationship of climatic variables to infectious diseases was found for this subset of
infectious diseases, and the judgment was made that the high levels of nutrition, health care, and hygiene found
in the ILS. were likely to prevent a significant impact of climate changes on other more common bacterial and
viral diseases.  The discussion that follows focuses  principally on the impacts that climatic change could
potentially  have on the tick and the mosquito.  In addition, this section includes information on the impact of
climatic variables on intermediate vertebrate hosts.

        The introduction  of a vector  into a disease process means that there  are now three places (agent,
vector/intermediate host, and human host) that require attention to control a disease, instead of the standard
two (agent and host).   Because of this intermediate step between the agent and the host, control of these
diseases becomes more difficult than control of diseases such as pneumonia or tuberculosis, which are induced
directly by  the agent in the host

        The two most important factors related to a vector's transmission of disease are the geographic range
(both in distance and in amount of time  during  the year that the vector is present)  and the vector's rate of
infectivity by any parasite. The geographic distribution of tick vectors in the United States is determined by a
complex set of factors which are both geographic and climatic in nature. For example, D. andersoni. the vector
of Rocky Mountain spotted fever (RMSF) in the western part of the United States, is associated with "shallow
soils, moderate shrub cover, exposed rock, steep slopes, numerous pines, log litter" and decreasing grass cover
(McDade and Newhouse, 1986). Those same  factors influence the abundance of the vertebrate  host for  the
larval tick.

        Temperature and relative humidity are also important in the vector's spatial distribution.  The relative
humidity must be high enough to prevent desiccation of ticks and their eggs, and the ambient temperature must
be high  enough (app. 20C) to allow the life cycle  of  the vector to be completed. However, winter soil
temperatures must be low enough to release the adult ticks from their diapause, a period of lowered metabolism,
that prevents their feeding in the fall (Wilkinson, 1967; McDade and Newhouse, 1986). This appears to be less
than 5C.  Shorter survival rates have been observed at  75% relative humidity  than at 85-95%, although  the
optimum relative humidity for vector reproduction and survival has not yet been determined (Wilkinson, 1967).

        The difference in the timing of onset  of disease, as contrasted by the pattern of RMSF in Virginia,
Massachusetts, and Nova Scotia, may be explained by the direct or indirect effect of environmental changes. For
example, a change in the temperature isotherms in the various areas could have modified a vector's life cycle,
or a change in the composition of the flora and/or fauna could have resulted in the introduction of an additional
vector whose life cycle differs temporally from the original vector so  that maturing and' overwintering ticks
overlap considerably in terms of the time of activity. The definitive combination of factors that are conducive
to the continued geographic spread of the vector has not yet been determined (Garvie et al., 1978).

        The impact of climatic factors on mosquitoes serving as vectors has been studied for encephalitis virus
infections.  Transmission of arboviruses by mosquitoes is influenced by a number of factors. Among these  are
population levels, biting habits, and the intrinsic factors affecting the actual biological transmission of the specific
agents. These variables are usually very dosely related to climatic change, especially temperature and rainfall,
which in turn determine the geographical distribution of the individual species and the viruses for which they
are specific (specific viruses are carried only by specific susceptible vectors).

         The population levels and biting habits of virus-specific mosquitoes vary according to climate, genetic
determination, and  abundance of hosts.   In  species which  undergo diapause^ and are  thus capable of
    25Diapause is a physiological state of suspended activity or arrested development that facilitates survival
 through a period of unfavorable conditions, but is initiated before the onset of these conditions (Bailey, 1982).

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overwintering, the population levels26 vary throughout the year.  Viral activity is usually increased during the
active summer months and decreased during winter months because of reduced feeding levels related to the
onset of diapause.  Diapause is  induced in late-stage  larvae and pupae  by a combination  of shortened
photoperiod and cooler temperatures, and thus varies temporally with latitude (Bailey, 1982). In a study of Culex
pipiens. indigenous to temperate climates  and capable of overwintering,  and Culex quinquefasciatus. found in
pantropical regions (Florida) and incapable of hibernation, it was found that although both species develop fat
reserves on a sugar diet, only C. pipiens within this complex of species  underwent the additional physiologic
changes associated with diapause in response to exposure to shortened photoperiod and decreased temperatures.
The .  E- quinquefasciatus is apparently unable to utilize its fat reserves or decrease its activity in order to
survive temperate-zone winters. The C. . pipiens. on the other hand, showed signs of overall decreased activity,
including reduced blood-feeding27 (Eldridge,  1968).
        In addition to influencing population levels and biting habits, climate variables strongly influence the
capability and rate of transmission in vectors that undergo biologic transmission. Effective biologic transmission
(or extrinsic incubation, El) depends on several variables such as the infectivity threshold, virus multiplication
rates, and susceptibility and dissemination barriers, many of which are temperature-dependent.

        The  El period is the time required  after ingestion of an infective blood-meal, during which the viral
multiplication takes place and before the virus can be transmitted orally by the vector (Hardy et aL, 1983). The
specific time  varies for each virus and mosquito, and the length of time the mosquito must be able to survive
after ingestion  in order to  transmit the virus can be determined from it.  Longer survival rates of mosquito
populations, then, are required to maintain cycles of viruses with long El periods (Hardy et al., 1983).  Viral
multiplication rates vary directly with temperature, as shown in a study of vector capability of Aedes aegypti for
California encephalitis virus and dengue viruses at various temperatures.  A. aegvpti is indigenous to wanner
climates and  is a highly effective vector of dengue, a tropical arbovirus, but is an ineffective vector of CE28,
which is endemic at latitudes where frigid conditions prevail. At a range of temperatures, the El period of DEN-
2 virus increased from 6-13 days with a decrease in temperature from 90-75F.  Transmission of the Yukon
strain of CE was very ineffective, with El periods of 3 weeks at 80F, and 4 weeks at 55F (McLean, 1977). In
a similar study of A. aegvpti. viral replication of Yukon and Norway strains of CE and MVE (found in moderate
climates) was seen in its full viable range (13-39C),  with rates of viral multiplication  decreased  at lower
temperatures and increased at higher (McLean, 197Sa,b). Therefore, although the A. aegvpti is susceptible to
infections from regions of  the world  in which  the species is absent, the decreased temperature has such a
negative effect  on the El period that this warm-climate vector would  not  be a competent vector in colder
climates.

        The infectivity threshold (IT), or concentration of virus that must be ingested by the vector in order for
strains to become infective, varies among viruses and mosquito species. There are many barriers, such as salivary
gland and mesenteronal barriers^9 preventing infection of certain tissues, and so the most effective viruses have
the lowest infectivity thresholds.  However, a low IT is not necessarily a requirement for successful transmission
     An investigation of seasonal biting habits of Aedes aegvpti in Bangkok, Thailand, showed little fluctuation
in the seasonal population levels of the mosquito. The increased occurrence of dengue hemorrhagic fever during
monsoon season could not be attributed to an increase in population due to the heavy rainfall, but rather to the
increased activity of the existing population under favorable climatic conditions (Yasuno and Tonn, 1972).

     The same study indicated a correlation of lower body fat with more normal ovarian development.
        is ineffective only because it cannot diapause. However, A. albopictus is not so affected by colder
conditions.

    29These barriers are not directly affected by climate change, but rather by dose and time, and are primarily
genetically determined.  They are therefore beyond the scope of this report and will not be discussed.

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if the virus produces very high levels of viremia in its vertebrate host, or if transovarial (vertical) transmission
is possible (Hardy et al., 1983).

        Transovarial transmission has been observed in many mosquito species and is considered to be a primary
means by which some arboviruses are maintained during winter, dry seasons, and under adverse environmental
conditions under which their arthropod hosts are either inactive or unable to survive.  This is especially important
in species in cooler climates and incapable of overwintering.  Transovarial transmission was first observed for
yellow fever virus in A. aegvpti  in 1905 (Rosen, 1981). Vertical transmission of SLE has also been widely
demonstrated in eight species which occur in Florida. In this study, larval rearing temperatures affected such
transmission of the virus in A. taeniorhvnchus. with effective transmission at 18C, but not at 27C (Nayar et al.,
1986).  In a different study, vertical transmission of SLE by female A. albopictus and A. epactius occurred.
Minimal infection rates of F. adults reared at 18C were much higher than in those reared at 27C. This type
of transmission is postulated to be a mechanism for overwintering of  the SLE virus in temperate regions of
North America.  Dengue,  JBE, and yellow fever viruses are also transmitted vertically at low levels by Aedes
mosquitoes (Hardy et al., 1980).

        It is difficult  to make any generalizations regarding the geographic distributions of specific vectors
without addressing each one individually. However, based on the affects of temperature changes, one can make
a broad conclusion that species that are capable of overwintering or of transmitting vertically, and which have
higher rates of transmission at lower El temperatures, are more likely to be found in latitudes corresponding to
temperate-zone to arctic-zone  climates.  The viruses for which they are specific will also be endemic to those
areas.


DEFINITIVE HOST

        The definitive host is the organism where the infectious agent grows and sexually multiplies. For these
vector-borne diseases, the  human host provides nutrition and the necessary environment for proliferation. The
information on the five vector-borne diseases was reviewed; very little information was found specifically relating
to the impact of climatic factors  on modifying the role of the host in the infectious disease process.

          ...it is becoming increasingly evident that man rather than nature is likely to be responsible
          for the direct or indirect dispersal of an arbovirus over great distances.  Although by no
          means proved,  it is distinctly possible that recent major and singular epizootic epidemic
          outbreaks of Venezuelan equine encephalitis in Central and North America and of Rift
          Valley fever in Egypt were caused by human  behaviour. In any event, it is now clear that
          most disease-producing arboviruses are not introduced into a known endemic region
          annually by migratory birds or other long-distance non-human travellers (WHO, 1985a).

Theoretically, there are two types of human activity that could impact the disease process and could in turn be
modified by changes in climate: those activities that humans as society undertake and those activities that humans
as individuals undertake.

         Human activities in the societal sense, particularly as they relate to the environment,  increase or
decrease the amount of disease.  Clearings, power lines,  logging roads, and campsites frequently become heavily
infested with ticks  carrying RMSF (Hoogstraal, 1981).   Increased  use of irrigation may lead to increases in
mosquito populations (Gratz, 1973).

           The disappearance  of plague from Uganda coincided with the introduction  of antibiotics
           and DDT but probably had nothing to do with either, just as the virtual disappearance of
           malaria from die USA in the 1950s (which stood at 4 million cases per year  in the 1930s)
           had little, if anything to do with the new anti-malarials and DDT.  I well remember L.W.
           Hackett emphasizing this point when I was studying epidemiology at Berkeley in 1955. In
           the USA, as in Western Europe, changes in  the ways of man were probably involved.


                                                 3-26

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          Perhaps some of us should be making a special study of the factors involved in bringing about these
          great recessions with as much energy as we bring to the study of the factors  responsible for the
          establishment of endemic and epidemic conditions (Gillett, 1985).

        The environmental changes  resulting  from global climate change as well  as  the activities  taken in
response to these changes could potentially result in changes in the pattern of infectious disease.   All the
implications of global  climate change are not yet known; however, within EPA's program  to evaluate the
potential impacts, consideration is being given to how hydrology, agriculture, forestry and infrastructure will
change on a regional level (EPA, 1987).  Potential changes which would result from sea level rise and changes
in temperature and rainfall patterns include increased use of irrigation and impacts on wetlands and coastal, lake,
and river ecosystems, such as geographic shifts and changes in composition;  changes in the composition and
growth rate of forests; and changes in crop yields, geographic distribution, and pesticide use.  All  of these
changes have potential for impact on disease patterns and the growth and development of  agent-vector pairs.

        Perhaps of equal importance in the transmission of infectious disease in the United States is man's
behavior as an individual.  The best studied example of this is the use of air  conditioning  and television as it
relates to mosquito-borne encephalitis in the San Joaquin Valley (Gahlinger et al., 1986).  It was found that the
use of these appliances decreased the amount of time people spent outdoors on summer evenings, the feeding
time for the vector Culex tarsalis. The decreased prevalence of WEE and  SLE in humans, together with the
virus* continued presence in avian and equine populations, as well as  the prevalence  of  the vector, can be
accounted for only by the individual activities of man.


ADDITIONAL DISEASES

        Participants at the workshop identified three additional diseases that they felt deserved attention in this
report. A brief description of these diseases is given below.

        Rift Valley fever (RVF) is a mosquito-borne, acute febrile disease of cattle, sheep, and man.  It is
characterized  by  fever,  vomiting, hemorrhagic manifestations, vascular  retinitis,  encephalitis, and CNS
complications (WHO,  1985b).   RVF has long been recognized as a self-limited human febrile disease in
veterinarians, butchers and shepherds. A1975 RVF outbreak in South Africa produced the first known outbreak
of RVF with encephalitis and fatal hemorrhagic fever (WHO, 1985a).

       Although RVF has generally been confined to sub-Saharan Africa, outbreaks occurred in 1977-78 in the
irrigated region of Egypt with devastating consequences. It is estimated that between 20,000 and 200,000 cases
and 600 deaths occurred. Tests confirmed that RVF had not previously occurred in Egypt  (WHO, 1985a).

        RVF has not yet been reported outside Africa. However, the 1977-78 outbreak in Egypt demonstrated
that it can occur in new areas with devastating  results. Although the natural reservoir of RVF is unknown, it
is believed that cattle and sheep act as amplifiers of the disease. At least  26 species of mosquito have been
implicated as potential  vectors  of the virus by isolation in laboratory experiments including . pipiens (WHO,
1985b).  Its penetration into Egypt represents movement into a totally new ecosystem and  combined with the
severity of die human epidemic, it demonstrates disastrous potential for areas  outside Africa.

        Yellow fever, which shares clinical features with other hemorrhagic fevers, but has a more severe hepatic
involvement, is a viral disease endemic to the tropical regions of the Americas  and Africa.  It is transmitted by
mosquitoes from monkey to man and from man to man.  At present, yellow fever has been reported from ten
Latin American countries with most  cases coming  from Bolivia,  Brazil, Columbia,  and Peru (WHO, 1985a;
Monath, 1987).

       Of particular importance is the outbreak of yellow fever in urban areas infested with A. aeevpti. which
is present in large parts of the United States.  Several outbreaks of urban yellow fever have been traced to
persons who were infected in forested areas and subsequently brought the disease to the city (WHO, 1985b).


                                                3-27

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        Although an effective vaccine for yellow fever exists, supplies are not adequate. Should an outbreak
occur in the continental United States, it has been predicted that supplies could not be produced in sufficient
amounts to prevent an epidemic (Drs. Robert Shope and William Reeves, personal communication).
        The changes in climate will increase the incidence and severity of skin infections and infestations.  Skin
infections, including dermatophytosis,30 candidiasis,31 streptococcal pyodenna, erythrasma, tinea versicolor,32 and
scabies are altered by temperature and humidity (Taplin et al., 1987). The importance of lifestyle and behavior
upon contracting disease cannot, however, be dismissed.

        Skin diseases were the single greatest cause of outpatient visits to Army medical facilities during the
Vietnam War (Allen, 1977). When compared with temperature, relative humidity, and rainfall, outpatients' visits
coincided with the mean monthly index values for rainfall and relative humidity, but were four months different
from variations in monthly temperature (Figure 10).  Thus, outpatient skin diseases were directly affected by
rainfall and relative humidity, but not by temperature changes (Allen, 1977).
    3ttThe dermatophytes consist of three genera of fungi - Microsporum, Trichophyton and Epidermophyton.
 The infections caused by these fungi are usually referred to as ringworm or Tinea (Stein, 1983).

    31 Of the seven species of Candida known to infect man, the majority of infections are composed of Candida
 albicans. Although Candida albicans is a common inhabitant of the human body, it is increasingly a cause of
 serious inflection (Stein, 1983),

    3zlinea versicolor is caused by the infection of the superficial layer of the epidermis of the yeast Malassezia
 furfur (Stein, 1983).

                                                 3V28

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       cr
       UJ
       01
       UJ


       Q.


       O
1200


1100


1000


 900


 800


 700


 600


 500


 400


 300
                _      OUTPATIENT VISITS
                                                RELATIVE
/
^ y

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~  t
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\N JUN
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JAN JUN
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> HUMIDITY
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                                           MONTH AND YEAR
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                                                                          TEMPERATURE CC)-J

                                                                             RELATIVE HUMIDITY
88


86


84


82


80


78


76


 74
Figure 10.   Outpatient visits for skin diseases in relation to mean monthly temperature, rainfall, and relative
            humidity for VS. Army personnel in Vietnam, 1967-70.

Source: Allen (1977).
                                               3-29

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                                            CHAPTER 4

                                      POLICY IMPLICATIONS


        A major focus of the two-day workshop was to address the issue of what policies would need to be
implemented to lessen the increase in morbidity and mortality from infectious disease caused by climate change.
It was felt that there was already a significant amount of information known that could be preventively used to
combat the spread of infectious disease in the United States.

        The  workshop participants felt that disease and vector surveillance programs are a cornerstone to
dealing with the issues. Several states have in place surveillance programs which are adequate to deal with the
problems (e.g., the California Encephalitis Surveillance Program). However, these programs are in danger of
not being able to deal effectively with the situation because of a decrease in state and federal funding and a lack
of trained personnel.  There are also many areas in the country where these programs do not exist and  may
need to be established.

        A major concern of the .workshop was the deterioration in the centers of excellence that could be called
upon to spearhead  drives against the increases in infectious disease.  For example, the number of arboviral
research units in the United States has decreased, and it  is the belief of  the  workshop attendees  that the
expertise may not be present in sufficient quantities to deal  effectively with the situation.

        The  workshop attendees found that these issues are multidimensional in nature, and effective solutions
would also have to be interdisciplinary. It was, therefore, felt that interdisciplinary teams need to be established,
so that the groups can be effectively integrated. The workshop felt that an effective integration necessitates
working together for a period of time and, therefore, these groups need to be formed now.

        The  workshop participants expressed great concern that EPA's Endangered Species Act would limit
pesticide use and thereby curtail the ability of various agencies to control vector-borne disease.
                                                 3-30

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                                            CHAPTERS

                                  SUMMARY AND CONCLUSIONS


        As has been discussed, climate has a great impact on patterns of infectious disease in the extent of their
geographic radius as well as in their seasonal duration. Although the importance of certain climatic conditions
has been defined  for a number  of infectious diseases, it is not well understood how changes  in climate,
particularly gradual change, will affect disease patterns.

        This report has reviewed what is known on many of the issues and has presented our best estimates of
how climatic changes could alter the patterns of infectious disease in the United States. Without knowing exactly
what changes in climate will occur (information which the EPA is in the process of generating), it is not possible
to predict what the impacts of the global climate changes due to the emissions of "greenhouse gases" will be.
In addition, recommendations are given below with regard to the data gaps which need to be filled.


ADDITIONAL RESEARCH NEEDED

        In the course  of developing this report, it was  realized that there are many areas that need additional
research.  These research areas  are outside the traditional health literature, but are issues that directly impact
on the question of climatic change and infectious disease.

        o   Research as to the living conditions of the poor in the United States with specifics as to sanitation,
            differences between rural and urban poor as well as use of air conditioning and types of housing.
            All these elements impact on  the interaction of the vector  with man and will influence  disease
            patterns.

        o   Research on the impact climatic change will have on intermediate animal hosts such as the white-
            footed mouse, white-tailed deer, and resident and migratory birds. As the range of the vector is tied
            to the range of the intermediate host, the increase or decrease in the animal host's range may
            correspondingly increase or decrease the area in which the disease is present.

        o   Research in behavioral science as to the impact of climatic change on man's daily life.  This issue
            is related to the amount of time a person would be outdoors and in the vicinity of a disease-carrying
            vector.

        o   Research as to specific changes in agriculture patterns, forest growth and type of forests as these
            factors impact on the presence of vectors  and animal hosts.
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                                            GLOSSARY


anopheline mosquitoes - mosquitoes of the genus Anopheles: many are malarial vectors.

antibiotic - a chemical derived from a fungus or bacteria which is inhibitory to other microorganisms.

antigen - substance which induces an immune response upon contact with the immune system

arbovirus - arthropod-borne virus.

arthropod - member of the invertebrate phylum Arthropoda which includes insects, crustaceans, spiders, and
           ticks.

candidiasis - infection caused by yeast species of the genus Candida, often Candida albicans (Stem, 19831).

CDC - Centers for Disease Control

CE - California encephalitis.

chloroquinine - see quinine.

CNS - central nervous system.

coagulation - the dotting of blood

coccobatillus -  a type  of bacteria.

definitive host - organism in which the infectious agent grows and sexually multiplies; for the diseases discussed
                in this paper, the definitive host is often a human.

Dengue fever - infectious disease caused by the dengue virus, which is transmitted by mosquitoes.

DEN-1, -2, '3, -4 - the four serotypes of the dengue virus.

dennatophytosis - infection caused by fungus of one of three  genera:  Microsporum,  Trichophyton, or
                  Epidermophyton; may be referred to as ringworm or Tinea (Stein, 1983).

desiccation - drying.

DHF - dengue hemorrhagic fever.

diapause - physiological state of suspended activity or arrested development that facilitates survival through a
           period of unfavorable conditions, but is initiated before the onset of these conditions (Bailey, 1982).

dysarthria - malformation  or disturbance of a joint due to emotional stress, paralysis, or spasticity of muscles.

edema - swelling as a result of accumulation of fluid.

EEE - eastern equine encephalitis.

encephalitis - inflammation of fhe brain.

endemic - present in a certain area or among a specific population.


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                                       GLOSSARY (continued)


epithelium - layer of cells covering all free surfaces of an organism.

epizootic - a disease which simultaneously attacks or is present in a large number of animals.

erythema chronicum migran (ECM) - skin lesion consisting of an inflamed, red ring with advancing hardened
        edges leaving a central clear area; emanates from an insect bite; characteristic of Lyme disease.

erythrasma - eruption of reddish brown patches as a result of Corvnebacterium minutissimum.

etiology - cause of disease.

extrinsic incubation (El) period - interval between host's ingestion of the virus and subsequent transmission
        through biting; varies for each virus and vector.

febrile - relating to fever.

gram-negative - a defining characteristic of a group of bacteria; after being Gram stained, gram-negative cells
        do not readily retain crystal violet dye.

helminth -  an intestinal parasite.

hemorrhagic - relating to or characterized by bleeding.

hepatic - relating to the liver.

host - organism from which infectious agent gains sustenance.

indigenous - originating in a particular area

infectious feeding - introduction of the agent to the vector when the vector is feeing on the blood of an infected
        organism.                                                           i

infectious agent - the virus, bacteria, protozoan,  or other microorganism which induces disease.

infectivity threshold - concentration of virus that must be ingested by the vector in order for strains to become
        infective; varies among viruses and vectors.

JBE - Japanese B encephalitis.

larva - immature form of certain organisms (e.g., insects and ticks) which emerge from the egg.

Lyme disease - inflammatory infectious disease caused by the tick-transmitted spirochete, Borrelia buredorferi.

meningeal - relating to the membranes surrounding the  spinal  cord and brain.

meningitis - inflammation of the membranes of the brain and/or spinal cord.

mesenteronal - relating to the layers of tissue surrounding the abdominal viscera

mesic - characterized by a moderate amount of moisture.
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                                        GLOSSARY (continued)


nymph - immature form of certain organisms (e.g., ticks); the larva molts to become a nymph, which is adult-
        like in form though usually smaller.

pantropical - relating to areas which are predominantly tropical.

parenchymal - relating to the distinguishing cells of a gland or organ.

paresis - partial or incomplete paralysis.

periorbital - relating to the area around the eye socket.

photoperiod - duration of light.

plasmodia - members of the family Plasmodiae; blood  parasites of vertebrates.

protozoa - unicellular eukaryotic microorganisms.

pupa - inactive form of an organism during which the larva transforms into an adult.

questing period - time when tickseither nymphs or  adultsare seeking hosts.

quinine/chloroquinine - antimalarial chemical effective against the asexual and red blood cell-attacking forms
        of the plasmodia.

resistance - ability of an organism to remain unaffected by a toxic substance.

retinitis - inflammation of the retina.

rickettsia - a type of coccobacillus (bacteria); all but one of this group are vector-borne parasites.

RMSF (Rocky Mountain spotted fever; also know as tick typhus) - infectious disease caused by the tick-borne
        bacteria Rickettsiae rickettsii

RVF - Rift Valley fever.

scabies - skin irritation accompanied by intense itching caused by the female Sarcoptes scabiei var. hominis
          burrowing into the skin.

sequela - effect of a disease.

serotype - subdivision  of a species or virus identifiable on the basis of antigenic character.

SLE - St Louis encephalitis.

spirochete - spiralling  bacteria.

streptococcal pyoderma - a pus-forming skin infection caused by a member of the genus Streptococcus.

systemic - relating to the organism as a whole.

tinea versicolor - infection of the superficial layer of the epidermis by the yeast Melassezia furfur  (Stein, 1983).


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                                       GLOSSARY (continued)





transovarial transmission - passage of infectious agent to eggs within the ovaries; larvae are subsequently infected.



transstadial transmission - transmission of agent between different stages in the life history of an organism.



vector - organism which transmits the infectious agent to the host; examples include ticks and mosquitoes.



VEE - Venezuelan equine encephalitis.



venereally - relating to sexual intercourse.



vertical transmission - see transovarial transmission.



viremia - the presence of a virus in the bloodstream.



WEE - western equine encephalitis.



yellow fever - acute, harmful infectious disease caused by a mosquito-borne virus.
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                                         APPENDIX
                                   AGENDA OF WORKSHOP
                                          MONDAY
                                     NOVEMBER 9,1987
 8:30 - 9:00 am

 9:00 - 9:30 am

 9 JO -10:00 am


 10:00 -  10:30 am


 10:30 - 10:45 am

 10:45 - 12:30 am

 12:30 -1 JO pm

 1:30 - 2:00 pm


 2:00  - 2:30  pm


 230 - 5:00 pm
Coffee

Opening remarks - Mr. Joel Smith, EPA; Mr. Dan Lasoff, EPA

Presentation - Ms. Eleanor Cross, Naval Medical Research Station, "Use of Climate
and Weather for Predicting Vector-Borne Disease Distribution"

Presentation - Dr. Ronald Schwarz, TRAIN, Inc., "Anthropology and Medical
Ecology in Infectious Disease Research"

Coffee

Discussion

Lunch

Presenation - Dr. Dan Haile, USD A, "Computer Simulation of Vector Population
Dynamics and Disease Transmission"

Presentation - Dr. Byron Wood, TGS Technology, "Use of Remote Sensing to
Monitor the Effects of Climate Change"

Discussion
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                                   AGENDA OF WORKSHOP
                                           TUESDAY
                                      NOVEMBER 10,1987
 8:30 - 9:00 am           Coffee
 9:00 - 9:30 am           Presentation - Dr. David Taplin, University of Miami, "Effects of Climate on Skin
                        Infections and Infestations"

 9:30 -  10:00 am          Presentation - Dr. Paul Reiter, CDC, " Weather, Vector Biology and Arboviral
                        Recrudescence"

10:00 - 10:30 am          Presentation - Dr. Thomas Chambers, St. Jude's, Memphis, "Seasonal Effects on
                        Influenza Epidemics"

10:30 -10:45 am          Break

10:45 -  12:30 am          Discussion

12:30 -1:30 pm           Lunch

 2:00 - 3:30 pm           Discussion

 3:30 - 4:00 pm           Conclusion
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                              GOAL OF THE PROGRAM AND ISSUES
                                     FOR THE WORKSHOP
GOAL:

   The primary goals of the workshop were to determine which infectious diseases would become significantly
   greater human health problems due to climate change and to determine what public health policy decisions
   can presently be made to lessen the morbidity and mortality of these infectious diseases due to changes in
   climate.  The workshop also had the goal the defining of a research agenda for the future.


ISSUES:

1. Which infectious diseases pose the greatest threat in terms of morbidity and mortality within the United
   States due to climate change?

2. To what climate factors do these infectious diseases show the greatest sensitivity and which elements (i.e.,
   agent, vector, reservoir host, human host) are most sensitive?

3. How significant could the infectious disease problem become in the future if temperatures rise by 2 to 4C
   and precipitation changes by +. 20 percent?  What would a 1C rise and a 10% change in precipitation do?

4. Are there any short or long term public health policy decisions currently being made which are likely to
   be impacted by climate change? Examples might be implementation of health screening of immigrants,
   or planning and/or implementing vector control programs.

5. What research needs are most critical in order to develop an assessment of the problem?

6. How would your answers change if these questions were applied to other developed countries?  To
   underdeveloped countries?
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 1.   Which infectious diseases pose the greatest threat in terms of morbidity and mortality within the United
     States due to climate change?

     The consensus of the workshop was that the United States would again have endemic (and epidemic)
     malaria and dengue (which is already present in Puerto Rico) in significantly greater numbers than is true
     today.  These  diseases would be mainly focused  in the  south-southeast and California, although the
     workshop did not rule out that these diseases would also occur in other areas of the United States.

     The workshop also believed that yellow fever would again become a problem, even though a vaccine exists
     for the disease.  This is so because very little of the vaccine exists in the United States (or throughout the
     world) and the supplies would easily be exhausted in the United States should a major outbreak occur.

     It was generally felt that tick-borne diseases such as Lyme disease and RMSF would not become a greater
     problem due to climate change, but that the geographic  focus of the diseases could change.

2.   To what climate factors do these infectious diseases show the greatest sensitivity and which elements (i.e.,
     agent, vector, reservoir host, human host) are most sensitive?

     The workshop  felt that temperature was the most  important climatic  variable and that rainfall was  the
     second most important variable.  Small changes in these variables significantly impact on the geographic
     range and temporal  duration of the vector  which  was considered to  be  the  element most sensitive to
     climatic change.

3.   How significant could the infectious disease problem become in the future if temperatures rise by 2 to 4C
     and precipitation changes by _+. 20 percent? What would a 1C rise and  a 10% change in precipitation do?

     The workshop felt that these relatively small changes would have a dramatic impact in changing patterns
     of infectious disease.  This is due to the real impact that small changes  in climate can have on the vector.
     It was felt that the most important impact would be that small increases  in temperature would increase  the
     geographic range in which the vector would be present throughout the  entire year.

4.   Are there any short or long term public health policy decisions currently being made which are likely to
     be impacted by climate change?  Examples might be implementation of health screening of immigrants,
     or planning and/or implementing vector control programs.

     Several public health decisions are presently being made which will undermine the ability of the United
     States to adequately deal with the changes in patterns of infectious disease brought about by climatic
     change.

     One element is the  lessening of the disease surveillance  system  in the United States.  Without good
     surveillance data, preventive measures cannot be put into operation effectively.

     There are becoming less centers of excellence, such as the arboviral research centers, in the United States
     that are conducting research on these questions and that  will be able to advise  and respond as necessary.

     Due to the lack of career paths and adequate  funding, fewer and fewer individuals, both in the United
     States and throughout the world, are being trained  in vector  eradication techniques. As climate change
     increases the importance of these programs,  there will be a lack of adequately trained personnel to deal
     with the  problem.

     The issues discussed  are multi-dimensional in nature.  There are at present no  multi-dimensional centers
     or groups that have integrated epidemiologists, entomologists, behavioral scientists and physicians that will
     be able to respond to the new problems raised by climate change.
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5.   What research needs are most critical in order to develop an assessment of the problem?

     The workshop felt that the most critical research  needs were the collection of better data as to the
     incidence of infectious disease, particularly in those groups which traditionally do not use the health care
     system, i.e., the poor and recent immigrants.

     It was also felt that greater surveillance of the various disease-carrying vectors is needed so that abatement
     programs can be maintained or developed as needed.

6.   How would your answers change if these questions  were applied to  other  developed countries?  To
     underdeveloped countries?

     In relation to other developed countries, it was generally felt that the same or similar problems as predicted
     for the  United States would occur in those countries. Similar influxes of immigrants from highly endemic
     areas occur throughout Europe as in the United States, and a similar strain on the public health systems
     of those countries is presently taking place.

     The  workshop  believed  that  the  impact  of climate change  on patterns of infectious disease  in
     underdeveloped countries would be significantly greater than in developed countries. This was because the
     public health systems and vector abatement programs in these countries are already overburdened, and any
     additional burdens on these systems will result in significantly greater incidence of disease. In addition, the
     sanitation and nutrition levels in many of the underdeveloped countries will promote a greater incidence
     of infectious disease than in the more developed countries.
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                                    WORKSHOP ATTENDEES
Dr. Joan Aron
Department of Population Dynamics
Johns Hopkins University School of Public Health
615 North Wolfe
Baltimore, MD  21205
301/955-3708

Dr. Thomas Chambers
St. Jude's Children's Medical Research Center
Department of Virology
Box 318
Memphis, TN  38101
901/522-0300

Dr. James Childs
Department of Immunology and Infectious Disease
Johns Hopkins University School of Public Health
615 North Wolfe
Baltimore, MD  21205
301/955-3708

Dr. Jeanne Courval
Division of Epidemiology
School of Public Health
Columbia University
600 West 168 Street
New York, NY  10032
212/305-3921

Ms. Eleanor Cross
Naval Medical Research
Mail Stop 7
Bethesda,MD  20814
301/295-1731

Ms. Margo Daniel
United States Environmental
 Protection Agency
Washington, DC
202/382-2776

Dr. I.F. Goldstein
School of Public Health
Columbia University
600 West 168 Street
New York, NY 10032
212/928-7674
 Dr. John Grayzell
 ST/RD/RRD
 Room 608
 Dept. of State
 Washington, DC 20523
 202/235-8860

 Dr. Dan Haile
 USDA
 1600 SW 23rd Drive
 Box 14565
 Gainesville, FL  32604
 904/374-5928

 Dr. Charles Hughes
 Department of Family and Preventive Medicine
 University of Utah Medical Center
 Salt Lake  City, UT 84132
 801/581-5310

 Ms. Terri  Lavin
 Department of Geography
 University of Delaware
 Newark, DE  19716

 Dr. Janice Longstreth
 ICF/Clement Associates
 9300 Lee Highway
 Fairfax, VA 22031
 703/934-3102

 Ms. Terry Meinking
 Department of Dermatology and Cutaneous Surgery
 University of Miami School of Medicine
 Box 016960 R-117
 Miami, FL 33101
 305/547-6214

 Dr. Greg Mertz
 Tufts School of Veterinary Medicine
 200 Westboro Road
 North Grafton, MA 10536
617/839-5302
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Ms. Marilyn Milby
School of Public Health
Warren Hall
University of California
Berkeley, CA 94720
415/642-3938

Dr. William Reeves
School of Public Health
Warren Hall
University of California
Berkeley, CA 94720
415/642-3938

Dr. Paul Reiter
CDC Laboratory
GPO Box 4532
San Juan, PR 00936
809/781-3636

Dr. Ronald Schwarz
TRAIN, Inc.
2816 Cheswolde
Baltimore, MD  21209
301/358-9561

Dr. Robert Shope
Yale University School of Medicine
Department of Epidemiology and Public Health
Box 3333
New Haven, CT  06510
203/785-4821

Dr. David Slade
Deputy Director
Physical and Technical Research Div. ER-74
Office of Health1 and Environmental Research
Department of Energy
Washington, DC 20545
202/353-4375

Dr. Chip Stem
Tufts School of Veterinary Medicine
200 Westboro Road
North Graf ton, MA 10536
617/839-5302

Dr. David Taplin
Department of Dermatology and Cutaneous Surgery
University  of Miami School of Medicine
Box 016960 R-117
Miami, FL 33101
305/547-6214
Ms. Kathleen Valimont
Department of Geography
University of Delaware
Newark, DE 19716

Dr. Byron Wood
TGS Technology Inc.
Mail Stop 242-4
NASA
Ames Research Center
Moffit Field, CA  94035
415/694-6184
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