Download Disease - Institute for the Study of Society and Environment

Environment, Society, Climate and Health:
Analysis, Understanding and Prediction
Mark L. Wilson
Department of Epidemiology
and
Global Health Program
School of Public Health
The University of Michigan
Summer Colloquium on Climate and Health
NCAR
Boulder, Colorado
19 July, 2006
Outline
1. Introduction: Infectious Disease Epidemiology
2. Patterns of Environmental Influences
3. Climate as an Environmental Driver
4. Discussion of examples from your research/interests
5. Examples from my lab's research
(IF TIME PERMITS)
Classical Epidemiological Triad
Environment
Agent
Host
Environment*
(biophysical, psycho-social, etc.)
Agent
Host
(diverse exposures,
including noncontagious )
(animal, plant,
ultimately human)
*CLIMATE is an Environmental Influence
Environment
Agent
Host
Examples Involving Infectious Diseases
Environment
longevity & infectivity
outside host
host distribution,
abundance, infection
e.g. cholera
hantaviral disease
hookworm
schistosomiasis
nutrition
hygiene
treatment
housing
e.g. TB, HIV/AIDS,
diarrheal diseases,
acute respiratory
infections
Agent
Host
tissue tropisms,
pathogenicity,
immune response,
host specificity
e.g. rabies,
Lyme disease,
malaria,
cryptosporidiosi.
But for ALL diseases, complex interactions occur...
Environment
Altered hygiene
Improved irrigation
Redesigned housing
Better nutrition
Agent
Host
Environment
Agent transport to new areas
New antibiotics, pesticides
Labor actions affecting toxin exposure
Agent
Host
Environment
Agent
Host
Exposure probability, host immunity,
support networks, availability of supportive care
Examples of Environmental and Epidemiological Data
•
•
•
•
•
•
•
Climate patterns – variability… perhaps change…
Land Use / Land Cover patterns
Human case data (specific or syndromic)
Vector abundance and pathogen infection
Reservoir abundance / infection prevalence
Environmental use and exposures
Economic development, human demography,
migration … more
Each of these is historically changing in
time and space
Environmental Determinants of Human Disease
Social and Economic Policies
Institutions (including medical care)
Living Conditions
Social Relationships
Individual Risk Factors
Genetic/Constitutional
Factors
Pathophysiologic
pathways
Individual/Population
Health
Modified from Kaplan, 2002
Research Challenge – Analyze and understand
interactions!
Social and Economic Policies
Institutions (including medical care)
Living Conditions
Social Relationships
Individual Risk Factors
Genetic/Constitutional
Factors
Pathophysiologic
pathways
Individual/Population
Health
Climate Variability vs. Climate Change
• Climate Change:
- persistent change or trend in mean atmospheric
conditions
- current changes unprecedented in human history
• Climate Variability:
- day-to-day (weather) or relatively short term (seasonal)
changes in atmospheric conditions
- effects on disease patterns most easily analyzed, and
used in forecasts
Environmental Variable
What is climate change? Climate variability?
Unchanging Average, Unchanging Extremes
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Environmental Variable
Unchanging Average, Increasing Extremes
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Environmental Variable
Increasing Average, Unchanging Extremes
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Environmental Variable
High
Different Rates of Increasing Averages
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Environmental Variable
Increasing Average, Greater Extremes
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Environmental Variable
Increasing Rate of Increasing Average,
Unchanging Extremes
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Environmental Variable
Increasing Rate of Increasing Average,
Greater Extremes
Average Trend
(solid line)
Actual Measure
(dashed line)
Low
Time
Each of these climate change patterns
may have different impacts on particular
disease risks.
Effects will depend on the ecology of
transmission and the etiology and
expression of disease.
Each exposure type should be considered in context of:
 PERSON (age, behavior, gender, SES, etc.)
 TIME (year, season, adjacent periods, etc.)
 PLACE (geographic location, habitat, proximity, etc.)
Most Epidemiological studies only superficially consider
this for environmental (climatic) exposures:
+ PERSON most often involves standard descriptors that do not
include "social" characteristics or other environmental
exposures (e.g. climatic).
 TIME is rarely dynamic, considers only recent past, and
climate pattern over long periods not always available.
 PLACE often ignored or not carefully evaluated (e.g. spatial
autocorrelation, climate patterns in regions may be important ).
Environment and Exposure
Direct Exposure
Indirect Exposure
Environmental Exposures
Source
Source
Vehicle
Humans
Humans
Solar UV
EM Radiation
Tetanus
Stream pollutants
Air Particulates
Legionella
Anthroponotic Infections
Humans
Humans
Vehicle
Humans
Vehicle
Humans
STDs
Measles
Hepatitis B
Malaria
Dengue
Roundworm
Zoonotic Infections
Animals
Animals
Vehicle
Animals
Humans
Vehicle
Animals
Anthrax
Ebola (?)
CJD
Humans
Lyme Disease
Hantaviral Disease
Most arboviral diseases
Environment and Exposure
Where might Climate Impact?
Direct Exposure
Indirect Exposure
Environmental Exposures
Source
Source
Vehicle
Humans
Solar UV
EM Radiation
Tetanus
Humans
Stream pollutants
Air Particulates
Legionella
Environment and Exposure
Where might Climate Impact?
Direct Exposure
Indirect Exposure
Anthroponotic Infections
Humans
Humans
Vehicle
Humans
STDs
Measles
Hepatitis B
Vehicle
Humans
Malaria
Dengue
Roundworm
Environment and Exposure
Where might Climate Impact?
Direct Exposure
Indirect Exposure
Zoonotic Infections
Animals
Animals
Vehicle
Animals
Humans
Vehicle
Animals
Anthrax
Ebola (?)
CJD
Humans
Lyme Disease
Hantaviral Disease
Most arboviral diseases
What diseases are the most
climate sensitive?
Sensitivity
High
Low
–
–
–
–
–
–
–
–
heat stress
effects of storms
air pollution effects
asthma
vector-borne diseases
water-borne diseases
food-borne diseases
sexually-transmitted
diseases
Respiratory Diseases
• Climate change impacts on air pollutants uncertain
– ozone increase most likely
• Longer growing seasons, long-term climate changes
may alter pollen burden
• May alter incidence or exacerbate
– may affect development of asthma
• Adaptive Measures
– early warning systems
– public education
Water-borne Diseases
• Cholera
– growing understanding of
climate linkage
– controlled by sanitary
infrastructure in developed
countries
• Cryptosporidiosis
– linkage to extreme precipitation
events
– may lead to higher pre-treatment
levels
Vector-Borne Diseases
• Many parts of complex systems are climate sensitive
– vector survival, reproduction, development, biting rates
– pathogen reproduction, development
• Disease activity depends on multiple factors and is
region specific
– lifestyle, vector control measures, medical care
• Vigilance needed for imported diseases
– Greatest threat remains foreign travel, border areas
Sexually transmitted
Disease
Heat stress
Effects of Storms
Water-borne disease
Food-borne disease
Asthma
Atherosclerosis
Vector-borne Disease
Cancer (not skin)
Myocardial Infarction
Violence
More Climate Sensitive
Committee Members
DONALD BURKE (Chair)
Johns Hopkins University
ANN CARMICHAEL
Indiana University
DANA FOCKS
U.S. Department of Agriculture
DARELL GRIMES
University of Southern Mississippi
JOHN HARTE
University of California, Berkeley
SUBHASH LELE
University of Alberta
PIM MARTENS
Maastricht University, Netherlands
JOHNATHAN MAYER
University of Washington
LINDA MEARNS
National Center for Atmospheric Res.
ROGER PULWARTY
University of Colorado / NOAA
LESLIE REAL
Emory University
CHET ROPELEWSKI
Intl. Research Inst. for Climate Prediction
JOAN ROSE
University of South Florida
ROBERT SHOPE
University of Texas Medical Branch
JOANNE SIMPSON
NASA Goddard Space Flight Center
MARK WILSON
University of Michigan
LAURIE GELLER
SUSAN ROBERTS
JONATHAN DAVIS
NRC Staff
Board on Atm. Sciences and Climate
Ocean Studies Board
Institute of Medicine
KEY FINDINGS 1:
Climate-Disease Linkages
Weather fluctuations and seasonal-tointerannual climate variability influence
many infectious diseases
• Characteristic geographic distributions and seasonal variations of many
infectious diseases (IDs) are prima facie evidence of linkages with weather
and climate.
• Studies have shown that temperature, precipitation, humidity affect life
cycles of many pathogens, vectors (directly and indirectly); this, in turn,
may influence timing, intensity of outbreaks.
• However, ID incidence also affected by other factors (e.g. sanitation, public
health services, population density, land use changes, travel patterns.
• The importance of climate relative to these and other variables must be
evaluated in the context of each situation.
KEY FINDINGS 2:
Climate-Disease Linkages
Observational and modeling studies must
be interpreted cautiously
• Numerous studies showing associations between climatic variations and
ID incidence can not fully account for complex web of causation underling
disease dynamics; most are not reliable indicators of future changes.
• Various models simulating effects of climatic changes on incidence of
diseases (e.g. malaria, dengue, cholera) are useful heuristic tools for
testing hypotheses and undertaking sensitivity analyses; they are not
intended to serve as predictive tools; often exclude physical/biological
feedbacks and human adaptation.
• Caution needed in using these models to create scenarios of future disease
incidence, providing early warnings, and developing policy decisions.
KEY FINDINGS 3:
Climate-Disease Linkages
The potential disease impacts of global
climate change remain highly uncertain
• Changes in regional climate patterns caused by long-term global
warming could affect potential geographic range of many diseases.
• However, if climate of some regions becomes more suitable for
transmission of particular disease agents, human behavioral adaptations
and public health interventions could serve to mitigate many adverse
impacts.
• Basic public health protections (adequate housing, sanitation),and new
interventions (vaccines, drugs), may limit future distribution & impact
of some infectious diseases, regardless of climate-associated changes.
• These protections, however, depend on maintaining strong public health
programs, and assuring vaccine and drug access in poorer countries.
KEY FINDINGS 4:
Climate-Disease Linkages
Climate change may affect the evolution
and emergence of infectious diseases
• Potential impacts of climate change on the evolution and emergence of
infectious disease agents are an additional highly uncertain risk.
• Ecosystem instabilities from climate change and concurrent stresses (e.g.
land use changes, species dislocation, increasing global travel) could
influence genetics of pathogenic microbes through mutation and
horizontal gene transfer.
• New interactions among hosts and disease agents could occur, fostering
emergence of new infectious disease threats.
KEY FINDINGS 5:
Climate-Disease Linkages
Potential pitfalls exist in extrapolating
climate and disease relationships among
spatial and temporal scales
• Relationships between climate and infectious disease are often highly
dependent upon local-scale parameters.
• Difficult or impossible to extrapolate these relationships meaningfully to
broader spatial scales.
• Temporal climate variability (seasonal, interannual) may not represent a
useful analog for long-term impacts of climate change.
• Ecological responses on such time scales (e.g. El Niño event) may be
significantly different from the ecological responses and social
adaptations expected under long-term climate change.
• Long-term climate change may influence regional climate variability
patterns, hence limiting the predictive power of current observations.
climate
mean temperature,
precipitation, humidity,
extreme weather events
ecology
vegetation, soil moisture,
species competition
transmission biology
microbe replication/movement,
vector reproduction/movement,
microbe/vector evolution
disease outcome
Risk, rate of transmission
Spread to new areas
social factors
sanitation, vector control,
travel/migration,
behavior/economy,
population/demographics
KEY FINDINGS 6:
Climate-Disease Linkages
Recent technological advances should
improve modeling of infectious disease
epidemiology
• New techniques in several disparate scientific disciplines may encourage
different approaches to infectious disease models.
• Advances include sequencing of microbial genes, satellite-based remote
sensing of ecological conditions, Geographic Information System (GIS),
new analytical techniques, increased computational power.
• Such technologies should improve analyses of microbe evolution and
distribution, and of relationships to different ecological niches.
• This may dramatically improve abilities to quantify disease impacts
from climatic and ecological changes.
KEY FINDINGS 7:
Disease "Early Warning" Potential
Future epidemic control strategies should
complement "surveillance and response"
with "prediction and prevention"
• Current epidemic control strategies depend largely on surveillance for
new outbreaks followed by a rapid response to control the epidemic.
• Climate forecasts and environmental observations could help identify
areas at risk of epidemics, thus aiding efforts to limit or prevent.
• Operational disease early warning systems not yet feasible due to limited
understanding of climate/disease relationships and climate forecasting.
• Establishing goal of developing early warning capacity will foster the
needed analytical, observational, and computational developments.
KEY FINDINGS 8:
Disease "Early Warning" Potential
Effectiveness of early warning systems
will depend upon context of their use
• Where risk mitigation is simple and low-cost, early warning may be
feasible given only general understanding of climate/disease associations.
• If mitigation actions are significant, precise and accurate prediction may
be necessary, requiring more thorough mechanistic understanding of
underlying climate/disease relationships.
• Value of climate forecasts depends on disease agent and locale (e.g.
reliable ENSO-related disease warnings restricted to regions with clear,
consistent ENSO-related climate anomalies).
• Investment in sophisticated warning systems not effective use of
resources where capacity for meaningful response is lacking, or if
population not highly vulnerable to hazards being forecasted.
KEY FINDINGS 9:
Disease "Early Warning" Potential
Disease early warning systems cannot
be based solely on climate forecasts
• Need for other appropriate indicators (e.g. meteorological, ecological,
epidemiological surveillance) that complement climate forecasts.
• Such combined information may permit a “watch” to be issued for
regions, and a “warning” if surveillance data confirms projections.
• Vulnerability and risk analyses, feasible response plans, and strategies
for effective public communication needed as part of system.
• Climate-based early warning for other applications (e.g. agricultural
planning, famine prevention) may provide many useful lessons.
KEY FINDINGS 10:
Disease "Early Warning" Potential
Development of early warning systems
should involve active participation of
the system’s end users
• Input from stakeholders (e.g. public health officials, local policymakers)
needed to help ensure that forecast information is provided in a useful
manner and that effective response measures are developed.
• Probabilistic nature of climate forecasts must be clearly explained to
communities using these forecasts, allowing development of response
plans with realistic expectations of possible outcomes range.
RESEARCH RECOMMENDATIONS
• Research on climate and infectious disease linkages must be
strengthened
• Further development of transmission models needed to assess
risks posed by climatic and ecological changes
• Epidemiological surveillance programs should be
strengthened
• Observational, experimental, and modeling activities must be
coordinated
• Research on climate and infectious disease linkages inherently
requires interdisciplinary collaboration
Unpredictability of climate-disease
linkages suggests reducing human
vulnerability is most prudent public
health strategy
• Understanding of climate linkages to ecosystems and health not yet solid,
making most early warning systems not yet feasible.
• Some unpredictability will always be present.
• Thus, strengthening of public health infrastructure (e.g. vector control,
water treatment systems, vaccination programs) should be high priority.
• Reducing overall vulnerability of populations at risk is the most prudent
strategy for improving health.
Knowing is not enough; we must apply.
Willing is not enough; we must do.
(Goethe)
Discussion…
From YOUR EXPERIENCES or INTERESTS:
• What diseases might have a climate link and what
climate variables might impact on which diseases?
• WHY? What are the biological or social pathways?
• How would these be investigated/researched?
• What additional information would you seek?
• How would you integrate this into OTHER
determinants of risk?
• Could you forecast risk based on these analyses alone?
• What other factors should be considered and why?