Transcript Climate and Disease - dimacs

Climate and Health
Fred Roberts
Rutgers University
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Acknowledgements
•DIMACS Workshop on Climate and Disease
–April 7-8, 2008
–Organizers:
Ben Cash
Andy Dobson
Jim Kinter
Mercedes Pascual
•DIMACS Initiative on Climate and Health
–2008-2010
–Organizers:
Nina Fefferman
Endre Boros
Rick Lathrop
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Climate and Health
•Concerns about global warming.
•Resulting impact on health
–Of people
–Of animals
–Of plants
–Of ecosystems
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Climate and Health
•Some early warning signs:
–1995 extreme heat event in Chicago
514 heat-related deaths
3300 excess emergency admissions
–2003 heat wave in Europe
35,000 deaths
–Food spoilage on Antarctica
expeditions
Not cold enough to store food
in the ice
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Climate and Health
•Some early warning signs:
–Malaria in the African Highlands
–Dengue epidemics
–Floods, hurricanes
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Climate and Health
•Prediction of global warming
•Blame on increased carbon emissions
•Predictions of dire health consequences
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Climate and Health
•What is the state of climate science?
–Little understanding of reliability of climate models
–Some agreement on “sign” of change, little on
“value” of change
–Many sources of uncertainty:
Natural variation
Future emissions scenarios
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Climate and Health
•Still, we have some evidence that change in
climate affects health.
•What are major research challenges?
•How can policy makers make best use of results
of models?
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Climate and Health
Evidence that change in climate affects health:
•With very high confidence (Simon Mason, IRI):
–Climate change affects transmission season for
diseases such as malaria
•With high confidence (Simon Mason):
–Global warming leads to increased
malnutrition
–Global warming leads to increased
number of people suffering from
extreme weather events
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Climate and Health
Evidence that change in climate affects health:
•With high confidence (Simon Mason):
–Global warming leads to increase in cardio-respiratory
disease related to air quality
–Climate change leads to change in infectious disease
vectors
–Global warming leads to decrease
in cold-related deaths
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Malaria
•For each disease, effect of climate raises its own complex
modeling challenges
•Malaria a case in point (Mercedes Pascual).
•Climate change impacts:
–Transmission rate changes with climate conditions
–Affects dynamics of both host and mosquito
–Affects time lag for parasite development as a function of
temperature
–Affects time lag for development of
symptoms
–Affects length of time patient remains immune
–Rainfall affects the carrying capacity for larvae
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Malaria
•But, there are complexities (David Rogers)
–Models that depend on average change in temperature or
rainfall miss out on spatial variation
–There are changes in the time of the malaria cycle during
which rainfall changes result in changes in impact
–With global warming, there are areas where malaria
would appear and others where malaria would disappear
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Malaria
•Other complexities:
–Confounding factors: climate change not the only variable
Changing land use
Migration of people (perhaps related
to changing climate)
Emergence of other diseases (HIV)
Drug resistance (TB)
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Malaria
•Other complexities:
–WHO’s early warning system for
malaria
Monitors weather and climate
Weather is not the same as climate
Temporal scale issues:
But how far in the future can we reliably predict?
Short range: one year?
Long range: one decade???
Spatial scale issues
What is an appropriate resolution for
predictions/models?
By the kilometer? The region? The continent?14
Malaria
•The challenge of climate change: Malaria springs up
in areas it wasn’t in before.
•Highlands of Kenya
•Potential for Malaria in the US – Texas, Florida,
Washington, …
•A key role for modelers:
Aid in early warning:
surveillance.
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Comment on Spraying
•One goal of modeling effect of climate change is to
get early warning to policy makers.
•This will allow them to take early preventive action.
•But there are complexities in analyzing impacts of
preventive actions.
•Warning of expected increase in mosquito population
suggests spraying of pesticides.
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Comment on Spraying
•Spraying may affect health.
•Health effects of spraying well studied.
•E.g., in hot, dry regions, pesticides
can trigger severe asthma.
•Issue is exacerbated when increased spraying follows
extreme climate events such as floods.
•Research needed on balancing benefit of spraying vs.
health impacts of spraying, under scenario of
fluctuating climatic conditions.
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Cholera
•Complex interaction between climate and disease
•Regional climate variations have significant effect on cholera
forecast
•Prevalence of the bacteria affected by conditions of sea water.
•Real correlation between January sea surface temperature and
incidence of cholera in Bangladesh (Rita Colwell, Ben Cash)
•But: how consistent is the “signal”?
•Other relevant factors (related to climate):
–Water level
–Salinity
–Nutrients in the water
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Meningoccocal (Epidemic) Meningitis
•Occurs when bacteria penetrate the mucus membrane
and enter the bloodstream
•Transmission of disease spikes in dry season,
decreases when humidity hits.
•Modeling based on land cover and seasonal humidity
profile (Madeleine Thomsen)
•But, also relevant are seasonal dust profile, soil type,
population density
•Disease incidence clearly
climate related
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Meningoccocal (Epidemic) Meningitis
•In Mali, clear relationship between onset of dry winds
and seasonal meningitis epidemic (Madeleine
Thomsen)
•But, this is a statistical relationship.
•We don’t understand the mechanism.
•Is loss of integrity of mucus membrane due to
physical damage from humidity? Dust?
Dust storm
Bamako, Mali
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Dengue Fever
•Mosquito-borne disease.
•Appearing in places it hasn’t appeared before.
•Large outbreak in Brazil this year.
•Seems climate-related.
•Excessive rainfall leads to excessive cases (Timothy
Desole)
•However, counterintuitive:
•Drought also leads to excessive cases.
•Why? Challenge for modellers.
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Dengue Fever
•One explanation of drought case:
•In drought, people store water in containers.
•This provides breeding grounds for mosquitoes.
•Complex interaction among weather, mosquito
populations, people’s responses to weather conditions,
etc.
•Another conundrum: 50,000 cases along the Rio
Grande between Mexico and Texas.
•Almost all in Mexico.
•Why?
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Lyme Disease in Canada
•Increase in Lyme Disease in Canada.
•Is it due to climate change or normal range expansion
for the ticks that carry the disease?
•Migratory birds carry the disease into Canada.
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Lyme Disease in Canada
•Complex interactions among tick life cycles, bird
migrations, climate, etc. (Michael Ogden)
•Temperature changes affect patterns of bird
migrations.
•Do temperature changes also affect speed of bird
migration?
•Temperature changes affect life cycle of ticks, birds
•Different climate change
scenarios yield different tick
life cycles
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St. Louis Encephalitis
•Cycling of a virus between mosquitoes and birds is
necessary to affect humans.
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St. Louis Encephalitis
•Rainfall has heavy influence on mosquito population.
•SLE outbreak in Florida in 1990. Chickens bitten.
•Complex interactions among mosquito life cycle,
rainfall cycles (Jeffrey Haman).
•Precipitation not only determinant of soil moisture.
•Model movement of water between layers of ground,
model runoff, connect to nesting
preferences for birds and reproductive
cycle of mosquitoes.
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Some Animal Diseases
•Much data is anecdotal.
•Anthrax: related to rainfall.
•African horse sickness: related to combination of
heavy rainfall and drought.
•West Nile Virus: Mild winter followed by severe
Spring
•Rabies: Affected by rainfall – related to crowding
around the waterhole in dry season
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Some Animal Diseases
•Source: Giulio DeLeo
•With humans: effect of climate can be masked by
socioeconomic processes, sanitation, drug resistance.
•Humans: relatively homogenous compared to diversity of
animal species
•With animals: effect of climate and environment more
pervasive
•With animals: role of fluctuations in abundance and age and
spatial distribution
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Some Animal Diseases
•Issues for research:
–Environmental stochasticity
–Complications from multispecies systems
–Role of thresholds in relation to response to
climate
–Possibility of evolution or adaptation to climate
change
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Blue Tongue
•Source: David Rogers
•Until the 1960s, restricted to Africa.
•Then, an outbreak in Europe.
•In the 1990s, permanently established In Southern Europe.
•The African vector (C. Imocale) moved there.
•Complex factors involved:
–Climate
–Weather
–Vector/host ratio
–Transmission coefficients
–Biting rate
–Incubation rate
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Diseases of Plants
•Clear relation between drought/rainfall and health of
plants.
•Effect of fungicides, pesticides, etc. complicates
matters for the modeler.
•Possibility of genetic modification
of crops to help them deal with
global warming – presents complex
modeling challenges
Potato disease
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Biodiversity
•Extinction and danger for species due to global
warming.
•Example: challenges for the polar bear.
•Some predict a 15 to 37% reduction in biodiversity
due to global warming. (Source: Kevin Lafferty)
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Biodiversity
•But, other factors may be more important than
climate – e.g., pollution, changes in land use.
•Some factors such as habitat loss are intertwined with
climate change.
•The effects of climate change on biodiversity need to
be modeled on different temporal and spatial scales.
•By the kilometer or by the continent?
•By the year or by the decade?
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Extreme Events due to Global Warming
•We anticipate an increase in number and severity of
extreme events due to global warming.
•More heat waves.
•More floods, hurricanes.
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Extreme Heat Events
•Result in increased incidence of heat stroke,
dehydration, cardiac stress, respiratory distress
•Hyperthermia in elderly patients can lead to cardiac
arrest.
•Effects not independent: Individuals under stress due
to climate may be more susceptible to infectious
diseases
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Extreme Heat Events
•One response to such events: evacuation of most
vulnerable individuals to climate controlled
environments.
•Modeling challenges:
–Where to locate the evacuation centers?
–Whom to send where?
–Goals include minimizing travel time, keeping facilities to
their maximum capacity, etc.
–Relevance of mathematical tools of operations research –
location theory
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Extreme Heat Events
•A side effect of such events: Extremes in energy use lead to
need for rolling blackouts.
•Modeling challenges:
–Understanding health impacts of
blackouts and bringing them into models
Lack of air conditioning
Elevators no work: vulnerable people
over-exert
Food spoilage
–Minimizing impact on most
vulnerable populations
–Some optimization problems here
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SocioEconomic & Behavioral Factors
•Climate change might have significant socioeconomic and
behavioral impacts
–Changing locations of urban centers due to flooding,
changing weather
–Population migrations
–Changing land use regulations
–Changing agricultural practice
–New industries growing up to deal with mitigation of
climate effects
–Need to divert resources to mitigating effect of climate
change
–Restrictions on certain kind of industrial processes
–Behavioral responses to climate and health events
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SocioEconomic & Behavioral Factors
•Climate change might have significant
socioeconomic impacts
–Hard to predict what these might be
–Different short-term (responses to extreme events)
and long-term
–However, important to build these into our models
–Models cannot assume the “status quo”
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Behavioral Responses
to Health/Climate Events
•Models in epidemiology typically omit behavioral
responses.
–Hard to quantify.
–Hard to measure.
•Quite different issues for short-term responses to
extreme events and long-term responses to gradual
change.
•Leads to challenges for behavioral scientists.
•Leads to challenges for modelers
•Leads to challengers to the interface between 40
modelers and policy makers
Behavioral Responses
to Health/Climate Events
•We can learn some things from the study of
responses to various disasters:
–Earthquakes
–Hurricanes
–Fires
–Etc.
Turkey earthquake 1999
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New Orleans hurricane 2005
Behavioral Responses
to Health/Climate Events
Some Behavioral Responses that Need to be
Addressed:
•Compliance:
–Quarantine
–Resistance
–Willingness to seek/receive treatment
–Credibility of government
–Trust of decision makers
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Behavioral Responses
to Health/Climate Events
Some Behavioral Responses that Need to be
Addressed:
•Movement
•Rumor
•Perception of risk
•Person to person interactions
•Motivation
•Social stigmata (discrimination against social
groups)
•Panic
•Peer pressure
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Behavioral Responses
to Health/Climate Events
Some Challenges:
•How do we measure some of these factors?
•How do we bring them into mathematical models?
•How do we test out our ideas and make them useful
in practical decision making.
•Hard to decide these things without a dialogue
between modelers and policy makers
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Some Final Observations
•Hard to predict the future.
•Major challenges of scale:
–Spatial and temporal
–Need to understand micro-climates
–Average numbers may not be useful
–What defines “long-range”?
–How accurate are long-range predictions?
–What is reasonable spatial “resolution” for our
models?
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Some Final Observations
•Sometimes the most serious consequences of
change are the indirect effects.
•Models relating climate change to health need to
take into account secondary and tertiary effects.
•Models need to take into account socioeconomic
and behavioral responses to climate change
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Some Final Observations
•Modelers and policymakers can work together to
understand, mitigate, and prepare for the effects
of climate change on health.
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