Climate and Health

1. Climate and Health Fred Roberts Rutgers University

2. 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 Acknowledgements

3. Climate and Health Concerns about global warming. Resulting impact on health Of people Of animals Of plants Of ecosystems

4. 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

5. Climate and Health Some early warning signs: Malaria in the African Highlands Dengue epidemics Floods, hurricanes

6. Climate and Health Prediction of global warming Blame on increased carbon emissions Predictions of dire health consequences

7. 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

8. 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?

9. 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

10. 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

11. 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

12. 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

13. 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)

14. 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?

15. 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.

16. 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.

17. 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.

18. 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

19. 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

20. 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

21. 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.

22. 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?

23. 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.

24. 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

25. St. Louis Encephalitis Cycling of a virus between mosquitoes and birds is necessary to affect humans.

26. 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.

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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)

33. 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?

34. 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.

35. 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

36. 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

37. 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

38. 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

39. 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”

40. 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 modelers and policy makers

41. Behavioral Responses • to Health/Climate Events • We can learn some things from the study of responses to various disasters: • Earthquakes • Hurricanes • Fires • Etc. New Orleans hurricane 2005 Turkey earthquake 1999

42. 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

43. 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

44. 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

45. 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?

46. 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

47. Some Final Observations Modelers and policymakers can work together to understand, mitigate, and prepare for the effects of climate change on health.