1. 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 Colloquium on Climate and Health NCAR Boulder, Colorado 23 July, 2004

2. Outline 1.Introduction: Infectious Disease Epidemiology 2.Patterns of Environmental Influences 3.Climate as an Environmental Driver 4.Examples from our research 5.Discussion of examples from your research/interests

3. 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

4. Agent Host Environment Classical Epidemiological Triad

5. Agent (diverse exposures, including non- contagious ) Host (animal, plant, ultimately human) Environment* (biophysical, psycho-social, etc.) *CLIMATE is an Environmental Influence

6. Environment Agent Host

7. Environment host distribution, abundance, infection longevity & infectivity outside host e.g. cholera hantaviral disease hookworm schistosomiasis Agent nutrition treatment e.g. TB, HIV/AIDS, diarrheal diseases, acute respiratory infections housing hygiene Host tissue tropisms, pathogenicity, immune response, host specificity e.g. rabies, Lyme disease, malaria, cryptosporidiosi. Examples Involving Infectious Diseases

8. Agent Host Environment Altered hygiene Redesigned housing Better nutrition Improved irrigation But for ALL diseases, complex interactions occur...

9. Agent Host Environment Agent transport to new areas New antibiotics, pesticides Labor actions affecting toxin exposure

10. Agent Host Environment Exposure probability, host immunity, support networks, availability of supportive care

11. 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

12. Social and Economic Policies Physical Environment Institutions (including medical care) Living Conditions Social Relationships Individual Risk Factors Genetic/Constitutional Factors Pathophysiologic pathways Individual/Population Health Environmental Determinants of Human Disease Modified from Kaplan, 2002

13. Social and Economic Policies Climate? Institutions (including medical care) Living Conditions Social Relationships Individual Risk Factors Genetic/Constitutional Factors Pathophysiologic pathways Individual/Population Health Research Challenge – Analyze and understand interactions!

14. What is climate change? Climate variability? Time Environmental Variable Low High Average Trend (solid line) Actual Measure (dashed line) Unchanging Average, Unchanging Extremes

15. Time Environmental Variable Low High Average Trend (solid line) Actual Measure (dashed line) Unchanging Average, Increasing Extremes

16. Time Environmental Variable Low High Average Trend (solid line) Actual Measure (dashed line) Increasing Average, Unchanging Extremes

18. Time Environmental Variable Low High Average Trend (solid line) Actual Measure (dashed line) Increasing Average, Greater Extremes

19. Time Environmental Variable Low High Average Trend (solid line) Actual Measure (dashed line) Increasing Rate of Increasing Average, Unchanging Extremes

20. Time Environmental Variable Low High Average Trend (solid line) Actual Measure (dashed line) Increasing Rate of Increasing Average, Greater Extremes

21. 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.

22. 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 ).

23. Anthroponotic Infections Zoonotic Infections Direct ExposureIndirect Exposure Environmental Exposures Vehicle Humans Source Stream pollutants Air Particulates Legionella Humans STDs Measles Hepatitis B Vehicle Humans Vehicle Malaria Dengue Roundworm Vehicle Animals Humans Lyme Disease Hantaviral Disease Most arboviral diseases Animals Humans Anthrax Ebola (?) CJD Environment and Exposure Source Humans Solar UV EM Radiation Tetanus

24. Direct ExposureIndirect Exposure Environmental Exposures Source Humans Solar UV EM Radiation Tetanus Vehicle Humans Source Stream pollutants Air Particulates Legionella Environment and Exposure Where might Climate Impact?

25. Anthroponotic Infections Direct ExposureIndirect Exposure Humans STDs Measles Hepatitis B Vehicle Humans Vehicle Malaria Dengue Roundworm Environment and Exposure Where might Climate Impact?

26. Zoonotic Infections Direct ExposureIndirect Exposure Vehicle Animals Humans Lyme Disease Hantaviral Disease Most arboviral diseases Animals Humans Anthrax Ebola (?) CJD Environment and Exposure Where might Climate Impact?

27. Elements of Climate and Health Maximum Temperature Minimum Temperature Mean Temperature Rainfall Amount Rainfall Frequency Rainfall Rate Heat-related mortality Extreme Events Air Pollution Vector-borne Diseases Water-borne Diseases Agricultural Production

28. What diseases are climate sensitive? More sensitive –Which are more sensitive???? High Moderate Sensitivity Less sensitive –What about less sensitive??? Low Lowest Sensitivity

29. What diseases are climate sensitive? More sensitive –heat stress –effects of storms –air pollution effects –asthma –vector-borne diseases –water-borne diseases –food-borne diseases High Moderate Sensitivity Less sensitive –sexually transmitted diseases –violence –most cancers –atherosclerosis –tuberculosis –myocardial infarction Low Lowest Sensitivity

30. More Climate Sensitive Heat stress Asthma Vector-borne Disease Water-borne disease Myocardial Infarction Cancer (not skin) Sexually transmitted Disease Atherosclerosis Violence Effects of Storms Food-borne disease

31. 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?

33. Importance of temporally and spatially extensive data in analyzing and interpreting role of climate: Climate change occurring over long time period Climate variability change not easy to recognize without long-term observations Time-space changes in disease patterns require accurate and consistent surveillance (often non- existent, especially in developing countries) Inference of climate-disease links limited without carefully considering time-space patterns

34. a a b b c c d d Interpreting Spatial Patterns of Risk Area of risk Size of areas Location and pattern Inter-area distances Connectivity among locations

35. How can extensive time-space datasets help? T1T1 T2T2 T3T3 Pattern of disease … or knowledge, SES, exposure, etc...

36. How can extensive time-space datasets help?

37. How can extensive temporal datasets help? Time Abundance / Prevalence

38. How can extensive temporal datasets help? Establishment and Colonization Dispersal, Invasion, Extinction, Reinvasion Inter-annual Fluctuations Time Abundance / Prevalence

39. Environmental Index Abundance or Infection LowHigh Low High Habitat Fragmentation Change in Suitable Habitat Distance from Source Climate variable How can extensive spatial datasets help?

40. Some Sources of Data Meteorological Stations (climate, weather) Satellite – climate, vegetation, soil moisture, etc Census: population, age, sex, location, etc… Passive or active surveillance of human cases Surveillance of vector, reservoir abundance more...

41. Knowing is not enough; we must apply. Willing is not enough; we must do. (Goethe)