Source document: https://docs-lawep.s3.us-east-2.amazonaws.com/1694840102545.pdf (Mauritius)
Climate Change and Health Estimating the Burden of Impacts Mark L. Wilson, Sc.D.
Professor of Epidemiology and of Ecology and Evolutionary Biology The University of Michigan Ann Arbor, Michigan, USA Training on Climate Change Related Health Impacts Republic of Mauritius 14-18 May, 2012 Overview • Outline steps involved in estimating the burden of disease from climate change • Present examples for several of the health impacts assessment of burden of disease from climate change • Present overall results from this assessment, and describe usefulness and limitations for informing policy WHO 2009 We Know that There are Many Important Links to Health • Some expected impacts will be beneficial but most will be adverse • Expectations are mainly for changes in frequency or severity of familiar health risks CLIMATE CHANGE Health effects •Temperature-related illness and death •Extreme weather- related health effects •Air pollution-related health effects •Water and food-borne diseases •Vector-borne and rodent-borne diseases •Effects of food and water shortages •Effects of population displacement Based on Patz et al., 2000 WHO 2009 But Policy-Makers also Want Quantification • We want to know not only if health will be affected, but also – How important are these effects?
– Which diseases could have the biggest impacts?

– Which populations are most at risk, and how?
WHO 2009 Burden of Disease Assessment • Burden of disease methods: – Use standardized approaches to provide quantitative mortality and morbidity information – Use death and summary population health measures (e.g., Disability Adjusted Life Years — DALYs) – Can be applied either to diseases (e.g., total burden from all sequelae of diarrhoea), or risk factors (e.g., the overall burden from all health effects of smoking, lung cancer, cardiovascular disease) in a defined population – Can also inform on the distribution of burdens, by disease, population subgroup, etc.
WHO 2009 Burden of Disease Estimates due to Climate Change • Completed at the global/regional level • And for the Republic of Maurice... WHO 2009 Steps in Estimating Burden of Disease from Climate Change Step 1: Greenhouse gas emissions scenarios Step 2: Global climate modeling to generate maps of predicted future climate Step 3: Health impact model to estimate change in relative risk of specific diseases Step 4: Conversion to a single health measure Level 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 Age group (years) 0-4 1.0 1.2 1.7 1.0 5-14 1.0 1.2 1.7 1.0 15-29 1.0 1.2 1.7 1.0 30-44 1.0 1.2 1.7 1.0 45-59 1.0 1.2 1.7 1.0 60- 70+ 1.0 1.2 1.7 1.0 1.2 1.7 1.0 1.2 1.7 1.0 1.2 1.7 1.0 1.2 1.7 WHO 2009 Step 1: Defining Climate Scenarios • Exposure scenarios used in the global assessment: – Discrete climate scenarios derived from alternative 1961-1990 levels of GHGs and associated climate (baseline) future trajectories of GHG emissions 1) 2) Stabilization at 550 ppm CO2-equivalent in 2170 3) Stabilization at 750 ppm CO2-equivalent in 2210 4) Unmitigated current GHG emissions trends WHO 2009 Projected Future Climate Change Business as Usual emissions Temp increase (o C) 4 3 2 1 Baseline climate 1961-1990 1900 2000 2100 2200 Year WHO 2009 Projected Climate Change with Emissions Stabilization 2210 Business as Usual emissions Stabilisation, 750 ppm Temp increase (o C) 4 3 2 1 1900 2000 2100 2200 Year WHO 2009 Projected Climate Change with Emissions Stabilization Business as Usual emissions Stabilisation, 750 ppm Stabilisation, 550 ppm Temp increase (o C) 4 3 2 1 1900 2000 2100 2200 Year 2170 WHO 2009 Step 2: Describing Climate Exposures WHO 2009 Step 3: Selecting Likely Health Outcomes — Proposed Criteria • Sensitive to climate – Disease incidence should
 correlate with seasonal or intra-annual climate variation • Important health impact – Based on estimates of current mortality and/or morbidity • Already modeled at an appropriate scale – For example, existing models relating distribution of a disease to climate variables WHO 2009 Examples of Important Climate-Sensitive Diseases • Climate affects food production, water scarcity, and infectious disease transmission, which influence some of the biggest killers • Already, globally each year: – Undernutrition kills 3.5 million – Diarrhea kills 2.2 million – Malaria kills almost 1 million WHO 2009 Availability of Studies that Estimate Effects of Climate Change on Health Health impact Available studies of climate change effects Thermal extremes Temperature-mortality relationships examined in multiple cities throughout world Extreme weather (floods, high winds, droughts) No complete analysis of linkage from climate change to changes in extreme events and health impact projections Diarrhea Two local time series studies, no global model Malaria Dengue Malnutrition Three distinct global or continental models Two global models One global model of climate change to regional food availability WHO 2009 Step 3: Modeling Climate-Health Relationships Health Impact 1: Diarrhea WHO 2009 Quantifying Climate-Diarrhea Relationships s n o i s s i m d A a e h r r a i D e r u t a r e p m e T Daily measurements Jan 1993 – Dec 1998 Incidence of diarrheal disease is strongly related to climate variables.
In Lima, Peru, diarrhoea increased 8% for every 1°C temperature increase.
Checkley et al., 2000 WHO 2009 Converting to an Approximate Global Estimate – 5% increase in diarrhea per 1°C temperature increase in • Climate sensitivity developing countries • Change in relative risk – Projected temperature changes overlaid on population distribution map to give per capita increase in diarrhea risk • Disease burden attributable to climate change – Relative risk under each scenario/time point multiplied by WHO estimates of current/future “baseline” diarrhoea burden in each region • RESULT: Health impacts attributed to climate effects on diarrhea in the year 2000: – 47,000 deaths globally – 23,000 in WHO Southeast Asia region WHO 2009 Step 3: Modeling Climate-Health Relationships Health Impact 2: Dengue WHO 2009 Converting to an Approximate Global Estimate • Climate sensitivity – Relationship between climate variables and dengue distribution based on Hales et al.
(2002) global model • Change in relative risk – Projected future climate scenarios applied to global model to map changes in disease distribution.

Overlaid on population distribution map to give changes in population at risk (PAR).

• Disease burden attributable to climate change – Percent changes in PAR applied to WHO estimates of “baseline” burden in each region (e.g., 50% increase in PAR assumed = 50% increase in mortality and morbidity).
• RESULT: Health impacts on dengue attributed to climate in the year 2000: – 1,000 deaths globally WHO 2009 Step 4: Aggregating Across Different Diseases Subregion Malnutrition Diarrhoea Malaria Floods CVD* All causes AFR-D AFR-E AMR-A AMR-B AMR-D EMR-B EMR-D EUR-A EUR-B EUR-C SEAR-B SEAR-D WPR-A WPR-B World CVD* = Net changes in Cardiovascular disease deaths associated with both hot and cold temperatures WHO 2009 Conclusions: Poorest Populations are Most Vulnerable WHO 2009 Poorest are Least Responsible for Causing Climate Change Cumulative emissions of greenhouse gases, to 2002 WHO estimates of per capita mortality from climate change, 2000 Map projections from Patz et al., 2007 WHO 2009 Limitation 1: Crude Representation of Non-Climate Effects Health impact Direct physiological effects of heat and cold Diarrhea Malnutrition Malaria “Adaptive” effects over time Temperature associated with lowest mortality changes as temperature increases Diarrhoea baseline drops, becomes insensitive to temperature if GDP per capita > US$6,000/year Future increases in crop yields from technological advances, trade liberalization, increased GDP Malaria baseline drops, developed regions remain protected from malaria invasion Disasters: Deaths in coastal floods Baseline and relative risk of deaths in floods drops with GDP Disasters: Inland floods and landslides Baseline and relative risk of deaths in floods drops with GDP WHO 2009 Limitation 2: Many Impacts Cannot be Reasonably Modeled • Examples – Leishmaniasis, cholera, sleeping sickness, filariasis… – Flooding impacts on diarrhoea, mental health, non-communicable diseases (NCDs)… – Increased frequency of severe tropical storms – Floods from melting glaciers, water shortages from melting glaciers – Salination of water sources from sea-level rise – Aeroallergens WHO 2009 Limitation 2: Many Impacts Cannot be Reasonably Modeled • Examples – Forest fires – Dust storms – Effects on crop pests – Effects via species extinction and biodiversity loss – Social effects of population displacements WHO 2009 Interpreting and Using the Results • Estimates of burden of disease from climate change are just one dimension of a health assessment.
They should be presented alongside: • Estimates of the underlying disease burden, irrespective of climate change – How bad is the problem already?

• Information on the distribution of risks within a population – Who is most vulnerable?

WHO 2009 Interpreting and Using the Results (cont.)

• Qualitative assessment of potential health impacts that are difficult to quantify, or the possibility of extreme events – What else could happen?

• Assessments of interventions – What can we do about it?
WHO 2009 Conclusions • Global burden of disease studies show: – Much of the global burden of disease, especially in the poorest countries, is climate-sensitive.

– Failure to stabilize climate may already cause the loss of over 5.5 million years of healthy life (or over 150,000 lives) per year.

This is expected to rise in future decades.

– There is a need for strengthened control of climate-sensitive diseases (in the short-term), and reducing climate change (in the long-term).
WHO 2009 Conclusions (cont.)

• National burden of disease studies would: – Give more local, accurate, and context- specific measurements, with a stronger link to control interventions – Provide a stronger basis for accessing global “adaptation funds” for health protection WHO 2009 Discussion Questions?

Thoughts?

Concerns?

Suggestions?

Acknowledgements • Based in part on lectures developed by the author for courses taught at the University of Michigan, Ann Arbor, MI, USA.
• Some material was modified from the WHO “Training course for public health professionals on protecting our health from climate change (2009).” • Supported by the Mauritius Ministry of Environment & Sustainable Development (No: MoESD/AAP/02/11)