![International environment
agenda
1972 Club of Rome Limits to Growth .
1972 UN World Conference on the Human Environment.
1987. World Commission on Environment and Development “Our
Common Future”
WSSD. [World Summit on Sustainable Development] Rio 1992
– Framework Conventions on Climate Change, Biodiversity and others.
– Agenda 21
1997 Kyoto Protocol
WSSD - Johannesburg 2002 [Rio+10]
– UN Kofi Annan proposed five key areas for particular focus: WEHAB
[Water, Energy, Health, Agriculture, Biodiversity]
2005 Kyoto Protocol comes into force. US opts out.
Millennium Development Goals](https://image.slidesharecdn.com/rssoct05kovats-221203024735-640d0cc6/85/RSS_Oct05_Kovats-ppt-2-320.jpg)
![approx 27,720 deaths
2003 – Italy, 1/6 to 15/8 3134 (15%) in all
Italian capitals.
Deaths in same period in 2002 (Conti et al., 2005)
2003 – France
1/8 to 20/8
14802 (60%) Average of deaths for same period in
years 2000 to 2002
(Insitut de Veille
Sanitaire, 2003)
2003 – Portugal
1/8 to 31/8
1854 (40 %) Deaths in same period in 1997-2001 (Botelho et al., 2005)
2003 – Spain
1/8 to 31/8
3166 (8%) Deaths in same period 1990-2002 (Navarro et al., 2004)
2003- Switzerland,
1/6 to 31/8 [3 months]
975 deaths
(6.9%)
Predicted values from Poisson
regression model.
(Grize et al., 2005)
2003 – Netherlands
01/06 – 23/08
1400 deaths Number of degrees above 22,3 °C
multiplicated with the estimated
number of excess deaths per degree
(25-35 excess deaths
(Centraal Bureau voor de
Statistiek (CBS), 2003)
2003 - Baden-
Wuertermburg, Germany
01/08 – 24/08
1410 deaths Calculations based on mortality of past
five years
(Sozialministerium
Baden-Wuerttemberg,
2004)
2003 – Belgium 1297 deaths for
age group over
65
Average of deaths for same period in
years 1985 to 2002
(Sartor, 2004)
2003 – England and Wales
04/08-13/08
2091 (17%). Average of deaths for same period in
years 1998 to 2002
(Johnson et al., 2005)](https://image.slidesharecdn.com/rssoct05kovats-221203024735-640d0cc6/85/RSS_Oct05_Kovats-ppt-12-320.jpg)
![past Future
2020s, 2050+
present
learn
?analogues
mechanisms
responses
detection
attribution
predictive
modelling
three research tasks
Empirical studies
[epidemiology]](https://image.slidesharecdn.com/rssoct05kovats-221203024735-640d0cc6/85/RSS_Oct05_Kovats-ppt-15-320.jpg)
![Urban area Health
outcome
measure
Model Climate
scenario
Non-climate
assumptions
Results ref
UK Heat- and
cold-related
mortality
and hospital
admissions.
Empirical-
statistical
model,
derived
from
observed
mortality.
UKCIP
scenarios
2020s,
2050s,
2080s
No population
growth. No
acclimatization
assumed.
Medium-high climate
change scenario would
result in an estimated
2800 heat deaths per
year in the UK in the
2050s (250%
increase). Greater
reductions in cold-
related mortality.
Keatinge et al.
(Department
of Health,
2002)
Lisbon,
Portugal
Heat-related
death
Empirical-
statistical
model,
derived
from
observed
summer
mortality.
2xCO2
emissions
RCMs:
PROMES
and
HadRM2
SRES population
scenarios.
Assumes some
acclimatization.
Increases in heat
related mortality, by
2020s, to range 5.8-
15.1 deaths per
100,000, from baseline
5.4-6 deaths per
100,000
(Dessai, 2003)
Six cities in
Australia
[Adelaide,
Brisbane,
Hobart,
Melbourne,
Perth,
Sydney]
Two cities in
New Zealand
[Auckland,
Christchurch]
Heat- and
cold-related
mortality in
over 65s
Empirical-
statistical
model,
derived
from
observed
monthly
mortality.
High,
medium
and low
emissions.
CSIROMk2,
ECHAM4
Population
growth, and
population
ageing.
No
acclimatization.
Increases in heat-
related mortality in
over 65s, increases
large in temperature
cities. Less reductions
in cold related
mortality.
(McMichael et
al., 2003)](https://image.slidesharecdn.com/rssoct05kovats-221203024735-640d0cc6/85/RSS_Oct05_Kovats-ppt-26-320.jpg)
![Conclusions
Estimates of near term impacts for health policy
decision makers
Need scenarios of extremes
Downscaling
– Interactions between cc and UHI [urban heat island]
Importance of population projections
Competing trends
Importance of metrics
– Deaths, YLL, dollars.
Modifiers and adaptive capacity
– Must be evidence based, but up to a point….](https://image.slidesharecdn.com/rssoct05kovats-221203024735-640d0cc6/85/RSS_Oct05_Kovats-ppt-30-320.jpg)
RSS_Oct05_Kovats.ppt
- 1. Climate Change and Human Health: an overview Sari Kovats Centre on Global Change and Health, Department of Public Health and Policy, London School of Hygiene and Tropical Medicine. 17 October 2005 RSS Meeting
- 2. International environment agenda 1972 Club of Rome Limits to Growth . 1972 UN World Conference on the Human Environment. 1987. World Commission on Environment and Development “Our Common Future” WSSD. [World Summit on Sustainable Development] Rio 1992 – Framework Conventions on Climate Change, Biodiversity and others. – Agenda 21 1997 Kyoto Protocol WSSD - Johannesburg 2002 [Rio+10] – UN Kofi Annan proposed five key areas for particular focus: WEHAB [Water, Energy, Health, Agriculture, Biodiversity] 2005 Kyoto Protocol comes into force. US opts out. Millennium Development Goals
- 3. Shifting environmental burdens Local Immediate Delayed Risks to human health Risks to life support systems Global Smith et al. 1999
- 4. Source: WHO, 2003: Climate change and human health: risks and responses.
- 6. Past changes in global mean temperature
- 7. -1.00 0.00 1.00 2.00 3.00 4.00 5.00 6.00 1961 1971 1981 1991 2001 2011 2021 2031 2041 2051 2061 2071 2081 2091 Year Change in Global Temperatures wrt 1961-90 (°C) IS92A A1FI A2a A2b A2c A2(Mean) B1a B2a B2b B2(mean) Source: IPCC, 2001 Global mean temperature.. future projections
- 8. Several models - All SRES Envelope 1990 1900 2000 2100 I Risks to Unique and Threatened Systems II Risks from Extreme Climate Events III Distribution of Impacts IV Aggregate Impacts V Risks from Future Large-Scale Discontinuities Reasons for concern Temperature change ( o C) I II III IV V 6 5 4 3 2 1 0 -1 A1F1 A1B A1T A2 B1 B2 IS92A Observed
- 9. Changes in phenomenon Confidence in observed changes (latter half of 1900s) Confidence in projected changes to 2100 Higher maximum temperatures - more hot days Likely Very likely Higher minimum temperatures, - fewer cold days and frost days Very likely Very likely Increase of heat index over land areas Likely Very likely More intense precipitation events Likely, (N mid to high latitudes) Very likely Increased summer continental drying and associated risk of drought Likely, in a few areas Likely, over most mid- latitude continental interiors. Increase in tropical cyclone peak wind intensities Not observed in the few analysis available Likely, over some areas Increase in tropical cyclone mean and peak precipitation intensities Insufficient data Likely, over some areas IPCC WORKING GROUP I Third Assessment Report 2001
- 10. Climate change may entail change in variance, as well as a change in mean
- 11. : 1999-2002 versus 2003 Mortality in Paris during 2003 heat wave
- 12. approx 27,720 deaths 2003 – Italy, 1/6 to 15/8 3134 (15%) in all Italian capitals. Deaths in same period in 2002 (Conti et al., 2005) 2003 – France 1/8 to 20/8 14802 (60%) Average of deaths for same period in years 2000 to 2002 (Insitut de Veille Sanitaire, 2003) 2003 – Portugal 1/8 to 31/8 1854 (40 %) Deaths in same period in 1997-2001 (Botelho et al., 2005) 2003 – Spain 1/8 to 31/8 3166 (8%) Deaths in same period 1990-2002 (Navarro et al., 2004) 2003- Switzerland, 1/6 to 31/8 [3 months] 975 deaths (6.9%) Predicted values from Poisson regression model. (Grize et al., 2005) 2003 – Netherlands 01/06 – 23/08 1400 deaths Number of degrees above 22,3 °C multiplicated with the estimated number of excess deaths per degree (25-35 excess deaths (Centraal Bureau voor de Statistiek (CBS), 2003) 2003 - Baden- Wuertermburg, Germany 01/08 – 24/08 1410 deaths Calculations based on mortality of past five years (Sozialministerium Baden-Wuerttemberg, 2004) 2003 – Belgium 1297 deaths for age group over 65 Average of deaths for same period in years 1985 to 2002 (Sartor, 2004) 2003 – England and Wales 04/08-13/08 2091 (17%). Average of deaths for same period in years 1998 to 2002 (Johnson et al., 2005)
- 13. Impacts of climate change Agriculture and food security Sea level rise, coastal flooding and coastal areas. Biodiversity and ecosystems Water resources Human health Infrastructure, industry and human settlements Weather disasters (floods, storms).
- 14. REGIONAL WEATHER CHANGES: - extreme weather - temperature - precipitation Air pollution levels Contamination pathways Transmission dynamics HEALTH EFFECTS Heat-related illness, death Flood, storm- related health effects Air pollution effects Water- and food borne diseases Vector-borne and rodent-borne disease Adaptation measures Moderating influences CLIMATE CHANGE How climate change affects health
- 15. past Future 2020s, 2050+ present learn ?analogues mechanisms responses detection attribution predictive modelling three research tasks Empirical studies [epidemiology]
- 16. Complexity: different types of evidence for health effects Health impacts of individual extreme events (heat waves, floods, storms, droughts); Spatial studies, where climate is an explanatory variable in the distribution of the disease or the disease vector Temporal studies, – inter-annual climate variability, – short term (daily, weekly) changes (weather) – longer term (decadal) changes in the context of detecting early effects of climate change. Experimental laboratory and field studies of vector, pathogen, or plant (allergenic) biology.
- 17. Assessment of causality… measure and control confounders; describe the geographical area from which the health data are derived; use appropriate observed meteorological data for population of interest (the use of reanalysis data may give spurious results for studies of local effects); have plausible biological explanation for association between weather parameters and disease outcome; remove any trend and seasonal patterns when using time-series data prior to assessing relationships; report associations both with and without adjustments for spatial or temporal autocorrelation.
- 18. Detection and attribution What is the scientific evidence that global climate change is affecting human health? Where and how should we be looking for evidence? Considering the paucity of data, what do we accept as evidence within this context?
- 19. Tick-borne Encephalitis, Sweden: 1990s vs 1980s: winter warming trend Early 1980s Mid- 1990s White dots indicate locations where ticks were reported. Black line indicates study region. (Lindgren et al., 2000)
- 20. Evidence on biological effects of observed climate change effects on physiology: metabolic or development rates of animals, and plant processes; effects on distributions: response to shifts in mean temperature and precipitation conditions Effect on phenology: timing of life-cycle events, e.g. budding of flowers or egg laying; Adaptation: species with short generation times and rapid population growth rates may undergo some micro-evolution. Hughes 2000
- 21. Evidence of northward shifts: Europe Bluetongue virus- disease and vector in Europe – (Mellor and Hamblin, 2004; Purse et al., 2005) Leishmaniasis (which also affects humans) in dog reservoir – ? role of previous underreporting (Lindgren and Naucke, 2005) Tick vectors- – Sweden (Lindgren and Talleklint, 2000; Lindgren and Gustafson, 2001) – Denmark (Skarphedinsson et al., 2005) – Canada (Barker and Lindsay, 2000)
- 22. How CC differs from other environmental health risk assessments Scenario based. – Population not individual exposure assessment Future worlds: – Population growth – Development pathway disease baseline relationship between climate and impacts (adaptive capacity)
- 23. Global Burden of Disease Standard method developed by WHO. Based on best-available quantitative evidence Estimates by region, age, sex Combined metric – DALY – Disability adjusted life year Identifies global and regional health priorities…
- 24. Impact models Estimates of populations at risk • hunger • water stress • coastal flooding • malaria • dengue Greenhouse gas emissions scenarios Defined by IPCC Global climate scenarios: Generates series of maps of predicted future distribution of climate variables 30 year averages 2020s 2050s 2080s Time 2050 2100 2020s 2050s 2080s Modelling impacts of climate change
- 25. Assumptions: e.g. heat-related mortality Adaptive capacity – Climate change concept, reflects ability of a population to cope with impacts of climate change Acclimatization – Threshold of mortality response moves Changes in exposure response relationship – E.g. due to changes in air conditioning access, etc. – Evident for both heat and cold effects – ?independent of aging population Evidence base – Published studies that show observed changes since 1900….Heat (Davies, Keatinge) and cold (Kunst, Keatinge, Carson) .8 .9 1 1.1 1.2 1.3 Relative risk 0 10 20 30 40 Maximum temperature (lag 0) All-cause mortality
- 26. Urban area Health outcome measure Model Climate scenario Non-climate assumptions Results ref UK Heat- and cold-related mortality and hospital admissions. Empirical- statistical model, derived from observed mortality. UKCIP scenarios 2020s, 2050s, 2080s No population growth. No acclimatization assumed. Medium-high climate change scenario would result in an estimated 2800 heat deaths per year in the UK in the 2050s (250% increase). Greater reductions in cold- related mortality. Keatinge et al. (Department of Health, 2002) Lisbon, Portugal Heat-related death Empirical- statistical model, derived from observed summer mortality. 2xCO2 emissions RCMs: PROMES and HadRM2 SRES population scenarios. Assumes some acclimatization. Increases in heat related mortality, by 2020s, to range 5.8- 15.1 deaths per 100,000, from baseline 5.4-6 deaths per 100,000 (Dessai, 2003) Six cities in Australia [Adelaide, Brisbane, Hobart, Melbourne, Perth, Sydney] Two cities in New Zealand [Auckland, Christchurch] Heat- and cold-related mortality in over 65s Empirical- statistical model, derived from observed monthly mortality. High, medium and low emissions. CSIROMk2, ECHAM4 Population growth, and population ageing. No acclimatization. Increases in heat- related mortality in over 65s, increases large in temperature cities. Less reductions in cold related mortality. (McMichael et al., 2003)
- 27. High child, high adult High child, very high adult M F Both M F M F (000) (000) (000) (000) (000) (000) (000) Addictive substances Tobacco 3 893 1 014 4 907 43 7 84 26 Alcohol 1 638 166 1 804 53 15 125 30 Illicit drugs 163 41 204 5 1 1 0 Environmental risks Unsafe water, sanitation hygiene 895 835 1 730 129 103 207 169 Urban air pollution 411 388 799 11 11 5 5 Indoor smoke from solid fuels 658 961 1 619 93 80 118 101 Lead exposure 155 79 234 5 4 4 3 Climate change 76 78 154 9 9 18 18 Occupational risks Risk factors for injury 291 19 310 14 1 18 1 Carcinogens 118 28 146 1 0 1 1 Airborne particulates 217 26 243 3 0 3 0 Ergonomic stressors 0 0 0 0 0 0 0 Noise 0 0 0 0 0 0 0 World Africa World Health Report 2002 Global Burden of Disease World Health Organization
- 28. Diarrhoea incidence in AfrD 0.8 0.9 1 1.1 1.2 1.3 1.4 1990 2000 2010 2020 2030 2040 Year Ann. Incidence/1000 No cc UE (low) UE (mid) UE (high) Applying the relative risk to baseline incidence
- 29. Three eras of public health practice Era Risk Source Public health response Industrial revolution 1870-1930 Infectious disease Cholera, diphtheria, TB Water, air, crowding Technical solutions Sewerage, domestic hygiene, urban design Economic development 1930-1970 Ways of living. Acute toxicity, lung cancer, chemicals Lead, asbestos, waste Lifestyle change Petrol standards, monitoring and reporting, Sustainable Development 1970- Global stress Melanoma, disease spread, allergies, toxicity UV radiation, climate change, environmental degradation Governance solutions CFC controls, limit energy use, environmental management. Source: Brown et al. 2005, p 5.
- 30. Conclusions Estimates of near term impacts for health policy decision makers Need scenarios of extremes Downscaling – Interactions between cc and UHI [urban heat island] Importance of population projections Competing trends Importance of metrics – Deaths, YLL, dollars. Modifiers and adaptive capacity – Must be evidence based, but up to a point….