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Weather, climate and health
Simon Lloyd
London School of Hygiene
and Tropical Medicine
Health outcomes influenced by climate:
likely impacts of climate change
Figure 8.3: Ch 8 Human Health, IPCC 4AR
Health outcomes influenced by climate:
likely impacts of climate change
• Impact on existing burden of disease
• Various exposures of interest
• At times, complex links
Figure 8.3: Ch 8 Human Health, IPPC 4AR
Health outcomes influenced by climate:
likely impacts of climate change
Long term changes in means
Daily or weekly changes
Interannual variability
Extreme weather events
• Impact on existing burden of disease
• Various exposures of interest
• At times, complex links
Figure 8.3: Ch 8 Human Health, IPPC 4AR
Health outcomes influenced by climate:
likely impacts of climate change
• Impact on existing burden of disease
• Various exposures of interest
• At times, complex links
Figure 8.3: Ch 8 Human Health, IPPC 4AR
Exposure – outcome relationships
Epidemiology at individual level
Exposure
Smoking
Outcome
Cardiovascular
disease
Exposure – outcome relationships
Epidemiology at individual level
Exposure
Outcome
Cardiovascular
disease
Smoking
Weather/climate and health:
• Exposure at population level
• Pathway (often) indirect and complex
• Impact moderated by vulnerability
Climate change and health: Risks and Responses, WHO 2003.
Climate change and health: Risks and Responses, WHO 2003.
Climate change and health: Risks and Responses, WHO 2003.
Climate change and health: Risks and Responses, WHO 2003.
Types of evidence for health effects
Spatial studies
• Climate as an explanatory variable in the distribution of
the disease or the disease vector
Temporal studies
• short term (daily, weekly) changes
• inter-annual climate variability
• longer term (decadal) changes in the context of
detecting early effects of climate change.
Health impacts of individual extreme events
• heat waves, floods, storms, droughts
Diarrhoea and average weather
Diarrhoea and average weather
Diarrhoea
rates
Diarrhoea and average weather
Temperature
Diarrhoea
rates
Mechanism: pathogen survival
Diarrhoea and average weather
Temperature
High rainfall
Mechanism: water supply contamination (water quality)
Diarrhoea
rates
Diarrhoea and average weather
Temperature
High rainfall
Diarrhoea
rates
Low rainfall
Mechanism: use of unprotected water sources; reduced hygiene
behaviour (water quantity)
Diarrhoea and average weather
Temperature
Water and
sanitation
Diarrhoea
rates
High rainfall
Malnutrition
Low rainfall
etc.
Climate type
Socioeconomic conditions
Data
Outcome
Exposure
Co-variates
Data
Outcome
• Diarrhoea morbidity
• Children under 5 years
Exposure
• Low and middle income countries
• 36 study sites
Co-variates
Data
Outcome
• Av. temperature over study period
• Av. rainfall over study period
Exposure
CRU TS 2.1 dataset
• Underlying climate
Köppen climate classification
Co-variates
Data
Outcome
• Socioeconomic conditions
Exposure
• Water and sanitation
• Setting: urban, rural, slum
Co-variates
Study sites
Lloyd, Kovats & Armstrong. Clim Res 2007; 34:119-27
Diarrhoea cases vs average weather
Temperature and children aged one year
3
3
Rainfall and children 6-11 months old
Brazil
2
India Guatemala
Kenya
Egypt
Argentina Papua New Guinea
Nigeria
Zimbabwe
Bangladesh
India
China
Costa Rica
Brazil
Guatemala
-1
0
India
Indonesia
India
Guatemala
Thailand
0
1
India
Ghana
1
Log episodes/child-year
2
Peru
Peru
Brazil
Egypt
Costa Rica
Indonesia
10
15
20
25
30
Average mean temperature (degrees C)
-1
5
0
100
200
300
Average precipitation (mm/month)
r=-0.36
Average monthly rainfall and log
diarrhoea incidence in children aged
6-11 months, showing country
400
Tropical
Arid
Temperate
Boreal forest
r=-0.03
Average temperature and log diarrhoea
incidence in children aged 1 year,
showing climate classification.
Lloyd, Kovats & Armstrong. Clim Res 2007; 34:119-27
Regression results
Variable
GDP
Precipitation
Model 1
Model 2
Model 3
Model 4
1.00 (1.00-1.00) 1.00 (1.00-1.00)
1.00 (1.00-1.00)
1.00 (1.00-1.00)
0.97 (0.94-1.00)
0.97 (0.94-1.00)
0.96 (0.93-0.99)
1.02 (0.97-1.07)
1.03 (0.97-1.09)
Temperature
Setting: rural
1
urban
0.73 (0.42-1.29)
slum
1.01 (0.45-2.28)
mixed
1.63 (0.38-6.93)
All models are adjusted for age group. Coefficients indicate the change in diarrhoea rate (episodes per
child-year) for each: 10USD (in 2000 USDs) increase in GDP/capita; 10mm/month increase in average
monthly rainfall; and, 1C increase in average temperature
Lloyd, Kovats & Armstrong. Clim Res 2007; 34:119-27
Regression results
Variable
GDP
Precipitation
Model 1
Model 2
Model 3
Model 4
1.00 (1.00-1.00) 1.00 (1.00-1.00)
1.00 (1.00-1.00)
1.00 (1.00-1.00)
0.97 (0.94-1.00)
0.97 (0.94-1.00)
0.96 (0.93-0.99)
1.02 (0.97-1.07)
1.03 (0.97-1.09)
Temperature
Setting: rural
urban
slum
1
Diarrhoea ↓ 4% (1 – 7%) for
for each 10mm/month rainfall ↑
mixed
0.73 (0.42-1.29)
1.01 (0.45-2.28)
1.63 (0.38-6.93)
All models are adjusted for age group. Coefficients indicate the change in diarrhoea rate (episodes per
child-year) for each: 10USD (in 2000 USDs) increase in GDP/capita; 10mm/month increase in average
monthly rainfall; and, 1C increase in average temperature
Lloyd, Kovats & Armstrong. Clim Res 2007; 34:119-27
Extreme events: coastal flooding
• Spatial scale
– WHO GBD regions
Extreme events: coastal flooding
• Spatial scale
– WHO GBD regions
• Event and outcome data
– International Emergency Disaster Database,
University of Louvain, Belgium.
EM-DAT
Initial estimates of impacts of extratropical & tropical cyclones, 1980 - 2007
Region
[EMDAT, 2008]
Events
Killed
Killed/event
Affected
Affected/event
AP_HI
83
2715
33
2 180 872
26 276
As_C
2
0
0
2800
1400
As_E
161
9736
60
221 000 000
1 372 671
As_S
105
185 095
1763
105 000 000
1 000 000
As_SE
247
33 461
135
109 000 000
441 296
Au
28
63
2
18 925
676
Ca
185
4478
24
15 300 000
82 703
Eu_C
6
13
2
8000
1333
Eu_E
21
71
3
329 326
15 682
Eu_W
36
236
7
3 475 200
96 533
LA_A
1
518
518
580 000
580 000
LA_C
109
23 799
218
11 000 000
100 917
LA_S
-
-
-
-
-
LA_T
1
4
4
150 000
150 000
NA_HI
59
2447
41
10 400 000
176 271
NA_ME
6
127
21
180 050
30 008
Oc
94
688
7
1 623 948
17 276
SSA_C
1
17
17
0
0
SSA_E
62
2472
40
8 404 123
135 500
SSA_S
4
125
31
1 132 000
283 000
SSA_W
4
33
8
9322
2331
Initial estimates of impacts of extratropical & tropical cyclones, 1980 - 2007
Region
[EMDAT, 2008]
Events
Killed
Killed/event
Affected
Affected/event
AP_HI
83
2715
33
2 180 872
26 276
As_C
2
0
0
2800
1400
As_E
161
9736
60
221 000 000
1 372 671
As_S
105
185 095
1763
105 000 000
1 000 000
As_SE
247
33 461
135
109 000 000
441 296
Au
28
63
2
18 925
676
Ca
185
4478
24
15 300 000
82 703
Eu_C
6
13
2
8000
1333
Eu_E
21
71
3
329 326
15 682
Eu_W
36
236
7
3 475 200
96 533
LA_A
1
518
518
580 000
580 000
LA_C
109
23 799
218
11 000 000
100 917
LA_S
-
-
-
-
-
LA_T
1
4
4
150 000
150 000
NA_HI
59
2447
41
10 400 000
176 271
NA_ME
6
127
21
180 050
30 008
Oc
94
688
7
1 623 948
17 276
SSA_C
1
17
17
0
0
SSA_E
62
2472
40
8 404 123
135 500
SSA_S
4
125
31
1 132 000
283 000
SSA_W
4
33
8
9322
2331
Initial estimates of impacts of extratropical & tropical cyclones, 1980 - 2007
Region
[EMDAT]
Events
Killed
Killed/event
Affected
Affected/event
AP_HI
83
2715
33
2 180 872
26 276
As_C
2
0
0
2800
1400
As_E
161
9736
60
221 000 000
1 372 671
As_S
105
185 095
1763
105 000 000
1 000 000
As_SE
247
33 461
135
109 000 000
441 296
Au
28
63
2
18 925
676
Ca
185
4478
Eu_C
6
13
2
8000
1333
Eu_E
21
71
3
329 326
15 682
Eu_W
36
236
7
3 475 200
96 533
LA_A
1
518
518
580 000
580 000
LA_C
109
23 799
218
11 000 000
100 917
LA_S
-
-
-
-
-
LA_T
1
4
4
150 000
150 000
NA_HI
59
2447
41
10 400 000
176 271
NA_ME
6
127
21
180 050
30 008
Oc
94
688
7
1 623 948
17 276
SSA_C
1
17
17
0
0
SSA_E
62
2472
40
8 404 123
135 500
SSA_S
4
125
31
1 132 000
283 000
SSA_W
4
33
8
9322
2331
140 000 in a single
24
15 300 000
event in 1991
82 703
Interannual variability: ENSO
• Human impact of natural disasters increases
during El Niño
• ENSO associated with infectious diseases in
some areas, esp cholera risk and malaria
epidemics
• ENSO and seasonal climate forecasts may
have public health use
Interannual variability: ENSO
• Human impact of natural disasters increases
during El Niño
• ENSO associated with infectious diseases in
Global disaster burden associated with El Niño over
some areas, esp cholera risk and malaria
a 30 year period (1964-1993)
epidemics
• Exposure: consensus El Niño years
• ENSO and seasonal climate forecasts may
• Outcome: affected by a natural disaster
have public health use
World population affected by natural disasters
Rate per 1000 people, 1964-93
Incidence per 1000
80
70
60
50
40
30
20
10
El Niño years
Possible El Niño years
Bouma, Kovats et al. Lancet 1997; 350:1435-8
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
0
Non-El Niño years
World population affected by natural disasters
Rate per 1000 people, 1964-93
Incidence per 1000
80
70
60
50
40
30
20
10
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
0
Strongest association between El Niño and drought
(including food shortage and famine):
• sub-Saharan Africa, South America, and South and
West Asia
Extreme rainfall and tropical cyclones: mixed effects by
region
Bouma, Kovats et al. Lancet 1997; 350:1435-8
El Niño: a natural disaster cycle?
Incidence /1000 (dev.trend)
30
25
20
15
10
5
0
-5
N-2
N-1
Nino year
-10
-15
-20
Bouma, Kovats et al. Lancet 1997; 350:1435-8
N+1
N+2
El Niño: a natural disaster cycle?
Incidence /1000 (dev.trend)
30
25
20
15
150
10
5
million
0
-5
N-2
N-1
Nino year
-10
-15
-20
Bouma, Kovats et al. Lancet 1997; 350:1435-8
N+1
N+2
people
Climate and respiratory health in children
Climate and respiratory health in children
Previous studies
↓ temperature range
↓ relative humidity range
Asthma ↑ with:
↑ temperature in coldest month
↑ mean annual temperature
Data needs and queries
• How well does data represent climate at particular
study sites?
• Are there areas that are not well represented?
• Can data be used to quantify elements of events?
• E.g. rainfall in floods; extent, intensity & duration of drought.
• How well are ENSO events and their associated
impacts on climate events represented?