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Malaria, India, all states

Climate suitability for falciparum and vivax malaria transmission

Temperature transmission windows based on observed associations between temperature and malaria cases

HadRM2 driven by IS92a emissions scenario

2 to 4°C increase compared with current climate

None

By 2050s, geographical range projected to shift away from central regions towards south-western and northern states. The duration of the transmission window is likely to widen in northern and western states and shorten in southern states.

Bhattacharya et al., 2006

Malaria, India, all states

Climate suitability for falciparum and vivax malaria transmission

Temperature transmission windows based on observed associations between temperature and malaria cases

HadRM2 driven by IS92a emissions scenario

2 to 4°C increase compared with current climate

None

By 2050s, geographical range projected to shift away from central regions towards south-western and northern states. The duration of the transmission window is likely to widen in northern and western states and shorten in southern states.

Bhattacharya et al., 2006

Dengue, global

Population at risk

Statistical model based on vapour pressure. Baseline number of people at risk is 1.5 billion.

ECHAM4, HadCM2, CCSR/NIES, CGCMA2, and CGCMA1 driven by IS92a emissions scenarios

Population By 2085, with both population growth and growth based on climate change, global population at risk 5 to 6 region-specific billion; with climate change only, global projections population at risk 3.5 billion.

Hales et al., 2002

Dengue, Map of vector Threshold model based on New Zealand 'hotspots'; dengue rainfall and temperature currently not present in New Zealand

DARLAM GCM driven by A2 and B2 emissions scenarios 2050,2100

None

Potential risk of dengue outbreaks in some regions under the current climate. Climate change projected to increase risk of dengue in more regions.

Dengue, Australia

Map of regions climatically suitable for dengue transmission

Empirical model (Hales et al., 2002)

CSIROMk2, ECHAM4, 1.8 to 2.8°C global None and GFDL driven by average high (A2) and low (B2) temperature emissions scenarios and increase a stabilisation scenario compared with at 450 ppm 2100_1961-1990_

Regions climatically suitable increase southwards; size of suitable area varies by scenario. Under the high-emissions scenario, regions as far south as Sydney could become climatically suitable.

Woodruff et al., 2005

Lyme Geographical range Statistical model based on disease, and abundance of observed relationships; tick-Canada Lyme disease abundance model vector Ixodes scapularis

CGCM2 and HADCM2 driven by SRES A2 and B2 emissions scenarios 2020s, 2050s, 2080s

None

Northward expansion of approximately 200 km by 2020s under both scenarios, and approximately 1000 km by 2080s under A2. Under the A2 scenario, tick abundance increases 30 to 100% by 2020s and 2- to 4-fold by 2080s. Seasonality shifts.

Ogden et al. 2006

Tick-borne encephalitis,

Europe

Geographical range

Statistical model based on present-day distribution

HadCM2 driven by low, 3.45°C increase in None medium-low, medium-high, and high degrees of change (not further defined) 2020s, 2050s, 2080s mean temperature in 2050s under high scenario, baseline not defined

From low to high degrees of climate change, tick-borne encephalitis is pushed further northeast of its present range, only moving westward into southern Scandinavia. Only under the low and medium-low scenarios does tick-borne encephalitis remain in central and eastern Europe by the 2050s._

Randolph and Rogers, 2000

Diarrhoeal Diarrhoea disease, incidence global, 14 (mortality) world regions

Statistical model, derived from cross-sectional study, including annual average temperature, water supply and sanitation coverage, and GDP per capita

SRES A1B, A2, B1 and B2 emissions scenarios 2025, 2055

SRES population Results vary by region and scenario. Generally, Hijioka et al. growth diarrhoeal disease increases with temperature 2002

increase.

Diarrhoeal Hospital disease, admissions in

Aboriginal children aged community, under 10

central

Australia

(Alice Springs)

Exposure-response relationship CSIROMk2 and based on published studies

ECHAM4 driven by SRES B1, A1B and A1FI emissions scenarios 2020, 2050

0.4 to 2.0°C annual None average temperature increase in the 2030s, and 1.0 to 6.0°C in the 2070s, relative to 1990 (CSIRO)

Compared with baseline, no significant increase McMichael by 2020 and an annual increase of 5 to 18% by et al., 2003b 2050.

Food Notified cases of poisoning, food poisoning

England and (non-specific) Wales

Statistical model, based on observed relationship with temperature

UKCIP scenarios 2020s, 2050s, 2080s

0.57 to 1.38°C in 2020s; 0.89 to 2.44°C in 2050s; 1.13 to 3.47°C in 2080s compared with 1961-1990 baseline

None

For +1, +2 and +3°C temperature increases, absolute increases of approximately 4,000, 9,000, and 14,000 notified cases of food poisoning

Department of Health and Expert Group on Climate Change and Health in the UK, 2001

Table 8.3. Projected impacts of climate change on heat- and cold-related mortality.

Health effect

Climate Temperature scenario, time increase and slices baseline

Population projections and other assumptions

Main results

Reference

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