Climate change will affect human health through a wide range of mechanisms and for a number of diseases (such as malaria) and health outcomes. It is possible to quantify the impact of future climate scenarios on human health using observed associations between climate and health. For example:
- Temperature and rainfall both affect the seasonal pattern of diarrhoeal disease. There is evidence that rainfall is a determinant of diarrhoeal disease at the global level, irrespective of socio-economic factors. A global study examined diarrhoea incidence in children under five, taking account of age, socio-economic conditions, and access to improved water and sanitation. The incidence of infant diarrhoea was found to increase by 4% for each 10 mm fall in monthly rainfall.
- Climate change is associated with an increase in diarrhoeal disease due to temperature sensitivity, but this is against a background of declining mortality due to diarrhoeal disease.
- Climate change will increase heat-related mortality and decrease cold-related mortality (as the Athens study below illustrates). Estimated changes in temperature-sensitive cardiovascular (heart-related) mortality are largely due to an ageing population, and the high incidence of cardiovascular disease in low and middle income countries.
- Climate change is projected to reduce labour productivity, particularly in South East Asia and Africa.
Future disease projections, however, are sensitive to underlying assumptions about population growth, ageing, and future health status.
Health impacts of high temperatures in Athens
A statistical model for heat stress was constructed for Athens, using weather and daily mortality data for summer months 1992-2006. Two approaches were taken to calculate excess deaths (deaths beyond those expected – calculated by subtracting the expected from the observed daily death values):
- A. Use of a fixed mean (average) of daily mortality for each summer month (78.9 deaths for June, 81.2 in July and 79.1 in August).
- B. Use of a 30-days running mean, which smoothes the fluctuations in the death data.
Both approaches show that heat-related deaths are not discernible below 34°C but hotter days are associated with greater mortality risk. Substantial heat-related deaths occur at very high temperatures (left figure) in a quasi-exponential mode (i.e., with an upward curve, rather than as a straight line).
To provide an estimate of future mortality, the statistical model above was applied to daily output data from two ENSEMBLES regional climate models for two 30-year future periods (2021-2050 and 2071-2100).Significantly increased rates of mortality were projected for 2021-2050 and 2071-2100 especially when using an exponential fit which may overestimate the impact. Therefore an adaptation factor of 1oC per 30 year period was assumed, meaning that people will adapt to a 1oC temperature increase after a 30-year period. Even with this adaptation factor, both linear and exponential fits show increases in heat related deaths (right-hand figure) which should be taken into account by governmental health services.