Future projections of climate change impacts on health often build on empirical relationships between observed weather indicators, socio-economic indicators and health outcomes. However, these relationships often fall short, because except for direct heat stress, most weather related health impacts, in particular malnutrition and malaria, are expected to be indirect, i.e. induced by the effect of weather on biophysical indicators such as food supply (crop yields), hydro-climatic extremes (flooding, water scarcity), natural vegetation etc. Most of these bio-physical drivers are not only influenced by weather but also by local management decisions such as investment into agriculture (development of irrigation schemes and reservoirs, fertilizer input), water management, land use changes and disaster risk reduction (e.g. flood protection). Thus, using the actual weather-related bio-physical drivers as predictors of health outcomes could lead to higher explanatory power regarding observed health outcomes than using the raw weather data.
The project will develop and apply methods for the projection of health impacts of climate change on malaria, malnutrition and heat-related mortality at the local scales of two study areas in Kenya and Burkina Faso as well as the national scale for these two countries at different time horizons (2030, 2050 and 2100).
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