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Using climate information for improved health in Africa: relevance, constraints and opportunities
Stephen J Connor1, Pietro Ceccato, Tufa Dinku
1International Research Institute for Climate and Society, The Earth Institute at Columbia University, Palisades, New York 10964-8000, USA.
Abstract:
Good health status is one of the primary aspirations of human social development and, as a consequence, health indicators are key components of the human development indices by which we measure progress toward sustainable development. Certain diseases and ill health are associated with particular environmental and climate conditions. The timeframe of the Millennium Development Goals (MDGs) demands that the risks to health associated with current climate variability are more fully understood and acted upon to improve the focus of resources in climate sensitive disease control, especially in sub-Saharan Africa, where good epidemiological surveillance data are lacking. In the absence of high-quality epidemiological data on malaria distribution in Africa, climate information has long been used to develop malaria risk maps illustrating the climatic suitability boundaries for endemic transmission. However, experience to date has shown that it is difficult in terms of availability, timing and cost to obtain meteorological observations from national meteorological services in Africa. National health services generally find the costs of purchasing these data prohibitive given their competing demands for resources across the spectrum of health service requirements. Some national health services have tried to overcome this access problem by using proxies derived from satellites, which tend to be available freely, in 'near-real-time' and therefore offer much promise for monitoring applications. This paper discusses the issues related to climate and health, reviews the current use of climate information for malaria endemic and epidemic surveillance, and presents examples of operational use of climate information for malaria control in Africa based on Geographical Information Systems and Remote Sensing.
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