Session 4.3 Providing a climatological perspective for malaria early warning systems in Africa

Tuesday, 21 June 2005: 2:45 PM
South Ballroom (Hilton DeSoto)
Emily K. Grover-Kopec, IRI/Columbia Univ., Palisades, NY; and M. B. Blumenthal, S. J. Connor, M. Kawano, R. W. Klaver, and P. Ceccato

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Estimates indicate that more than 110 million people in sub-Saharan Africa live in areas prone to epidemics of malaria, making the disease a major public health problem in many parts of the region. Malaria Early Warning Systems (MEWS) have been advocated as a method of improving the preparedness for, and timely response to, these epidemics, thereby reducing their impact on society. Rainfall is one of the major factors triggering malaria epidemics in warm semi-arid and desert-fringe areas. Consequently, monitoring of rainfall is an essential component of MEWS. While the Famine Early Warning Systems Network (FEWS Net) produces maps that combine information about dekadal rainfall anomalies and epidemic malaria risk, field visits to epidemic-prone countries have indicated that additional information about the temporal distribution of rainfall would greatly benefit the users of these data.

In response to this issue, a new monitoring interface was recently developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of current rainfall estimates. Using an interactive map, dekadal rainfall can be spatially averaged over a variety of user-selected areas, including administrative districts. Upon the selection of this sampling area and the specific location of interest, four time series are generated that provide an analysis of recent rainfall. The analysis compares recent dekadal rainfall with that of previous seasons and climatology. A comparison of cumulative rainfall from the most recent 12-month period and the corresponding cumulative climatology is also shown. We anticipate that this MEWS interface will be modified to respond to user feedback and the future needs of the malaria control community. Users may access the interface via the IRI Data Library Maproom (

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