An extensive evaluation of 10 different satellite rainfall products was performed using station network over a complex topography, where elevation varies from below sea level to 4620 m. Evaluation was for two groups of products. The first group had low spatial (2.5u) and temporal (monthly) resolution and included the Global Precipitation Climatology Project (GPCP), the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) merged analysis (CMAP), and the Tropical Rainfall Measuring Mission (TRMM-3B43). The second group comprised products with relatively high spatial (0.1u to 1u) and temporal (3-hourly to 10-daily) resolution. These included the NOAA-CPC African rainfall estimation algorithm, GPCP one-degree-daily (1DD), TRMM-3B42, Tropical Applications of Meteorology using SATellite and other data (TAMSAT) estimates, and the CPC morphing technique (CMORPH). These products were aggregated to a 10-day total and remapped to spatial resolutions of 1u, 0.5u and 0.25u. TRMM-3B43 and CMAP from the first group and CMORPH, TAMSAT and TRMM-3B42 from the second group performed reasonably well.

Until recently, drought events were inconsistently recorded in EM-DAT. Problems included inconsistent establishment of start and end dates, misattribution of losses, and difficulties with handling multiyear and multicountry events, mostly arising from the slow onset, spatially extensive, prolonged, and complex nature of drought. This article summarizes the procedures and results of a comprehensive review of 807 drought and 76 famine entries from 1900 to 2004. A standardized methodology has been developed for characterizing drought events that is consistent with all other natural hazards recorded in the database. The result consists in a reduction of 56% from the original number of drought entries, a 20% increase in the number of deaths and a 35% increase in economic losses. Based on the revised data, more than half of all deaths associated with natural hazards are now classified as drought related, and only floods rank higher in terms of the number of people affected.

Malaria remains a major public health threat to more than 600 million Africans and its control is recognized as critical to achieving the Millennium Development Goals. The greatest burden of malaria in Africa occurs in the endemic regions where the disease pathogen is continuously present in the community. These regions are characterized by an environment that is conducive to interactions between the Anopheles mosquito, malaria parasites and human hosts, as well as housing of generally poor quality, which offers little protection from mosquito-human contact. Epidemic malaria tends to occur along the geographical margins of endemic regions, when the equilibrium between the human, parasite and mosquito vector populations is occasionally disturbed and a sharp but temporary increase in disease incidence results. When malaria control measures are inadequate, as is the case in much of sub-Saharan Africa, the disease distribution is closely linked with seasonal patterns of the climate and local environment. In the absence of good epidemiological data on malaria distribution in Africa, climate information has long been used to develop malaria risk maps that illustrate the boundaries of 'climatic suitability for endemic transmission.' The best known of these are produced by the Pan-African-based MARA Collaboration. This paper describes the development of additional malaria suitability maps which have been produced in an online, interactive format to enable temporal information (i.e., seasonality of climate conditions) to be queried and displayed along with spatial information. These maps and the seasonal information that they contain should be useful to the malaria control and health service communities for their planning and operational activities.

Periodic epidemics of malaria are a major public health problem for many sub-Saharan African countries. Populations in epidemic prone areas have a poorly developed immunity to malaria and the disease remains life threatening to all age groups. The impact of epidemics could be minimized by prediction and improved prevention through timely vector control and deployment of appropriate drugs. Malaria Early Warning Systems are advocated as a means of improving the opportunity for preparedness and timely response.

A number of the major human infectious diseases (like malaria and dengue) and Desert Locusts that still plague the developing world are sensitive to inter-seasonal and inter-decadal changes in environment and climate. Monitoring variations in environmental conditions such as rainfall and vegetation helps decision-makers at Ministries of Agriculture and Ministries of Health to assess the risk levels of Desert Locust outbreaks or malaria epidemics. The International Research Institute for Climate and Society (IRI) has developed products based on remotely sensed data to monitor those changes and provide the information directly to the decision-makers. This paper presents recent developments which use remote sensing to monitor climate variability, environmental conditions and their impacts on the dynamics of infectious diseases (malaria) and Desert Locust outbreaks.