An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa

被引:69
作者
Grover-Kopec, E
Kawano, M
Klaver, RW
Blumenthal, B
Ceccato, P
Connor, SJ
机构
[1] Columbia Univ, Earth Inst, Int Res Inst Climate Predict, Palisades, NY 10964 USA
[2] WHO, Publ Hlth Mapping Grp, CH-1211 Geneva 20, Switzerland
[3] WHO, Geog Informat Syst, Communicable Dis, CH-1211 Geneva 20, Switzerland
[4] US Geol Survey, EROS Data Ctr, Sioux Falls, SD 57198 USA
关键词
D O I
10.1186/1475-2875-4-6
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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. Rainfall is one of the major factors triggering epidemics in warm semi-arid and desert-fringe areas. Explosive epidemics often occur in these regions after excessive rains and, where these follow periods of drought and poor food security, can be especially severe. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization. The Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics recommended that a simple indicator of changes in epidemic risk in regions of marginal transmission, consisting primarily of rainfall anomaly maps, could provide immediate benefit to early warning efforts. In response to these recommendations, the Famine Early Warning Systems Network produced maps that combine information about dekadal rainfall anomalies, and epidemic malaria risk, available via their Africa Data Dissemination Service. These maps were later made available in a format that is directly compatible with HealthMapper, the mapping and surveillance software developed by the WHO's Communicable Disease Surveillance and Response Department. A new monitoring interface has recently been developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of the current rainfall estimates by comparing them to previous seasons and climatological averages. These resources are available at no cost to the user and are updated on a routine basis.
引用
收藏
页数:5
相关论文
共 11 条
[1]  
[Anonymous], WHOCDSRBM200132
[2]  
CONNOR SJ, 2003, IMPROVED KNOWLEDGE C
[3]   Improving epidemic malaria planning, preparedness and response in Southern Africa [J].
DaSilva, J ;
Garanganga, B ;
Teveredzi, V ;
Marx, SM ;
Mason, SJ ;
Connor, SJ .
MALARIA JOURNAL, 2004, 3 (1)
[4]   Forecasting, warning, and detection of malaria epidemics: a case study [J].
Hay, SI ;
Were, EC ;
Renshaw, M ;
Noor, AM ;
Ochola, SA ;
Olusanmi, L ;
Alipui, N ;
Snow, RW .
LANCET, 2003, 361 (9370) :1705-1706
[5]   Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II.: Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions -: art. no. 44 [J].
Teklehaimanot, HD ;
Schwartz, J ;
Teklehaimanot, A ;
Lipsitch, M .
MALARIA JOURNAL, 2004, 3 (1)
[6]   Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia I.: Patterns of lagged weather effects reflect biological mechanisms -: art. no. 41 [J].
Teklehaimanot, HD ;
Lipsitch, M ;
Teklehaimanot, A ;
Schwartz, J .
MALARIA JOURNAL, 2004, 3 (1)
[7]  
*WHO, 2002, WEEKLY EPIDEMIOLOGIC, P276
[8]  
WHO, 2004, US CLIM PRED INF DIS
[9]  
WHO, 2004, MAL EP FOR PREV EARL
[10]  
WHO, 2002, 3 M RBM TECHN RES NE