OBJECTIVE: To identify the malaria hot spots at health subcentre level in an endemic district using a geographical information system (GIS). The results will be useful for rapid retrieval of malaria information, and to prioritize malaria control efforts in identified hot spots. STUDY DESIGN: Extraction, analysis and synthesis of relevant data. METHODS: Malaria epidemiological data from 2006 to 2009 were analysed to determine the annual parasitic index, slide positivity rate, annual blood examination rate and Plasmodium falciparum percentage for each health subcentre in the district. Maps were produced using GIS, and integrated to identify the malaria hotspots. RESULTS: Out of 288 health subcentres, GIS identified 10 hot spots at extremely high risk of malaria and 14 hot spots at high risk of malaria. Malaria may flare up in these hot spots whenever favourable transmission conditions arise. Health authorities have been advised to establish control measures in these selected hot spots for timely prevention. CONCLUSION: There is a need for adequate monitoring and allocation of available resources for better interventions in the malaria hotspots. The GIS model used in this study can be used, even at village or cluster level, to pin point the malaria hot spots, and information can be updated and retrieved easily.
OBJECTIVE: To identify the malaria hot spots at health subcentre level in an endemic district using a geographical information system (GIS). The results will be useful for rapid retrieval of malaria information, and to prioritize malaria control efforts in identified hot spots. STUDY DESIGN: Extraction, analysis and synthesis of relevant data. METHODS:Malaria epidemiological data from 2006 to 2009 were analysed to determine the annual parasitic index, slide positivity rate, annual blood examination rate and Plasmodium falciparum percentage for each health subcentre in the district. Maps were produced using GIS, and integrated to identify the malaria hotspots. RESULTS: Out of 288 health subcentres, GIS identified 10 hot spots at extremely high risk of malaria and 14 hot spots at high risk of malaria. Malaria may flare up in these hot spots whenever favourable transmission conditions arise. Health authorities have been advised to establish control measures in these selected hot spots for timely prevention. CONCLUSION: There is a need for adequate monitoring and allocation of available resources for better interventions in the malaria hotspots. The GIS model used in this study can be used, even at village or cluster level, to pin point the malaria hot spots, and information can be updated and retrieved easily.