Analysing malaria incidence at the small area level for developing a spatial decision support system: a case study in Kalaburagi, Karnataka, India
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Notwithstanding long standing efforts to reduce the incidence of infectious diseases they continue to be a major cause of morbidity and premature death in many parts of the world. Part of the challenge is to understand better the factors that are associated with disease incidence at the local level and to put in place operational systems to achieve sustainable reduction. Spatial decision support systems have already proved their value in helping to reduce, in some cases eliminate, infectious diseases including malaria but to be effective in any particular part of the world they need to be designed to reflect local circumstances and local data availability over time. We report the first stage of a project to develop a spatial decision support system for infectious diseases for Karnataka State in India. The focus of this paper is on malaria incidence and we draw on small area data on new cases of malaria analysed in two-monthly time intervals over the period February 2012 to January 2016 for Kalaburagi taluk, a small area in Karnataka. We report the results of data mapping and cluster detection (identifying areas of excess risk) including evaluating the temporal persistence of excess risk and the local conditions with which high counts are statistically associated. We conclude by commenting on how this work might feed into a practical spatial decision support system useful to health practitioners tackling infectious diseases in Karnataka.
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1877-5853