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12 August 2010 Potential of using remote sensing for forecasting malaria in Tripura, India
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This study examined the relationship between environmental factors and malaria epidemic. The objective is to use NOAA environmental satellite data to produce weather seasonal forecasts as a proxy for predicting malaria epidemics in Tripura, India which has the one of the highest endemic of malaria cases in the country. An algorithm uses the Vegetation Health (VH) Indices (Vegetation Condition Index( VCI) and Temperature Condition Index (TCI)) computed from Advance Very High Resolution Radiometer (AVHRR) data flown on NOAA afternoon poler orbiting satellite.. A good correlation was found between malaria cases and TCI two months earlier than the malaria transmission period. Principal components regression (PCR) method was used to develop a model to predict malaria as a function of the TCI. The simulated results were compared with observed malaria statistics showing that the error of the estimates of malaria is small. Remote sensing therefore is a valuable tool for estimating malaria well in advance thus preventive measures can be taken.
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Mohammad Nizamuddin, Leonid Roytman, Mitch Goldberg, and Felix Kogan "Potential of using remote sensing for forecasting malaria in Tripura, India", Proc. SPIE 7809, Remote Sensing and Modeling of Ecosystems for Sustainability VII, 78090G (12 August 2010);

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