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Proceedings Paper

Satellite-observed sensitivity of weather condition for predicting malaria vector distribution in Bandarban district, Bangladesh
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Paper Abstract

A better understanding of the relationship between malaria epidemics, satellite data and the climatic anomalies could help mitigate the world-wide increase in incidence of the mosquitotransmitted diseases. This paper analyzes correlation between malaria cases and vegetation health (VH) Indices (Vegetation Condition Index (VCI) and Temperature Condition Index (TCI)) computed for each week over a period of 14 years (1992-2005). Following the results of correlation analysis the principal components regression (PCR) method was performed on weather components (TCI, VCI) of satellite data and climate variability during each of the two annual malaria seasons to construct a model to predict malaria as a function of the VH. A statistically significant relation was found between malaria cases and TCI during the month of June-July and September-October. Furthermore the simulated results found from PCR model were compared with observed malaria statistics showing that the error of the estimates of malaria is 5%.

Paper Details

Date Published: 30 April 2009
PDF: 7 pages
Proc. SPIE 7312, Advanced Environmental, Chemical, and Biological Sensing Technologies VI, 73120T (30 April 2009); doi: 10.1117/12.818316
Show Author Affiliations
Mohammad Nizamuddin, City College, CUNY (United States)
Atiqur Rahman, City College, CUNY (United States)
Leonid Roytman, City College, CUNY (United States)
Felix Kogan, National Oceanic and Atmospheric Administration (United States)
Al Powell, National Oceanic and Atmospheric Administration (United States)
Mitch Goldberg, National Oceanic and Atmospheric Administration (United States)


Published in SPIE Proceedings Vol. 7312:
Advanced Environmental, Chemical, and Biological Sensing Technologies VI
Tuan Vo-Dinh; Robert A. Lieberman; Günter Gauglitz, Editor(s)

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