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Proceedings Paper

Environmental data analysis and remote sensing for early detection of dengue and malaria
Author(s): Md Z. Rahman; Leonid Roytman; Abdelhamid Kadik; Dilara A. Rosy
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Paper Abstract

Malaria and dengue fever are the two most common mosquito-transmitted diseases, leading to millions of serious illnesses and deaths each year. Because the mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper we propose the development of an operational geospatial system for malaria and dengue fever early warning; this can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available ground-based epidemiological and vector ecology data, and current satellite remote sensing capabilities.
We use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4-km resolution as one predictor of malaria and dengue fever risk in Bangladesh. As a study area, we focus on Bangladesh where malaria and dengue fever are serious public health threats. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A malaria and dengue fever early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks.

Paper Details

Date Published: 5 June 2014
PDF: 9 pages
Proc. SPIE 9112, Sensing Technologies for Global Health, Military Medicine, and Environmental Monitoring IV, 91121C (5 June 2014); doi: 10.1117/12.2050587
Show Author Affiliations
Md Z. Rahman, LaGuardia Community College (United States)
Leonid Roytman, The City College of New York (United States)
Abdelhamid Kadik, LaGuardia Community College (United States)
Dilara A. Rosy, Univ. of Dhaka (Bangladesh)

Published in SPIE Proceedings Vol. 9112:
Sensing Technologies for Global Health, Military Medicine, and Environmental Monitoring IV
Šárka O. Southern; Mark A. Mentzer; Isaac Rodriguez-Chavez; Virginia E. Wotring, Editor(s)

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