Cost effective malaria risk control using remote sensing and environmental data

Md. Z. Rahman; Leonid Roytman; Abdel Hamid Kadik

doi:10.1117/12.918814

4 May 2012 Cost effective malaria risk control using remote sensing and environmental data

Md. Z. Rahman, Leonid Roytman, Abdel Hamid Kadik

Proceedings Volume 8371, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX; 83711I (2012) https://doi.org/10.1117/12.918814
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Malaria transmission in many part of the world specifically in Bangladesh and southern African countries is unstable and epidemic. An estimate of over a million cases is reported annually. Malaria is heterogeneous, potentially due to variations in ecological settings, socio-economic status, land cover, and agricultural practices. Malaria control only relies on treatment and supply of bed networks. Drug resistance to these diseases is widespread. Vector control is minimal. Malaria control in those countries faces many formidable challenges such as inadequate accessibility to effective treatment, lack of trained manpower, inaccessibility of endemic areas, poverty, lack of education, poor health infrastructure and low health budgets. Health facilities for malaria management are limited, surveillance is inadequate, and vector control is insufficient. Control can only be successful if the right methods are used at the right time in the right place. This paper aims to improve malaria control by developing malaria risk maps and risk models using satellite remote sensing data by identifying, assessing, and mapping determinants of malaria associated with environmental, socio-economic, malaria control, and agricultural factors.

Citation Download Citation

Md. Z. Rahman, Leonid Roytman, and Abdel Hamid Kadik "Cost effective malaria risk control using remote sensing and environmental data", Proc. SPIE 8371, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX, 83711I (4 May 2012); https://doi.org/10.1117/12.918814

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KEYWORDS

Satellites

Remote sensing

Environmental sensing

Geographic information systems

Vegetation

Agriculture

Data modeling

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