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Satellite imagery in the study and forecast of malaria

Nature volume 415, pages 710–715 (2002)Cite this article

Abstract

More than 30 years ago, human beings looked back from the Moon to see the magnificent spectacle of Earth-rise. The technology that put us into space has since been used to assess the damage we are doing to our natural environment and is now being harnessed to monitor and predict diseases through space and time. Satellite sensor data promise the development of early-warning systems for diseases such as malaria, which kills between 1 and 2 million people each year.

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Figure 1: Hypothetical relationship between the challenge to a host population by a vector-borne pathogen and the risk of the host becoming infected.
Figure 2: Distributions of five mosquito species in the Anopheles gambiae complex in Africa, predicted from temporal Fourier-processed satellite data (Box 1) and elevation (global coverage provided by the digital elevation model GTOPO30; http://edcdaac.usgs.gov/gtopo30/README.html) at a spatial resolution of 0.05°.
Figure 3: Satellite-derived predictions of entomological inoculation rate (EIR) in Africa.
Figure 4: Amplitude of Fourier harmonics derived from windowed Fourier analysis of malaria cases per month and a range of climatic variables for the period January 1966 to December 1998.

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Acknowledgements

S.E.R. is currently supported by a NERC Senior Research Fellowship. R.W.S. is supported as a Senior Research Fellow by the Wellcome Trust. S.I.H. is currently supported as an Advanced Training Fellow by the Wellcome Trust. We thank M. Coetzee for supplying geo-referenced observations on the African distribution of the A. gambiae complex and D. Shanks for providing malaria incidence and meteorological data from the Brooke Bond Kericho Tea Estate.

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Authors and Affiliations

  1. Department of Zoology, TALA Research Group, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK

    David J. Rogers & Simon I. Hay

  2. Department of Zoology, Oxford Tick Research Group, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK

    Sarah E. Randolph

  3. Kenya Medical Research Institute/Wellcome Trust Collaborative Programme, PO Box 43640, Nairobi, Kenya

    Robert W. Snow & Simon I. Hay

  4. Centre for Tropical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK

    Robert W. Snow

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  1. David J. Rogers
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Correspondence to David J. Rogers.

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Rogers, D., Randolph, S., Snow, R. et al. Satellite imagery in the study and forecast of malaria. Nature 415, 710–715 (2002). https://doi.org/10.1038/415710a

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