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Satellite imagery in the study and forecast of malaria

Author

Listed:
  • David J. Rogers

    (TALA Research Group, University of Oxford)

  • Sarah E. Randolph

    (Oxford Tick Research Group, University of Oxford)

  • Robert W. Snow

    (Kenya Medical Research Institute/Wellcome Trust Collaborative Programme
    Centre for Tropical Medicine, University of Oxford, John Radcliffe Hospital)

  • Simon I. Hay

    (TALA Research Group, University of Oxford
    Kenya Medical Research Institute/Wellcome Trust Collaborative Programme)

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.

Suggested Citation

  • David J. Rogers & Sarah E. Randolph & Robert W. Snow & Simon I. Hay, 2002. "Satellite imagery in the study and forecast of malaria," Nature, Nature, vol. 415(6872), pages 710-715, February.
    • Handle: RePEc:nat:nature:v:415:y:2002:i:6872:d:10.1038_415710a
    DOI: 10.1038/415710a
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    Cited by:

    1. Daniel C Medina & Sally E Findley & Boubacar Guindo & Seydou Doumbia, 2007. "Forecasting Non-Stationary Diarrhea, Acute Respiratory Infection, and Malaria Time-Series in Niono, Mali," PLOS ONE, Public Library of Science, vol. 2(11), pages 1-13, November.
    2. Monika Punia & Suman Nain & Amit Kumar & Bhupendra Singh & Amit Prakash & Krishan Kumar & V. Jain, 2015. "Analysis of temperature variability over north-west part of India for the period 1970–2000," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(1), pages 935-952, January.
    3. Cord, Anna F. & Klein, Doris & Mora, Franz & Dech, Stefan, 2014. "Comparing the suitability of classified land cover data and remote sensing variables for modeling distribution patterns of plants," Ecological Modelling, Elsevier, vol. 272(C), pages 129-140.
    4. Luong Thi Nguyen & Huy Xuan Le & Dong Thanh Nguyen & Ha Quang Ho & Ting-Wu Chuang, 2020. "Impact of Climate Variability and Abundance of Mosquitoes on Dengue Transmission in Central Vietnam," IJERPH, MDPI, vol. 17(7), pages 1-16, April.
    5. Nicholas A S Hamm & Ricardo J Soares Magalhães & Archie C A Clements, 2015. "Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(12), pages 1-24, December.
    6. Chathurika Hettiarachchige & Stefan von Cavallar & Timothy Lynar & Roslyn I Hickson & Manoj Gambhir, 2018. "Risk prediction system for dengue transmission based on high resolution weather data," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    7. Bradley, Bethany A. & Olsson, Aaryn D. & Wang, Ophelia & Dickson, Brett G. & Pelech, Lori & Sesnie, Steven E. & Zachmann, Luke J., 2012. "Species detection vs. habitat suitability: Are we biasing habitat suitability models with remotely sensed data?," Ecological Modelling, Elsevier, vol. 244(C), pages 57-64.
    8. Zhoupeng Ren & Duoquan Wang & Jimee Hwang & Adam Bennett & Hugh J W Sturrock & Aimin Ma & Jixia Huang & Zhigui Xia & Xinyu Feng & Jinfeng Wang, 2015. "Spatial-Temporal Variation and Primary Ecological Drivers of Anopheles sinensis Human Biting Rates in Malaria Epidemic-Prone Regions of China," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-17, January.
    9. Paulina Phoobane & Muthoni Masinde & Tafadzwanashe Mabhaudhi, 2022. "Predicting Infectious Diseases: A Bibliometric Review on Africa," IJERPH, MDPI, vol. 19(3), pages 1-20, February.
    10. Gilioli, G. & Groppi, M. & Vesperoni, M.P. & Baumgärtner, J. & Gutierrez, A.P., 2009. "An epidemiological model of East Coast Fever in African livestock," Ecological Modelling, Elsevier, vol. 220(13), pages 1652-1662.
    11. Jörn P W Scharlemann & David Benz & Simon I Hay & Bethan V Purse & Andrew J Tatem & G R William Wint & David J Rogers, 2008. "Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-13, January.
    12. Xavier Rodó & Mercedes Pascual & Francisco Doblas-Reyes & Alexander Gershunov & Dáithí Stone & Filippo Giorgi & Peter Hudson & James Kinter & Miquel-Àngel Rodríguez-Arias & Nils Stenseth & David Alons, 2013. "Climate change and infectious diseases: Can we meet the needs for better prediction?," Climatic Change, Springer, vol. 118(3), pages 625-640, June.
    13. Ting-Wu Chuang & Michael C Wimberly, 2012. "Remote Sensing of Climatic Anomalies and West Nile Virus Incidence in the Northern Great Plains of the United States," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-10, October.

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