Predicting Malaria Epidemics in the Kenyan Highlands Using Climate Data: A Tool for Decision Makers (original) (raw)

Abstract

While the underlying cause of malaria epidemics in the East African highlands remains a subject of debate, we argue that permissive climatic conditions in the normally cool highlands are required for the epidemics to occur. Analysis of climate data from East Africa suggested that, over the last decade, there has been an increase in the frequency and intensity of anomalies in the mean monthly maximum temperatures. We found an association between rainfall and unusually high maximum temperatures and the number of inpatient malaria cases 3–4 months later. A malaria epidemic prediction model was then constructed.

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References

  1. Kovats, R.S. El Niño and human health. Bulletin of the World Health Organization 2000; 78: 1127–1135.
    PubMed CAS Google Scholar
  2. Bouma M.J. and Dye C. Cycles of malaria associated with El Niño in Venezuela_. Journal of American Medical Association_ 1997; 278: 1772–1774.
    Article CAS Google Scholar
  3. El Niño and its health Impacts WHO Fact sheet No 192 www.reliefweb.int.
  4. Githeko A K., Lindsay S.W., Confalonieri U, and Patz J.A. Climate change and vector borne diseases:a regional analysis. Bulletin of the World Health Organization 2000; 78: 1136–1147.
    PubMed CAS Google Scholar
  5. Snow R.W., Gouws E., Omumbo J, Rapuoda B., Craig. H., Tanser F.C., le Sueur D., Ouma. Models to predict the intensity of Plasmodium falciparum transmission: applications to the burden of disease in Kenya. Transactions of the Royal Society of Tropical Medicine and Hygiene 1998; 92: 601–6.
    Article PubMed CAS Google Scholar
  6. Hay S.I., Snow R.W., Rogers D.J. Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Transactions of the Royal Society Tropical Medicine and Hygiene 1998; 92: 12–20.
    Article CAS Google Scholar
  7. Patz J.A., Strzepek K., Lele S., Hedden M., Greene S., Noden B., Hay S.I., Kalkstein L., Beier J.C. Predicting key malaria transmission factors, biting and entomological inoculation rates, using modeled soil moisture in Kenya. Tropical Medicine and International Health 1998; 3: 818–27.
    Article PubMed CAS Google Scholar
  8. Linthicum K.J., Anyamba A, Tucker C.J., Kelley P.W., Myers. F., Peters C.J. Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya_. Science_ 1999; 285: 397–400.
    Article PubMed CAS Google Scholar
  9. Garrett-Jones, C., and Shidrawi, G.R. Malaria vectorial capacity of a population of Anopheles gambiae: An exercise of epidemiological entomology. Bulletin of the World Health Organization 1969; 40: 531–545.
    PubMed CAS Google Scholar
  10. Garrett-Jones, C., Magayuka, S.A. Studies on the natural incidence of Plasmodium and Wuchereria infections in Anopheles in rural East Africa I-Assessment of densities by trapping hungry female Anopheles gambiae Giles species. World Health Organization (mimeographed document) 1975; WHO/AL /77:8 51, WHO/VBC/75:541.
  11. MacDonald G. The epidemiology and control of malaria. Oxford University Press 1957.
  12. Lindsay S.W, Birley. H. Climate change and mal ari a transmission. A nnals of Tropical Medicine and Parasitology 1996; 90: 573–88.
    CAS Google Scholar
  13. Githeko A.K., Service M.W., Mbogo C.M., Atieli F.K. Resting behaviour, ecology and genetics of malaria vectors in large-scale agricultural areas of Western Kenya. Parassitologia 1996; 38: 481–9.
    PubMed CAS Google Scholar
  14. Craig. H., Snow R.W., and le Sueur D. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Parasitology Today 1999; 15: 105–111.
    Article PubMed CAS Google Scholar
  15. The regional Impacts of Climate Change. An Assessment of Vulnerability. A Special Report of IPCC Working Group II Ed. Watson RT. Zinyowera MC. Moss RH. Dokken DJ. Cambridge University Press 1998.

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Authors and Affiliations

  1. Kenya Medical Research Institute, P. O. Box 1578, Kisumu, Kenya
    Andrew K. Githeko
  2. Kenya Meteorology Department, Kenya
    William Ndegwa

Authors

  1. Andrew K. Githeko
  2. William Ndegwa

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Githeko, A.K., Ndegwa, W. Predicting Malaria Epidemics in the Kenyan Highlands Using Climate Data: A Tool for Decision Makers.Global Change & Human Health 2, 54–63 (2001). https://doi.org/10.1023/A:1011943131643

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