Volume 74, Issue 1
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645


Epidemiologic data of malaria cases were correlated with satellite-based vegetation health (VH) indices to investigate if they can be used as proxy for monitoring malaria epidemics in Bangladesh. The VH indices were represented by the vegetation condition index (VCI) and the temperature condition index (TCI). The VCI and TCI estimate moisture and thermal conditions, respectively. Sensitivity of VCI and TCI was assessed using correlation and regression analysis. During cooler months (November–March) when mosquitoes are less active, the correlation was low. It increased considerably during the warm and wet season (April–October), reaching 0.7 for the TCI in early October and −0.66 for the VCI in mid September.


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  1. Githeko A, Lindsay S, Confalonieri U, Patz J, 2000. Climate change and vector-borne diseases: a regional analysis. Bull World Health Organ 78 : 200–207.
    [Google Scholar]
  2. Boëte C, Koella J, 2002. A theoretical approach to predicting the success of genetic manipulation of malaria mosquitoes in malaria control. Malaria J 1 : 3.
    [Google Scholar]
  3. Elias M, Rahman M, 1987. The ecology of malaria carrying mosquito Anopheles and its relation to malaria in Bangladesh. Bangladesh Med Res Counc Bull 13 : 15–28.
    [Google Scholar]
  4. Smith D, McKenzie E, 2004. Statics and dynamics of malaria infection in Anopheles mosquitoes. Malaria J 3 : 13.
    [Google Scholar]
  5. Rosenberg R, Maheswary N, 1982. Forest malaria in Bangladesh, I. Parasitology. Am J Trop Med Hyg 31 : 175–191.
    [Google Scholar]
  6. Nagpal B, Sharma V, 1995. Indian Anophelines. New Delhi: Baba Barkha Nath Printers, 416–423.
  7. Faiz MA, Yunus EB, Rahman MR, Hossain MA, Pang LW, Rahman ME, Bhuiya SN, 2001. Failure of national guidelines to diagnose uncomplicated malaria in Bangladesh. Am J Trop Med Hyg 67 : 396–399.
    [Google Scholar]
  8. Kidwell KB, 1997. Global Vegetation Index User’s Guide. Technical Report, NOAA. Suitland, MD: U.S. Department of Commerce, 30–45
  9. Kogan F, 2001. Operational space technology for global vegetation assessment. Bull Am Meteorol Soc 82 : 1949–1964.
    [Google Scholar]
  10. Rogers D, Hay S, Packer M, 1996. Predicting the distribution of tsetse flies in west Africa using temporal Fourier processed meteorological satellite data. Ann Trop Med Parasitol 90 : 225–241.
    [Google Scholar]
  11. Hay S, Snow R, Rogers D, 1998. Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Trans R Soc Trop Med Hyg 92 : 12–20.
    [Google Scholar]
  12. Thomson M, Connor S, 2001. The development of malaria early warning systems for Africa. Trends Parasitol 17 : 438–445.
    [Google Scholar]

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  • Received : 01 Aug 2004
  • Accepted : 07 May 2005
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