title: The ecology of malaria--as seen from Earth-observation satellites.
abstract: Data from sensors on board geostationary and polar-orbiting, meteorological satellites (Meteosat and NOAA series) are routinely obtained free, via local reception systems, in an increasing number of African countries. Data collected by these satellites are processed to produce proxy ecological variables which have been extensively investigated for monitoring changes in the distribution and condition of different natural resources, including rainfall and vegetation state. How these data products (once incorporated, along with other data, into a geographical information system) could contribute to the goals of monitoring patterns of malaria transmission, predicting epidemics and planning control strategies is the subject of the present review. By way of illustration, an analysis of two of these products, normalized difference vegetation index (NVDI) and cold-cloud duration (CCD), is given in conjunction with epidemiological and entomological data from The Gambia, a country where extensive studies on malaria transmission have been undertaken in recent years. Preliminary results indicate that even simple analysis of proxy ecological variables derived from satellite data can indicate variation in environmental factors affecting malaria-transmission indices. However, it is important to note that the associations observed will vary depending on the local ecology, season and species of vector. Whilst further quantitative research is required to validate the relationship between satellite-data products and malaria-transmission indices, this approach offers a means by which detailed knowledge of the underlying spatial and temporal variation in the environment can be incorporated into a decision-support system for malaria control.
authors: Liverpool School of Tropical Medicine, U.K.
authors: M C
authors: MC
authors: Thomson
authors: S J
authors: SJ
authors: Connor
authors: P J
authors: PJ
authors: Milligan
authors: S P
authors: SP
authors: Flasse
mesh_terms: D000349:Africa / Q000453:epidemiology; D000818:Animals; D000852:Anopheles; D004463:Ecology; D005544:Forecasting; D005714:Gambia / Q000453:epidemiology; D006801:Humans; D008288:Malaria / Q000453:epidemiology / Q000635:transmission*; D008685:Meteorological Concepts; D010507:Periodicity; D011157:Population Dynamics; D017215:Satellite Communications; D012621:Seasons; D019371:Topography, Medical