An example of decision support for trypanosomiasis control using a geographical information system in eastern Zambia.

Abstract

In many African countries where both Government resources and donor aid for the control of tsetse-transmitted trypanosomiasis are declining, there is an increasing need to identify areas where intervention is most likely to be technically, economically, socially and environmentally sustainable. Activities then can be focused so that the maximum benefits are obtained from limited resources. We describe a decision-support framework based on a geographical information system to identify areas of high priority for the control of tsetse and trypanosomiasis in the common fly belt of eastern Zambia. Digital coverages were generated for six environmental variables: (1) cattle density, (2) human density, (3) land designation, (4) relative arable potential, (5) crop-use intensity and (6) proximity to existing control operations. The distribution of tsetse in the area was predicted using a multivariate (maximum likelihood) analysis of areas of known presence and absence and a series of environmental data. Experienced Zambian veterinarians and biologists working in the region established criteria weights for the input variables and the data were integrated in a geographical information system (GIS), using weighted linear combinations to prioritize areas for trypanosomiasis control. The results of this exercise and estimates of the errors involved are discussed.