Biogeographical patterns of African trypanosomoses for improved planning and implementation of field interventions

In this thesis the knowledge gaps and the requirements for an evidence-based decision making in the field of tsetse and trypanosomoses are identified, with a focus on georeferenced data and Geographic Information Systems (GIS). Datasets, tools and analyses are presented that aim to fill some of the identified knowledge gaps.

For the human form of the disease, also known as sleeping sickness, case detection and treatment are the mainstay of control, so that accurate knowledge of the geographic distribution of infections is paramount. In this study, an Atlas was developed that provides village-level information on the reported occurrence of sleeping sickness. The geodatabase underpinning the Atlas also includes the results of active screening activities, even when no cases were detected. The Atlas enables epidemiological maps to be generated at a range of scales, from local to global, thus providing evidence for strategic and technical decision making.

In the field of animal trypanosomosis control, also known as nagana, much emphasis has recently been placed on the vector. Accurate delineation of tsetse habitat appears as an essential component of ongoing and upcoming interventions against tsetse. The present study focused on land cover datasets and tsetse habitat. The suitability for tsetse of standardized land cover classes was explored at continental, regional and national level, using a combination of inductive and deductive approaches. The land cover classes most suitable for tsetse were identified and described, and tailored datasets were derived.

The suite of datasets, methodologies and tools presented in this thesis provides evidence for informed planning and implementation of interventions against African trypanosomoses at a range of spatial scales.