Spatial distribution of Tsetse (Diptera: Glossinidae) within the Trypanosoma brucei rhodesiense focus of Uganda.

One of the greatest problems for sub-Saharan Africa is shortage of epidemiological data to support planning for provision of adequate public and animal health services. The overriding challenge is to provide the necessary resources to facilitate the process of regular data collection in support of disease surveillance and vector monitoring across target regions. Due to such circumstances, there is currently an increasing interest towards devising cheaper but yet significantly reliable means for availing the needed epidemiological and vector data for planning purpose. This study comes as a contribution towards solving such challenges. The study has three research components starting with a review of past Uganda national tsetse and trypanosomiasis control efforts as a means towards appreciating the dynamics of controlling the vector and disease. This is an analysis of what was applied, what worked, what didn't, and why it didn’t as linked to the broader vector and disease control system. Secondly through the use of remote sensing, geographical information systems and global positioning technologies tsetse species were sampled within Lake Victoria Basin. Only two species of tsetse were trapped, G. f. fG. f. fuscipes which was widely distributed across the surveyed area, and G. Pallidipes which was detected in a few isolated locations close to the border with Kenya in Eastern Uganda. The analysis of land cover with tsetse findings showed an important association between G. f. fuscipes and particular vegetation mosaics. Unfortunately, while the results are highly informative, approaches for data collection such as this one are costly and unlikely to be sustained by the already over-burdened health systems in the low developed countries of Africa. The third and main part of this study investigates, demonstrates and delivers the possibilities of applying spatial epidemiological modelling techniques to produce both tsetse distribution and abundance maps. Four spatial and non-spatial regression models (Logistic, Autologistic, Negative binomial and Auto-negative binomial), were constructed and used to predict tsetse fly presence and tsetse fly abundance for the study area. The product is an improved understanding of association between environmental variables and tsetse fly distribution/abundance and maps providing continuous representations of the probability of tsetse occurrence and predicted tsetse abundance across the study area. The results indicate that tsetse presence and abundance are influenced differently. Tsetse abundance is highly determined by river systems while tsetse presence is majorly influenced by forested landscapes. Therefore, efforts to control trypanosomiasis through vector control in the Lake Victoria basin will call for delineation of such clearly identified high tsetse accumulation zones for targeted tsetse control operations. This will ensure optimum utilization of the scarce resources and above all contribute to the protection of humans and animals against trypanosomiasis infection