Modelled impact of Tiny Targets on the distribution and abundance of riverine tsetse

Abstract

BackgroundThe insecticide-treated baits known as Tiny Targets are one of the cheapest means of controlling riverine species of tsetse flies, the vectors of the trypanosomes that cause sleeping sickness in humans. Models of the efficacy of these targets deployed near rivers are potentially useful in planning control campaigns and highlighting the principals involved. Methods and principal findingsWe produced a simple non-seasonal model of the births, deaths, mobility and aging of tsetse, and we programmed it to simulate the impact of seven years of target use against the tsetse, Glossina fuscipes fuscipes, in the riverine habitats of NW Uganda. The models outputs matched reality in showing that: (i) good control can be achieved despite the degradation of targets, (ii) local elimination of tsetse is impossible if invasion sources are not tackled, and (iii) with invasion and target degradation it is difficult to detect any effect of control on the age structure of the tsetse population. ConclusionsDespite its simplifications, the model can assist planning and teaching, but allowance should be made for any complications due to seasonality and management challenges associated with greater scale. Author summaryWe produced a simple model of the population dynamics of the riverine tsetse fly, Glossina fuscipes fuscipes, to simulate the field results of controlling this insect for seven years using Tiny Targets, i.e., artificial insecticide-treated baits, in NW Uganda. The model is potentially useful in planning tsetse control and illustrating the principles involved. Thus, it confirmed that targets can give good control, even if the targets degrade so much that they need replacement after six months. It showed that reinvasion can limit severely the efficacy of control campaigns and mask the changes in the age structure of the population. We stress the need to consider the possibility of seasonal complications and problems of managing large scale operations.