Recent study: Quantifying geographic accessibility to improve efficiency of entomological monitoring
One of LSTM’s tsetse group PhD students, Joshua Longbottom, is first author on a paper describing a new method of estimating the best locations to sample for tsetse flies (or other insect vectors) by combining a surface predicting travel time, similar to GoogleMaps, with abundance estimates of flies.
The study, published in PLOS NTD in March, is based on an approach using GPS data and satellite imagery to predict how long it takes to travel in remote areas of Uganda where Gambian human African trypanosomiasis (gHAT), a neglected tropical disease (NTD) also known as sleeping sickness, persists. The work identifies efficient places to sample for tsetse flies, the vector of the disease, as part of an ongoing vector control programme using Tiny Targets to contribute to the effort to eliminate gHAT in north-western Uganda.
The approach was primarily developed to streamline the method for monitoring vector control programme impact. In the Tiny Target programme, impact is assessed by repeatedly measuring the abundance of tsetse within intervention areas, using monitoring traps, to see if abundance declines over the period of the programme. Longitudinal monitoring can be expensive, especially in the later stages of a successful program where numbers of tsetse and sleeping sickness cases are low, as more rigorous sampling is required to detect remaining flies. The authors, consisting of a team based at LSTM, aimed to pre-determine the most efficient locations in which to place tsetse traps to monitor abundance. This involved the identification of sites that are easy to reach and produce rich information on vector abundance before the control programme was initiated. The authors state that pre-determining where best to place sentinel monitoring sites may help to reduce costs associated with fuel and staff salaries, components which contribute toward the 10.6% of tsetse control programme budgets allocated toward tsetse monitoring.
Within the study, Mr Longbottom and others used image classification and cost-distance algorithms to produce estimates of accessibility within Koboko district, Uganda, where Tiny Targets are currently being used to contribute to efforts to eliminate sleeping sickness. The method described may be adapted for use in the planning and monitoring of tsetse- and other vector-control programmes. By providing methods to ensure that vector control programmes operate at maximum efficiency, the authors hope that they can ensure the limited funding associated with some vector borne NTDs has the largest impact.
Joshua Longbottom said “Previous approaches used to identify where best to place sentinel monitoring sites for tsetse were generally based on an ad-hoc approach which required local knowledge of geographic accessibility and intuition. Whilst this approach has worked within Uganda, there was a need to refine the methodology so that we could ensure that the process was efficient and could be applied to new areas as and when control programmes start/expand”.
LSTM researchers and the Co-ordinating Office for the Control of Trypanosomiasis in Uganda (COCTU) have been deploying Tiny Targets within north-Western Uganda since 2011 as part of an integrated effort with screening and treatment. The number of cases has reduced from 948 cases in 2000, to only two in 2019, with Uganda on track for reaching the World Health Organisation’s target of elimination of HAT by 2020.
Longbottom J, Krause A, Torr SJ, Stanton MC (2020) Quantifying geographic accessibility to improve efficiency of entomological monitoring. PLoS Negl Trop Dis 14(3): e0008096. https://doi.org/10.1371/journal.pntd.0008096