Tsetse flies transmit Trypanosoma species which cause sleeping sickness (Human African trypanosomiasis).  The WHO aims to eliminate HAT as a public health problem by 2020 and interrupt all transmission by 2030.  Control of tsetse vectors is an increasingly important part of the global effort against sleeping sickness. 

LSTM scientists, working with partners from Africa and Europe, developed ‘Tiny Targets’, insecticide-treated panels of cloth which are used to attract and kill tsetse.   Tiny Targets are being used to control tsetse in DRC, Chad, Guinea, Cote d’Ivoire and Uganda under the auspices of the Tryp-Elim and Trypa-NO! programmes. 

Planning and monitoring the impact of tsetse control programmes relies on networks of traps to quantify spatial and temporal changes in tsetse populations.  Monitoring is expensive and the relatively low numbers of tsetse caught (<1 tsetse/trap/day) even before the deployment of targets limit the information.  This project will develop and test genomic-based methods to analyse the genetics of tsetse populations before and after vector control programmes

The project will use whole-genome sequencing (WGS) data to calculate effective population size from pre- and post-intervention collections of tsetse, thus providing an estimate of the effectiveness of control methods. These data will also be used to apply methods that calculate historic population size based on WGS data to investigate past population dynamics. This will provide a better understanding of the history of tsetse populations in intervention areas, while also providing signals of the effectiveness of interventions.  The results will contribute directly to development and application of novel methods to monitor the impact of vector control programmes carried out by the Trypa-NO! and Tryp-Elim partnerships.

Where does the project lie on the Translational Pathway?

T3 – Evidence into Practice

Expected Outputs

Previous PhD students working with the Torr and Donnelly groups have produced 3-4 papers and have subsequently gone on to take up post-doctoral positions at LSTM or other universities.  We expect that the findings from this PhD could contribute to new methods for monitoring the impact of tsetse control programmes.

Training Opportunities

• Genomics
• Field entomology
• Machine learning
• Geostatistics