This PhD opportunity is being offered as part of the LSTM and Lancaster University Doctoral Training Partnership. Find out more about the studentships and how to apply.
| Abstract | Gambian human African trypanosomiasis (gHAT), commonly called sleeping sickness, is a neglected tropical disease caused by Trypanosoma brucei gambiense transmitted by tsetse flies (Glossina). The World Health Organisation aims to eliminate Gambian sleeping sickness by 2030. Towards this goal, six countries have eliminated gHAT as a public health problem and in 2025 two countries declared elimination of gHAT. Efforts to eliminate the disease rely on medical screening, treatment of human populations and control of tsetse flies. One of the most successful interventions to control tsetse flies is the deployment of Tiny Targets (artificial insecticide-treated baits). Theoretical and empirical evidence shows that Tiny Targets can reduce tsetse populations by >60% and consequently interrupting sleeping sickness transmission. As the elimination goals are achieved in countries such as Uganda and Cote d’Ivoire, the deployment of Tiny Targets and active screening is curtailed to be replaced by passive screening and monitoring of tsetse populations. In countries where gHAT persists (e.g., DRC, Congo, Angola, South Sudan), active entomological monitoring is essential for assessing the impact of vector control operations and identifying unknown hotspots of transmission. Deployment of traps is largely based on the expertise and experience of the control entomologists and ‘convenience’. On the one hand, this can lead to neglect of places which are inconvenient or where there is no prior knowledge that tsetse flies are present. On the other hand, there may be excessive deployment of traps in places which are convenient and/or where tsetse and gHAT was known to present, therefore reducing the cost effectiveness of the surveillance design. A more cost-effective strategy is suggested by work with monitoring of mosquito populations within an entomological adaptive surveillance design. Trials in Mozambique and Ghana have shown that adaptive surveillance resulted in better produced data quality and flexibility in relation to program decision thresholds, enabling programs to respond to emerging needs while maintaining operational feasibility. Integrating active and passive designs in adaptive frameworks can enhance surveillance efficiency by improving accuracy in the analyses of tsetse data, reducing site numbers, or accelerating detection of ecological changes. The key to effective entomological surveillance is not rigidly achieving a target, but continuously adapting toward it. Flexible surveillance and control frameworks need to account for the complexity of the disease and vector dynamics. In fact, in addition to the impact of vector control, the distribution and abundance of tsetse populations is also affected by anthropogenic changes in climate and landcover. Hence, historical foci of gHAT transmission may disappear and new foci emerge. Given the provided context, this project will: 1) estimate fluctuations in tsetse habitats based on historical and most recent tsetse and interventions data, and using remotely-sensed information to characterise anthropogenic changes; 2) develop surveillance systems that can effectively detect the emergence and disappearance of tsetse foci; and 3) assess the potential impacts of adaptive surveillance and control systems on the operational structure of national programmes. This project will leverage extensive data from North West Uganda where surveillance of tsetse flies and deployment of Tiny Targets is well documented with almost 15 years of historical data. The project will produce dynamic maps of suitable tsetse habitats over time and under different environmental (including climate) change conditions and in presence/absence of interventions. It will also result in a better framework for the deployment of active surveillance and screening of tsetse flies and trypanosomiasis, with a direct impact on the health of the most sleeping-sickness afflicted communities. |
| Where does this project lie in the translational pathway? | T2 - Human /Clinical Research,T3 - Evidence into Practice |
| Methodological Aspects | Analysis of field station and remotely sensed data; Bayesian Geostatistical analyses of tsetse distribution and abundance Power analysis integrated to optimisation of spatial and spatio-temporal surveillance designs Scenario-based modelling Scoping review or metanalysis of tsetse surveillance specific literature. |
| Expected Outputs | We expect that this PhD will result in at least two published papers concerning tsetse and their habitat surveillance and implications for trypanosomiasis control. The PhD will develop methods and guidance to aid national programmes implementing plans to eliminate sleeping sickness. The project will contribute an evidence-base for future funding to develop and validate, through field study, a tool set for up-to-date mapping of trypanosomiasis risk. |
| Training Opportunities | Geostatistics Computational and mathematical modelling QGIS, R language, Google Earth Engine Systematic review Handling large remote sensed datasets |
| Skills Required | Graduate degree in biology, ecology or statistics Interest in vector biology and control Some experience in statistics and language coding (Python, R etc…). |
| Subject Areas | Neglected Tropical Diseases: Targeting Tsetse |
| Key Publications associated with this project |
Jalilian, A., Mateu, J., and Sedda, L. (2024). A brief review and guidance on the spatiotemporal sampling designs for disease vector surveillance. Current Research in Parasitology & Vector-Borne Diseases: 100208, https://doi.org/10.1016/j.crpvbd.2024.100208 Monteiro, G. M., Djogbénou, L. S., Donnelly, M. J., and Sedda, L. (2024). Development and deployment of an improved Anopheles gambiae s.l. field surveillance by adaptive spatial sampling design. Front. Ecol. Evol., 11:1241617. https://doi.org/10.3389/fevo.2023.1241617 Longbottom J, Esterhuizen J, Hope A, Lehane MJ, Mangwiro TC, Mugenyi A, et al. Impact of a national tsetse control programme to eliminate Gambian sleeping sickness in Uganda: a spatiotemporal modelling study. BMJ Global Health. 2024;9:e015374. https://doi.org/10.1136/bmjgh-2024-015374 Lord JS, Hargrove JW, Torr SJ, Vale GA (2018) Climate change and African trypanosomiasis vector populations in Zimbabwe's Zambezi Valley: A mathematical modelling study. PLOS Medicine 15(10): e1002675. https://doi.org/10.1371/journal.pmed.1002675 Longbottom J, Caminade C, Gibson HS, Weiss DJ, Torr S, Lord JS. Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe. Parasit Vectors. 2020 Oct 19;13(1):526. doi: 10.1186/s13071-020-04398-3. PMID: 33076987; PMCID: PMC7574501. |