Targeting Tsetse and Trypanosomiasis Control in East and Southern Africa amid Anthropogenic Change

In East and Southern Africa, tsetse flies transmit trypanosomes that cause Rhodesian human African trypanosomiasis (r-HAT), in addition to animal African trypanosomiasis (AAT). Although r-HAT is less common than the other, more chronic disease ¬- Gambian HAT, the presence of reservoir hosts including wildlife, as well as livestock, means that the causative Trypanosoma brucei rhodesiense cannot be eliminated. The disease is under-reported, with foci often associated with remote areas adjacent to national parks and game reserves and has the potential for sporadic epidemics due to changing socio-economic, ecological or environmental conditions.

Although the total area at risk of r-HAT may have reduced in size due to large-scale population growth and conversion of natural tsetse habitat to farm and cropland, the coincident increase in livestock, and pressure at the edges of protected areas, mean that many foci of disease persist and new foci may emerge.
With limited resources, community-based approaches in hotspots of transmission for both r-HAT and AAT may be more sustainable than ‘top-down’ interventions. However, existing tsetse maps used to potentially target such actuvities are now 20 years old and, in that time, human and livestock populations have increased; in Tanzania for example, human and cattle populations have almost doubled.

This project will:

1) re-estimate past and present tsetse habitats based on historical and recent remotely-sensed data and data available on tsetse distribution and abundance;

2) quantify how land use, and specifically tsetse habitat, has changed in Tanzania in the last 20 years with quantitative estimation of erosion and expansion of tsetse habitats and consequences for trypanosomiasis;

3) assess the potential impacts of habitat fragmentation on the occurrence and co-occurrence of savanna tsetse species Glossina pallidipesGlossina swynnertoni and Glossina morsitans through spatially-explicit computational models.

The project will produce national-level, contemporary maps of suitable tsetse habitat which could be used in targeting surveillance and control efforts. It will also result in a better understanding of tsetse population dynamics in fragmented habitats and the optimal options for control in these areas.

Where does the project lie on the Translational Pathway?

T1 (Basic Research) & T3 (Evidence into Practice)

Expected Outputs

We expect that this PhD will result in at least two papers concerning national-level mapping of suitable tsetse habitat in addition to smaller-scale effects of habitat fragmentation on tsetse and implications for control.

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, in collaboration with the Vector and Vector-borne Diseases Research Institute in Tanzania. This includes methods for informing the sampling design of tsetse surveillance and monitoring. Through close links with government researchers and policy makers in Tanzania we will provide maps to guide their national planning of r-HAT and AAT control.

Training Opportunities


Computational and mathematical modelling

QGIS, R, Google Earth Engine

Systematic review

Skills Required

Graduate degree in biology, ecology or statistics

Interest in vector biology and control

Interest in statistics and language coding (Python, R etc…).

Key Publications associated with this project

Lord J.S., Lea R.S., Allan F.K., Byamungu M., Hall D.R., Lingley J., Mramba F., Paxton E., Vale G.A., Hargrove J.W., Morrison L.J., Torr S.J. and Auty H.K (2020). Assessing the effect of insecticide-treated cattle on tsetse abundance and trypanosome transmission at the wildlife-livestock interface in Serengeti, Tanzania. PLOS Neglected Tropical Diseases.

Lord J.S., Hargrove J.W., Torr S.J. and Vale G.A. (2019) Climate change and African trypanosomiasis vector populations in Zimbabwe’s Zambezi Valley: a mathematical modelling study. PLoS Medicine. 15(10). e1002675.

Lord J.S., Torr S.J., Auty H.K., Brock P., Byamungu M., Hargrove J.W., Morrison L.J., Mramba F., Vale G.A. and Stanton M.C. (2017). Geostatistical models using remotely-sensed data predict savanna tsetse decline across the interface between protected and unprotected areas in Serengeti, Tanzania. Journal of Applied Ecology. 55; 1997-2007. DOI: 10.1111/1365-2664-13091

Auty H., Morrison L., Torr S., and Lord J.S. (2016). Transmission dynamics of Rhodesian sleeping sickness at the interface of wildlife and livestock areas. Trends in Parasitology. 32(8), pgs 608-621: doi: http//


Sedda, L., Guerrini, L., Bouyer, J., Kone, N. & Rogers, D. J. Spatio-temporal modelling of Glossina palpalis gambiensis and Glossina tachinoides apparent densities in fragmented ecosystems of Burkina Faso. Ecography 33, 772-783, doi:10.1111/j.1600-0587.2009.06135.x (2010).

Deadline: Thursday 11th February 2021; 12:00 noon GMT

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