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Designing agricultural landscapes to limit zoonotic disease risk in The Gambia

Often decisions about agricultural development are taken with a unilateral aim of boosting financial or food security. There are often downstream, unintentional consequences such as increasing disease burden from disturbed, anthropogenic landscapes. Without taking such impacts into account poverty reduction interventions will be less effective. There is increasing evidence that healthy landscapes can benefit people, while still producing resources, and here we will look to create tools to enable such win-win scenarios.

The project addresses general patterns of risk rather than focussing on single disease systems. Unlike many previous approaches we will work in a multi-disease, multi-host framework where we look to capture a broader understanding of how different pathogens respond to contact rates across an agricultural gradient to inform policy and decision makers in a more holistic way.

The student will gain interdisciplinary skills including data science, machine learning, data visualisation, social science, counter-factual scenario modelling, interacting with stakeholders and end-users. There will be two principal focus areas: The student will use sequence and social science data to model how landscape factors drive spill-over risk. This will be undertaken in a quantitative framework and use methods such as network analysis and phylogeographic inference. Second, the student will work with end-users to design visualisation tools for non-experts, to both gain feedback on the modelling process but also to create end-products to allow environmental solutions to zoonotic risk to be implemented while balancing financial and food security.

This work takes a trans-disciplinary approach that incorporates ecological, epidemiological modelling and social science to develop real world solutions alongside stakeholders who are committed to integrating such data and modelling into their decision-making framework.

The student will be based primarily in the UK, with occasional short visits to work with the research team and external stakeholders in The Gambia.

Type
PhD position
Institution
LSHTM
City
London
Country
UK
Closing date
May 1st, 2023
Posted on
April 17th, 2023 15:06
Last updated
April 17th, 2023 15:08
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