Adaptive indicators for targeted treatment of parasitic disease in livestock and plants under climate change
Supervisors
Prof Eric Morgan, Queens University Belfast
Prof Adam Kleczkowski, Strathclyde University
Dr Didier Devaurs, Strathclyde University
Summary
Climate change and drug resistance are posing real issues for farmers, threatening animal welfare and the sustainability of livestock farming. The project will integrate real-time health information with predictive models of parasite transmission and deliver actionable advice on antiparasitic interventions.
The project will apply machine learning to identify the most informative health indicators and most efficient / effective monitoring strategies, using existing and new datasets from farms in the UK and Africa. Climate-driven predictions of parasite transmission potential will be added to help calibrate monitoring and action to epidemiological risks. The key output will be a smartphone app aimed at farmers and advisors, who will be involved as co-developers. The project will also explore the potential to align the app with comparable risk prediction tools for plant health, supporting farmers to deal with multiple threats to crops and animals, and thus food security.
The student will benefit from training in machine learning, app development, animal health and epidemiology. They will emerge with cutting-edge skills and experiences in digital health, which are in strong demand in academia, NGOs, public and private sectors. They will join a team working on underpinning BBSRC-funded research on endemic co-infections under climate change (https://www.ukri.org/news/uk-invests-9-million-in-fight-against-endemic-livestock-disease/) and will work closely with industry stakeholders.