Adaptive indicators for targeted treatment of parasitic disease in livestock and plants under climate change
Supervisors:
Prof Eric Morgan, Biological Science (Queen's University Belfast)
Prof Adam Kleckzkowski, Mathematics and Statistics, (University of Strathclyde)
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 the most efficient and effective monitoring strategies, using existing and new data sets from farms in the UK and Africa. Climate-driven predictions of parasite transmission potential will be added so that monitoring and action can be calibrated to epidemiological risks. The key output will be a smartphone app to provide this capability to farmers and advisors, with whom the app will be co-produced. 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 food security through simultaneous impacts on crops and animals.
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 that are in strong demand in research, NGO, public and private sectors. They will also join a team working on underpinning BBSRC-funded research on endemic coinfections under climate change (link below) and will work closely with industry stakeholders:
https://www.ukri.org/news/uk-invests-9-million-in-fight-against-endemic-livestock-disease/