Linking of epidemiological and economic models to optimise disease control when resources are limited

Supervisor: Professor C.A. Gilligan in collaboration with Professor R.E. Rowthorn, Dept Economics, Cambridge, Dr R. Laxminaryan, Resources for the Future, Washington D.C., Dr D.L. Smith, Fogarty International Center, National Institute of Health.
Project outline:
Wheat powdery mildew (upper view) has recently shown rapid increase in fungicide resistant isolates analogous to antibiotic resistance in human and animal populations. Soybean rust (lower view) is an example of an emerging disease that is spreading rapidly at local and continental scales This project will address problems that target plant, animal and human diseases
Many epidemics outstrip the resources available to treat all infected sites, especially when disease occurs simultaneously in different but inter-connected regions. This poses a dilemma for epidemiologists and administrators of how best to deploy limited resources amongst different regions: should preference be given to treating infected sites in regions with high or with low levels of infection, or to equalising levels of infection in different regions as fast as possible? Other problems arise in balancing the widespread demand for new pesticides or resistant varieties with strategies to minimise the risk of breakdown of control as pathogens become resistant to pesticides or acquire virulence, enabling them to infect resistant hosts. Choosing between these options requires a combination of epidemiological and economic insight that hitherto have tended to remain separate: epidemiological models take little account of economic constraints, while economic models mostly ignore the spatial and temporal dynamics of disease.

Bridging the gap between epidemiological and economic theory is at the forefront of modern epidemiology. This studentship is designed to introduce students to this new field that combines optimal control methods from economic theory, together with epidemiological theory for the invasion, persistence and variability of disease. Initial work will focus on the control of disease in metapopulations with and without quarantine. The studentship would suit students with a strong background in mathematics or physics. The student will join a team of experimenters and theoreticians with close links with mathematical economists and will have the opportunity to test theories using data for large-scale control of disease.