Professor Chris Gilligan
Find out more about Chris Gilligan and his Group or email Chris.Gilligan@plantsci.cam.ac.uk
Project titles:
- Disease spread and control on networks
- Linking of epidemiological and economic models to optimise disease control when resources are limited
Project Title: Disease spread and control on networks
Supervisor: Professor C.A. Gilligan
Project outline:
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One of the main goals of epidemiological modelling is to provide guidelines for controlling disease outbreaks. This is challenging, because it must deal with the cryptic spread of disease through a heterogeneous landscape. It is also urgent because of the increasing risks of new disease problems associated with changing trade patterns and climate change. This studentship is designed to test some methods for the control of a range of diseases that differ in dispersal strategies. More specifically, the student will analyse the effectiveness of different control measures for a range of crop diseases that spread on networks with local, global, scale-free (Albert-Barabasi) and 'small-world' connectivity. The work will involve a combination of analytical and simulation techniques. Initial work will concentrate on setting up a spatially-extended model incorporating various dispersal kernels and different control measures. Some simple models will then be considered to the possibility of obtaining analytical solutions (mean-field models, reaction-diffusion models, percolation) that can subsequently be used to guide simulations. The studentship is therefore designed to provide training in epidemiological modelling and network theory from statistical physics together with a grounding in contemporary epidemiological problems. The student will join a large team of experimenters and theoreticians and will have the opportunity to test theories using extensive field data for disease of agricultural, horticultural and plantation crops.
References
- *Dybiec, B., Kleczkowski, A. and Gilligan, C. A. (2004) Controlling disease spread on networks with incomplete knowledge. Physical Review E 70:0066145-1-5
- **Keeling M, Brooks S.P, Gilligan C.A. (2004) Using conservation of pattern to approximate spatial parameters from a single snapshot. Proceedings of the National Academy of Science 101: 9155-9160.
- ***Stacey, A. J., Truscott, J. E., Asher, M.J.C. and Gilligan, C. A. (2004) A model for invasion and spread of rhizomania in the UK: implications for disease control strategies. Phytopathology 94: 209-215.
* Proof of concept copy available from CAG;
** shows how to interface with data;
***illustrates a practical problem.
See Research or email: Chris.Gilligan@plantsci.cam.ac.uk
Project Title: 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:
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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.
References
- Gilligan, C.A. (2003) Economics of transgenic crops and pest resistance: an epidemiological perspective pp. 221-243 in Economics of resistance R. Laxminaryan (ed.). Resources for The Future, Washington. (Available from CAG.)
- Hall, R. J., Gubbins, S. G. and Gilligan, C. A. (2004) Invasion of drug and pesticide resistance is determined by a trade-off between biocide efficacy and relative fitness. Bulletin of Mathematical Biology 66: 835-840.
- Park, A. Gubbins, S. and Gilligan, C.A. (2002) Extinction times for spatially-structured closed epidemics. Ecology Letters 5: 747-755.
- Smith, D. L., Levin, S., and Laxminarayan, R., (2005), Strategic interactions in multi-institutional epidemics of antibiotic resistance, Proc. Nat. Acad. Sci. 102:3153 - 3158.
See Research or email: Chris.Gilligan@plantsci.cam.ac.uk