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Nick Savill

Nick is a mathematical modeller and has worked on evolutionary genetics and ecology, cellular dynamics, and infectious disease epidemiology. The unifying theme is of understanding and quantifying processes that govern the dynamics of biological systems. His work is driven by the belief that integrating mathematical modelling and empirical research is an efficient way of testing competing hypotheses, generating biological insight and using and re-using data. This approach entails the development of large numbers of models encompassing the set competing hypotheses and their testing against empirical data using methods of Bayesian model-based inference. In this way, integrating and iterating theory and experiment creates strongly supported, biologically plausible models.

Jayanthi Santhanam

Jay is a Physicist who applies modelling techniques well known in Physics to Biological and Social Sciences. She is particularly interested in understanding the effects of environmental pressures that lead to biological and social evolution. Her work is based on the belief that starting from first principles and using simple approximations, one can build models for complex systems, and still understand what causes an observed phenomena. She received her Ph.D in Physics from the University of Rochester, USA in 2004, and continued her research on  Bose-Einstein Condensation at the University of New Mexico. She started her interdisciplinary work when she was at the Epidemiology Group at the University of Liverpool, building models for gun crimes in  Greater Manchester. She continued her interdisciplinary work at the University of Warwick, where she worked on constructing a nationwide meta-population model for livestock diseases in the USA. She works with Nick and Andrew Read on developing and testing mathematical models of the within-host dynamics of rodent malaria infections.

Zach Janes

Zach is a PhD student with Nick. His main interests are 1) the application of computer simulations, particularly network-based models, to problems in epidemiology and population genetics which are too complex for current mathematical models to yield very informative results, and 2) using the results of these simulations to develop more complex mathematical models. His PhD project is on using large-scale simulations to gain a better understanding of the effect of a range of population dynamic processes - particularly complex population structure, intra-host competition and host-parasite coevolution - on the phylogeny (the phylodynamics) of epidemic viral diseases.

Past members

Suzanne St. Rose

Suzanne was a postdoc on a Defra funded project studying silent spread of highly pathogenic avian influenza (HPAI) in vaccinated poultry flocks. We built a detailed individual-based model of HPAI spread in different types of poultry rearing systems and parameterised it from experimental and epidemiological studies. We found some rather counter-intuitive results. A flock with about 80% of its birds vaccinated may be more infectious than an unvaccinated flock.The effectiveness of a vaccine in protecting individual birds from infection makes little difference to silent spread of bird flu. Our results suggested protection at the level of a flock is a more important risk factor of silent spread than vaccine effectiveness in individual birds. We concluded that vaccination should never be done without the use of unvaccinated 'sentinel' birds. These birds are the best method for rapid detection of bird flu in a vaccinated flock. Suzanne is now at LSHTM.

Martin Miller
Martin was a postdoc with Nick and Andrew Read on a Wellcome Trust funded project to develop and test mechanistic mathematical  models of the within-host dynamics of rodent malaria infections. Using high-quality experimental data from a  previously published experiment, Martin untangled and quantified the complexities of the immune responses against malaria parasites. Martin's work has formed the foundation upon which the group's other model fitting projects depend.

Brajendra Singh
Brajendra was a Research Fellow in the Interdisciplinary Centre for Human and Avian Influenza Research. He developed a new surveillance algorithm for specific, sensitive and rapid detection of pandemic influenza in Scotland. The algorithm uses historic weekly case data from sentinel GPs in Scotland to determine if current cases are unusual, thereby signalling a potential pandemic. The algorithm detects pandemics about a week faster, and is more sensitive, than other methods. More importantly it could potentially be used for other epidemic diseases.

Mike Tildesley
Mike was a CIIE fellow working with Nick and David Gally of the Roslin Institute on a model of E. coli O157 colonisation and growth in the terminal rectum of cattle. He showed that the immune the response has to completely limit bacterial replication on the epithelium within days 5-7, and the consequences of the response can result in a second peak in excretion which was only observed as a consequence of the modeling. In terms of the infection, Mike's work informs when samples should be taken and the types of innate response to be investigated.

Nicole Mideo
Nicole was a CIIE fellow working with Sarah Reece and Nick. She is interested in the ecology and evolution of infectious diseases, particularly understanding the within-host dynamics of malaria infections and why patterns of disease vary between parasite strains and in response to changes in the in-host environment (e.g. immunity, anemia). She integrates theory and experimentation to identify mechanisms and evolutionary explanations for these observed differences. Nicole's main aim is to build up a foundation from which to explore applied issues that are relevant for human health policy, using new modeling approaches that link the within- and between-host scales of disease dynamics.
Document made with KompoZerCreated 26 August 2006, Update 8 January 2012