Many recent examples, such as avian flu, SARS, West-Nile virus (WNV), BSE, foot-and-mouth-disease (FMD), etc. demonstrate that infectious diseases may have serious economic and public health consequences. Modelling the spread of disease in time and space i s considered as part of decision support related to disease control. Lots of models have been developed to describe the dynamics of various epidemics. It is typical, however, that traditional dynamical models focus on average trends and pay less attention to assessing the uncertainty of the predictions.
The aim of the project is to develop a methodology to assess the precision of results from existing dynamical epidemic models using modern statistical methods. This may lead to better identification of risk factors, more accurate predictions, more adequate planning of control measures, and improved ability to compare some alternatives. The project focuses on two applications: FMD and West Nile virus disease. In the host institution, there is high quality research on modelling of infectious diseases, with much experience on general methodology as well as on concrete models (rabies, FMD, phocine distemper virus, etc). I would like to contribute to this with my skills in statistics and stochastic modelling.
My field within statistics is re-sampling methods, which can be used to incorporate random variability into dynamical models in a natural way. Models developed at the host institution in former projects give opportunities to extensive experimentation with these methods. The project is based on a former cooperation: we had a joint scientific seminar in veterinary epidemiology in 2003-2004. I expect from the project to become an expert in epidemic modelling and to improve at organization and management of research projects. I could use these skills in future projects in Hungary and/or in the EU. On the other hand, the host institution could make use of my expertise in statistics and stochastic modelling.
Fields of science
Call for proposal
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