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CRiSM Seminar - Tilman Davies

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Location: A1.01

Tilman Davies (Massey University, NZ)

Refining Current Approaches to Spatial and Spatio-Temporal Modelling in Epidemiology

It is reasonable to expect both space and time to be important factors when investigating disease in human, animal and even plant populations. A common goal in many studies in geographical epidemiology, for example, is the idenification of disease risk 'hotspots', where spatial sub-regions that correspond to a statistically significant increase in the risk of infection are highlighted. More advanced problems involving not just space but space-time data, such as real-time disease surveillance, can be difficult to model due to complex correlation structures and computationally demanding operations. Decisions based on these kinds of analyses can range from the local, to national and even global levels. It is therefore important we continue to improve statistical methodology in this relatively young field, and ensure any theoretical benefits can flow through in practice.

This talk aims to give an overview of the PhD research currently underway in an effort to develop and implement refinements to spatial and spatio-temporal modelling. Of note include use of a spatially adaptive smoothing parameter for estimation of the kernel-smoothed relative-risk function, development of a novel, computationally inexpensive method for associated spatial tolerance contour calculation, release of an R package implementing these capabilities, and the scope for improvement to the current marginal minimum-contrast methods for parameter estimation in relevant stochastic models.

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