Presented by: Professor Sir Roy Anderson (Imperial)

The historical and epidemiological literature abound with accounts of infectious disease epidemics and of the concomitant effects on population abundance, social organisation and the unfolding pattern of historical events. Epidemics have long been a source of fear and fascination in human societies, but it is only in comparatively recent times that their origins and patterns have begun to yield their secrets through mathematical and scientific study.

The talk will examine the role played by predictive modelling in modern infectious disease epidemiology and will illustrate this by reference to past epidemics including the very recent H1N1 influenza pandemic (Did we overreact ? How can we better measure and predict pathogenicity? Will the H1N1 experience have a detrimental impact on how we respond to future epidemics?). The talk will also examine some of the neglected tropical diseases to address how can epidemiological modelling help the poorest societies in the world control infection and disease, and also help international agencies develop cost effective policies?

Free attendance

There will be a reception after the lecture

Main contact point: paula.matthews@warwick.ac.uk

Downloads: 2014-002-12-roy-anderson.pdf

Amanda Turner (Lancaster)

Small particle limits in a regularized Laplacian random growth model
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In 1998 Hastings and Levitov proposed a one-parameter family of models for planar random growth in which clusters are represented as compositions of conformal mappings. This family includes physically occurring processes such as diffusion-limited aggregation (DLA), dielectric breakdown and the Eden model for biological cell growth. In the simplest case of the model (corresponding to the parameter alpha=0), James Norris and I showed how the Brownian web arises in the limit resulting from small particle size and rapid aggregation. In particular this implies that beyond a certain time, all newly aggregating particles share a single common ancestor. I shall show how small changes in alpha result in the emergence of branching structures within the model so that, beyond a certain time, the number of common ancestors is a random number whose distribution can be obtained. This is based on joint work with Fredrik Johansson Viklund (Columbia) and Alan Sola (Cambridge).

Vasileios Maroulas (Bath/Tennessee)

Filtering, drift homotopy and target tracking

Abstract:
Target tracking is a problem of paramount importance arising in Biology, Defense, Ecology and other scientific fields. We attack to this problem by employing particle filtering. Particle filtering is an importance sampling method which may fail in several occasions, e.g. in high dimensional data. In this talk, we present a novel approach for improving particle filters suited to target tracking with a nonlinear observation model. The suggested approach is based on what I
will call drift homotopy for stochastic differential equations which describe the dynamics of the moving target. Based on drift homotopy, we design a Markov Chain Monte Carlo step which is appended to the particle filter and aims to bring the particles closer to the observations while at the same time respecting the dynamics. The talk is based on joint works with Kai Kang and Panos Stinis.

Audrey Kueh talks about the Cosmic Microwave Background. In the past 20 years, there has been a glut of high resolution data from Cosmic Background Explorer (COBE), Wilkinson Microwave Anisotropy Probe (WMAP) and the Planck Probe. However, the band containing the Milky Way is polluted with emissions from the Milky Way itself, thus we have incomplete data. Also, there is only 'one' observation. She will talk about spherical wavelets and how they sidestep the above problems and shed light on the origin of the universe.