Five challenges for stochastic epidemic models involving global transmission
Tom Britton,
Thomas House,
Alun L. Lloyd,
Denis Mollison,
Steven Riley,
Pieter Trapman
Affiliations
Tom Britton
Department of Mathematics, Stockholm University, Stockholm 106 91, Sweden
Thomas House
Warwick Infectious Disease Epidemiology Research Centre (WIDER) and Warwick Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK
Alun L. Lloyd
Department of Mathematics and Biomathematics Graduate Program, North Carolina State University, Raleigh, NC 27695, USA
Denis Mollison
Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh EH14 4AS, Scotland, UK
Steven Riley
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
Pieter Trapman
Department of Mathematics, Stockholm University, Stockholm 106 91, Sweden
The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?
