title: Modelling and inference for epidemic models featuring non-linear infection pressure.
abstract: We consider a Susceptible-Infective-Removed (SIR) stochastic epidemic model in which the infection rate is of the form βN⁻¹X(t)Y(t)(α). It is demonstrated that both the threshold behaviour of this model and the behaviour of the corresponding deterministic model differ markedly from the standard SIR model (i.e. α=1). Methods of statistical inference for this model are described, given outbreak data, and the extent to which all three model parameters can be estimated is considered.
authors.affiliation: School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK. philip.oneill@nottingham.ac.uk
authors.forename: P D
authors.initials: PD
authors.lastname: O'Neill
authors.forename: C H
authors.initials: CH
authors.lastname: Wen
mesh_terms: D000818:Animals; D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission / Q000662:veterinary; D003198:Computer Simulation / Q000706:statistics & numerical data; D058872:Epidemics / Q000706:statistics & numerical data*; D006801:Humans; D058751:Livestock; D008954:Models, Biological; D015233:Models, Statistical; D017711:Nonlinear Dynamics