An epidemic model with infector and exposure dependent severity.
A stochastic epidemic model allowing for both mildly and severely infectious individuals is defined, where an individual can become severely infectious directly upon infection or if additionally exposed to infection. It is shown that, assuming a large community, the initial phase of the epidemic may be approximated by a suitable branching process and that the main part of an epidemic that becomes established admits a law of large numbers and a central limit theorem, leading to a normal approximation for the final outcome of such an epidemic. Effects of vaccination prior to an outbreak are studied and the critical vaccination coverage, above which only small outbreaks can occur, is derived. The results are illustrated by simulations that demonstrate that the branching process and normal approximations work well for finite communities, and by numerical examples showing that the final outcome may be close to discontinuous in certain model parameters and that the fraction mildly infected may actually increase as an effect of vaccination.
Ball
Frank
F
School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK. frank.ball@nottingham.ac.uk
Britton
Tom
T
D003141:Communicable Diseases / Q000453:epidemiology*; D004196:Disease Outbreaks / Q000517:prevention & control*; D006801:Humans; D018448:Models, Immunological; D014611:Vaccination / Q000592:standards*