The persistence of a SIS disease in a metapopulation.
Abstract
Deterministic models predict that susceptible-infective-susceptible (SIS) disease, where there is no immunity to reinfection following recovery, will become infinitely persistent in a host population. The authors explored the incorporation of stochasticity into SIS models; modelled interacting host-disease agents in metapopulations; and examined model predictions in a real system involving feline enteric coronavirus (FECV) infection in domestic cats. SIS models incorporating stochasticity predicted that disease persistence would be finite and dependent on the host population size, provided the host population was isolated. However, the disease may persist by dynamic spread among inter-acting host metapopulations. FECV dynamics were well predicted by stochastic metapopulation models. The models are mathematically tractable, generalizable and mechanistically realistic. The findings from the cat-virus system are immediately applicable to the management of cattery populations and could be adapted to inform eradication programmes for other infectious diseases in animal and human populations. The most practical methods to eradicate FECV would be to remove small catteries (islands) from interactions with large catteries (mainlands) and to convert mainlands to islands by depopulation.