Eliminating infectious diseases of livestock: a metapopulation model of infection control

Abstract

When novel disease outbreaks occur in livestock, policy makers must respond promptly to eliminate disease, and are typically called on to make control decisions before detailed analysis of disease parameters can be undertaken. We present a flexible metapopulation model of disease spread that incorporates variation in livestock density and includes occasional high-mixing locations or events, such as markets or race meetings. Using probability generating functions derived from this branching process model, we compare the likely success of reactive control strategies in eliminating disease spread. We find that the optimal vaccine strategy varies according to the disease transmission rate, with homogeneous vaccination most effective for low transmission rates, and heterogeneous vaccination preferable for high levels of transmission. Quarantine combines well with vaccination, with the chance of disease elimination enhanced even for vaccines with low efficacy. Control decisions surrounding horse race meetings were of particular concern during the 2007 outbreak of equine influenza in Australia. We show that this type of high-mixing event is a powerful spread mechanism, even when the proportion of time spent at such events is low. If such locations remain open, elimination will require a highly effective vaccine with high coverage. However, a policy of banning animals from quarantined regions from attending such events can provide an effective alternative if full closure of events is economically or politically untenable.