Large-scale models based on population structure for the spatiotemporal distribution of U.S. porcine epidemic diarrhoea outbreaks

ABSTRACT

In 2013, U.S. swine producers were confronted with the disruptive emergence of porcine epidemic diarrhoea (PED). Movement of animals among farms is hypothesised to have played a role in the spread of PED among farms. Via this or other mechanisms, the rate of spread may also depend on the geographic density of farms and climate. To evaluate such effects on a large scale, we analyse state-level counts of outbreaks and state-level changes in the number of pigs weaned along with variables describing the distribution of farm sizes and types, aggregate flows of animals among farms, and an index of climate. Flows are found to be correlated with cross correlations in outbreak time series. We illustrate when such a relationship might be expected with simulation of a simple model of farm-to-farm spread. We then use stability selection to determine that balance-sheet variables and the number of farms in a state are relevant predictors of PED burdens. We fit a transmission model that estimates effects of both farm density and flows on transmission rates. These results may help connect the modeling of emerging livestock diseases with field data.