Simulation of foot-and-mouth disease spread within an integrated livestock system in Texas, USA.

We used a simulation study to assess the impact of an incursion of foot-and-mouth disease (FMD) virus on the livestock industries in an 8-county area of the Panhandle region of Texas, USA. The study was conducted in a high-density livestock area, with an estimated number of cattle on-feed of approximately 1.8 million. We modified an existing stochastic, spatial simulation model to simulate 64 scenarios for planning and decision-making. Our scenarios simulated four different herd types for the index herd (company feedlot, backgrounder feedlot, large beef, backyard) and variations in three mitigation strategies (time-of-detection, vaccine availability, and surveillance during disease control). Under our assumptions about availability of resources to manage an outbreak, median epidemic lengths in the scenarios with commercial feedlot, backgrounder feedlot, large beef and backyard index herd types ranged from 28 to 52, 19 to 39, 18 to 32, and 18 to 36 days, respectively, and the average number of herds depopulated ranged from 4 to 101, 2 to 29, 1 to 15 and 1 to 18, respectively. Early detection of FMD in the index herd had the largest impact on reducing ( approximately 13-21 days) the length of epidemics and the number of herds ( approximately 5-34) depopulated. Although most predicted epidemics lasted only approximately 1-2 months, and <100 herds needed to be depopulated, large outbreaks lasting approximately 8-9 months with up to 230 herds depopulated might occur.

The potential role of wild and feral animals as reservoirs of foot-and-mouth disease.

We investigated the potential role of feral pigs and wild deer as FMD reservoirs with a susceptible-latent-infected-recovered geographic-automata model, using spatially referenced data from southern Texas, USA. An uncontrolled FMD outbreak initiated in feral pigs and in wild deer might infect up to 698 (90% prediction interval 181, 1387) and 1557 (823, 2118) cattle and affect an area of 166 km(2) (53, 306) and 455 km(2) (301, 588), respectively. The predicted spread of FMD virus infection was influenced by assumptions we made regarding the number of incursion sites and the number of neighborhood interactions between herds. Our approach explicitly incorporates the spatial relationships between domesticated and non-domesticated animal populations, providing a new framework to explore the impacts, costs, and strategies for the control of foreign animal diseases with a potential wildlife reservoir.

The impact of potential mitigation strategies on the predicted spread of foot and mouth disease in white-tailed deer in south Texas.

The United States has been free of FMD since the 1920s. Faced with an incursion of FMD virus that might involve wildlife species, it is crucial that appropriate mitigation strategies be applied rapidly to control the disease. Disease spread models can be used to evaluate the design of optimal strategies. Using a previously developed susceptible-infected-recovered geographic automata model (Sirca) to simulate the spread of FMD through white-tailed deer populations in south Texas, we conducted a series of experiments to determine how pre-emptive mitigation strategies applied to white-tailed deer populations might impact the predicted magnitude and distribution of outbreaks following FMD virus incursion. Based on previously derived deer distributions in the two ecoregions found within the study area, simulated outbreaks were evaluated by comparing the median number of deer predicted to be infected and the median area predicted affected for a baseline scenario and 3 mitigation strategies: targeted cull, random cull and targeted depopulation buffer. Substantial differences were observed in the predicted magnitude of outbreaks both by mitigation strategy and by ecoregion: depending on the ecoregion, the creation of a targeted depopulation buffer could reduce the number of deer predicted infected by up to 52%, and the area affected by up to 31%. Results suggest that the outcome of an FMD incursion that involves wildlife species, such as white-tailed deer in south Texas, might depend on both where the incursion occurs and the type of pre-emptive mitigation strategy applied.

Modelling spread of foot-and-mouth disease in wild white-tailed deer and feral pig populations using a geographic-automata model and animal distributions.

We investigated how the size and distribution of wild deer and feral pigs - species that might act as potential foot-and-mouth disease (FMD) virus maintenance hosts - might affect the persistence and spread of FMD. We used a susceptible-latent-infected-recovered geographic-automata model and spatially referenced data from southern Texas, USA. Within this study area, 100 locations were randomly selected and FMD virus spread was simulated (50 simulations each) at each location. As expected, the predicted sizes (km(2)) of the wild deer outbreaks were highly correlated (r(SP)>0.95) with the number of deer at incursion locations, the total number of deer within 2 km of incursion locations, and the minimum and maximum deer herd size within 2 km of incursion locations. However, the predicted sizes of the feral pig outbreaks were only moderately correlated (r(SP) 0.63-0.67) with the total, maximum and variance of the number of feral pigs within 2 km of incursion locations. Lack of continuity within the feral pig herd distribution across the landscape makes predicting disease spread more difficult than for deer, a more homogenously distributed species. When assessing the potential of wild and feral animal species at a locality to act as maintenance hosts of FMD virus, estimates of the population size and distribution might serve as a useful indicator of potential outbreaks in some circumstances.

The impact of seasonal variability in wildlife populations on the predicted spread of foot and mouth disease.

Modeling potential disease spread in wildlife populations is important for predicting, responding to and recovering from a foreign animal disease incursion such as foot and mouth disease (FMD). We conducted a series of simulation experiments to determine how seasonal estimates of the spatial distribution of white-tailed deer impact the predicted magnitude and distribution of potential FMD outbreaks. Outbreaks were simulated in a study area comprising two distinct ecoregions in South Texas, USA, using a susceptible-latent-infectious-resistant geographic automata model (Sirca). Seasonal deer distributions were estimated by spatial autoregressive lag models and the normalized difference vegetation index. Significant (P < 0.0001) differences in both the median predicted number of deer infected and number of herds infected were found both between seasons and between ecoregions. Larger outbreaks occurred in winter within the higher deer-density ecoregion, whereas larger outbreaks occurred in summer and fall within the lower deer-density ecoregion. Results of this simulation study suggest that the outcome of an FMD incursion in a population of wildlife would depend on the density of the population infected and when during the year the incursion occurs. It is likely that such effects would be seen for FMD incursions in other regions and countries, and for other diseases, in cases in which a potential wildlife reservoir exists. Study findings indicate that the design of a mitigation strategy needs to take into account population and seasonal characteristics.