Uncertainty and realism in a national cattle foot-and-mouth disease model

Kendra E. Gilbertson, Biology, Colorado State University, Lindsay M. Beck-Johnson, Biology, Colorado State University, Fort Collins, CO, Peter Brommesson, Tom Lindstrom and Stefan Sellman, Linköping University, Sweden, Clayton Hallman, APHIS-VS-CEAH, USDA, Fort Collins, CO, Ryan S. Miller, Center for Epidemiology and Animal Health, USDA-APHIS, Veterinary Services, Fort Collins, CO, Amanda Minter, University of Oxford, United Kingdom, Katie Portacci, USDA APHIS VS CEAH, Fort Collins, CO, Michael J. Tildesley, Systems Biology and Infectious Disease Epidemiology Research Centre, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom, Colleen T. Webb, Department of Biology, Colorado State University, Fort Collins, CO

Background/Question/Methods
Foot-and-mouth disease (FMD) is a fast-moving virus with the potential to cost the United States (U.S.) cattle industry billions of dollars. The last FMD outbreak in the U.S. occurred in the early 1900s, so we rely on simulated outbreaks to evaluate control measures and factors affecting disease spread. The United States Disease Outbreak Simulation (USDOS), which was developed in an international collaborative effort between the Colorado State, Linköping and Warwick Universities, and the U.S. Department of Agriculture, with support of from the U.S. Department of Homeland Security, simulates local and long distance FMD spread in cattle nationwide. We used USDOS to address two questions: (1) how does adding increased realism to within-herd disease spread by allowing cattle on individual farms to become infectious over time, rather than the whole herd becoming infectious at once, affect outbreak metrics? and (2) what characteristics are important in determining outbreak metrics? To answer the first question, we compared outbreak simulation results with and without increased within-herd spread realism. To answer the second, we ran a sensitivity analysis modeling five different outbreak metrics incorporating farm, county, and national level covariates.
Results/Conclusions
We found that increasing the realism of within-herd disease spread increased the duration of the simulated outbreaks, but did not change their geographic pattern. Allowing herds to become infectious over time increases the length of time an individual farm is infectious, allowing more time for FMD to spread to other susceptible local farms. This effect on individual farms scales up and increases outbreak duration as a whole. The results of our sensitivity analysis showed that outbreak metrics are primarily influenced by demographic characteristics such as farm size, and county-level farm density, and clustering. Overall, we found that the results of our FMD disease simulations were driven by local characteristics, and while adding disease-spread realism affected outbreak duration, it will be more relevant to some research questions than others and should be balanced with its increased computational requirements.