 |
Center for Nonlinear Studies |
Animal diseases, such as foot-and-mouth disease and avian flu, are increasingly important in world economics, national security, and biodiversity. Rinderpest is an important animal disease related to human measles. It is a highly virulent and often lethal virus affecting cloven-hoofed animals such as cattle, sheep, and pigs. Rinderpest pandemics have caused wide-spread herd loss in Europe and Africa. If the disease enters the United States, it could be devastating to animal agriculture and the economy. To help prepare for this possibility, we create a spatially explicit stochastic model for multi-host animal diseases to better understand their spread in the United States. We explore the effectiveness of mitigation strategies such as quarantine, vaccination, and culling in a case study on rinderpest. Spread of rinderpest is modeled using county-level data and animal transportation rates to capture the within-county and between-county behavior. We compare different mitigation strategies and analyze the sensitivity of final epidemic size to these strategies in order to minimize loss due to an outbreak of rinderpest. We find that severe epidemics occur if the disease spreads to high animal density areas in the Midwest. Effective spatial control strategies include faster response time, better movement restriction, and widespread surveillance in certain key groups of counties. Reducing the time between detection and culling or quarantine also lowers the size of an epidemic. Vaccination, however, is not as effective for controlling a newly introduced, virulent disease such as rinderpest. Generalizations of control strategies for rinderpest are effective for other contagious animal diseases, such as foot and mouth disease.