Developing an agent-based model to simulate the beef cattle production and transportation in southwest Kansas

Abstract Modern beef cattle production in the U.S. is a highly specialized system that spans from cow–calf ranches, to stockers, to feedlots, to packers. The cattle production system is particularly interdependent with the transportation system, as cattle and feed need to be moved through production phases. Although this interdependence enables the economic functioning of the interdependent system, it also brings vulnerabilities to the system amplifying disease spreading and natural disaster consequences. Taking southwest Kansas as a study area, we explicitly model the beef cattle industry and the transportation industry as two independent but interconnected industries through agent-based modeling. Since cattle and truck movement data are scarce due to privacy concerns, we first generate cattle and truck movement data among production locations under normal operating conditions. We then assess the system robustness by constructing hypothetical disruptions in the cattle industry and in the transportation industry. The simulation results show that the interdependent system is robust to random failures but vulnerable to the targeted shutdown of cattle premises or truck premises. In addition, we observe that disruptions in the trucks serving packers have the worst impact on cattle production, as compared to other transportation disruptions. In disaster preparations, policymakers and system designers need to consider vulnerabilities caused by the interdependent infrastructure and pay particular attention to one of its critical components, meat packers.