Connecting livestock disease dynamics to human learning and biosecurity decisions - Bucini, Gabriela; Clark, Eric M.; Merrill, Scott C.; Langle-Chimal, Ollin; Zia, Asim; Koliba, Christopher; Cheney, Nick; Wiltshire, Serge; Trinity, Luke; Smith, Julia M. (Frontiers in Veterinary Science, 2023)
The acceleration of animal disease spread worldwide due to increased animal, feed, and human movement has driven a growing body of epidemiological research as well as a deeper interest in human behavioral studies aimed at understanding their interconnectedness. Biosecurity measures can reduce the risk of infection, but human risk tolerance can hinder biosecurity investments and compliance. Humans may learn from hardship and become more risk averse, but sometimes they instead become more risk tolerant because they forget negative experiences happened in the past or because they come to believe they are immune. We represent the complexity of the hog production system with disease threats, human decision making, and human risk attitude using an agent-based model. Monte Carlo simulations of scenarios designed with different risk tolerance amongst the swine producers provide distributions and trends of biosecurity and porcine epidemic diarrhea virus (PEDv) incidence emerging in the system. We examine interactions between modes of risk tolerance and timings of biosecurity response discussing consequences for disease protection in the production system. Simulations show that hasty and delayed biosecurity responses or slow shifts towards a biosecure culture do not guarantee control of contamination when the disease has already spread in the system. In an effort to support effective disease prevention, our model results can inform policy making to move towards more resilient and healthy production systems. The modeled dynamics of risk attitude have also the potential to improve communication strategies for nudging and establishing risk averse behaviors thereby equipping the production system in case of foreign disease incursions.