289. Modeling the Epidemiological and Social Drivers of Livestock Diseases: A System Dynamics Model of Bovine Respiratory Disease.

Abstract Bovine Respiratory Disease (BRD) is the primary driver of economic losses in beef production, resulting in high morbidity, mortality, and treatment expenses. Effectively mitigating BRD requires modeling the feedback between farmer stewardship and biological factors, as well as economic and antimicrobial use parameters. A comprehensive approach must capture how these variables interact to influence BRD's impact as a complex multifactorial disease. However, existing BRD models often overlook these complex feedback interactions, typically examining biological or economic factors separately through reductionist approaches. To accurately represent BRD in beef production systems, our model integrates herd dynamics, antimicrobial use, and profitability metrics, key interacting factors that shape disease susceptibility and farm sustainability. The dynamic hypothesis of this work is that disease risk factors and susceptibility drive antimicrobial use, which may optimize production in the short term but often hampers the herd's long-term productivity and profitability. We analyzed a causal loop diagram (CLD) developed through group model building (GMB) and broad literature synthesis. The CLD variables were de-identified into three subcategories denoted as stocks, flows, and auxiliary variables. The program Vensim PLE 10.2.0 was used to design a stock and flow model that visualizes system changes over time and captures the dynamic complexity of BRD. The model centered around three disaggregated systems: epidemiology, antimicrobial use, and economics (Figure 1). The epidemiology system demonstrates the SEIQR model, simulating disease progression in terms of cattle stocks (herd) as Susceptible (S), Exposed (E), Infected (I), Quarantine (Q), and Recovered (R) stocks (Figure 2). Each stock is modeled with corresponding inflows and outflows, which are affected by several biological and epidemiological factors (represented as auxiliary variables) integrated by mathematical equations {dS/dt = β(1-Ev - Eq)SI} and values that influence the deterministic model.Our key finding shows that targeted interventions like vaccination and targeted treatment/metaphylaxis can modulate BRD incidence, spread, and potential for profit in integrated beef production systems. Instead of focusing on a single cause, our model simulates the time-based dynamics of disease in feedlots, allowing farmers to test policy decisions virtually for improved stewardship and mitigating diseases. To consolidate the outcomes of this research, the next steps will incorporate antimicrobial resistance development cycle and an in-depth profitability model. For image description, please refer to the figure legend and surrounding text. For image description, please refer to the figure legend and surrounding text.