The intersection of science and policy remains a challenging space, perhaps highlighted most clearly in the world’s efforts to address COVID-19 and leverage rapidly evolving scientific information. For foot-and-mouth disease (FMD) and similar transboundary animal diseases (FAST), the need to prevent,detect and respond to shifting disease threats highlights the need for data-driven tools that can be used to collect critical health information, explore policy alternatives, anticipate consequences, and evaluate impacts. A variety of modelling tools are often used to evaluate alternative approaches to thecontrol of FAST diseases; however, the use of these tools is not without pitfalls, and the dangers of “garbage in, garbage out” are increasingly present.