Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

Issues in the fields of wildlife disease and One Health are often difficult to address by single research groups because of the many disciplines and areas of expertise required to effectively solve complex problems. Although collaborations are becoming increasingly prevalent in the professional realm, many undergraduate, graduate, and professional students are merely introduced to the idea of collaboration without fully understanding how team-based approaches function. In this report, we describe the framework for a one-day workshop hosted by the Colorado State University student chapter of the Wildlife Disease Association (CSU WDA), where we gathered students and professionals to collectively investigate a simulated wildlife disease outbreak. CSU WDA student members designed the workshop and recruited professionals who are experts in their respective fields to run an outbreak simulation during the event. Based on pre- and post-event evaluation responses, this workshop was effective in increasing participants’ knowledge of disease ecology, pathology, genetics, and microbiology, as well as the importance of collaboration among disciplines as it pertains to wildlife disease outbreaks.