Intervening and Monitoring: Health Policies and Practices during Infectious Disease Outbreaks
(Event video is embedded below.)
November 23, 2020
In “COVID-19 in Context: A Deans’ Forum on Living with a Pandemic” — a series of three virtual events — the Virginia Tech College of Liberal Arts and Human Sciences and the Virginia Tech College of Science are joining together to illustrate how a range of fields are contributing to our understanding of the pandemic.
The second of these events, “Intervening and Monitoring: Health Policies and Practices during Infectious Disease Outbreaks,” took place on November 12, 2020. Sally C. Morton, dean of the Virginia Tech College of Science, chaired the event.
The webinar included two presentations:
The Multiple Ontologies of International Infectious Disease
The Western biomedical framing of pathogens as stable, universal threats becomes disrupted during infectious disease outbreaks. Nevertheless, the real threat of diseases that “don’t respect borders,” a commonplace among global public health practitioners, creates shared challenges to which global health experts attempt to respond in a coordinated albeit localized fashion.
Drawing on her experience on the USAID Zika team and the international COVID-19 Task Force, Julie Gerdes briefly traced concepts of epidemiological data discrepancies, knowledge management, and formative behavior change research design to argue for a multiple ontology of infectious disease outbreaks.
Gerdes, an assistant professor of English at Virginia Tech, also turned to lessons learned from the international Zika response that would benefit practitioners and researchers responding to COVID-19. These lessons included user-centered knowledge sharing platforms, deep ethnographic and participatory approaches to formative risk communication research, and the externalization of implicit error in data visualization.
Choosing Intervention Strategies During an Emerging Epidemic: Bridging Basic and Applied Science
A key tool used by public health officials early in epidemics is contact tracing, where individuals who may have been exposed to the disease become the focus for interventions because of their enhanced risk. Often when traced, these contacts appear uninfected; however, given the timeframe between exposure and tracing, these individuals may simply not yet be symptomatic. In other words, these individuals may eventually begin to transmit the virus and develop symptoms of the disease.
The best way to manage these symptom-free contacts is the subject of much debate and controversy. Strict quarantine policies, where potentially infectious individuals are completely separated from the general population with perfect adherence, are always predicted to be most effective. In reality, however, quarantine requires resources to provide necessities, access to separated spaces, and means of enforcement; otherwise, adherence is low. Mathematical modeling provides important insight into idealized strategies but also allows for consideration of a range of policies and behaviors.
In “Choosing Intervention Strategies During an Emerging Epidemic: Bridging Basic and Applied Science,” Lauren Childs, an assistant professor of mathematics at Virginia Tech, discussed how models are typically employed in research and how they must be adapted to answer urgent, real-world questions on disease spread.