The Visual Language of COVID-19

Abstract

The history of public health is, in part, a history of visual representations of contagion. Efforts to halt the spread of infectious disease depend upon a concept of prevention which entails anticipation and mitigation of invisible threats. As a pandemic of the big data era, COVID-19 has presented new scenarios of prevention that depend on risk modelling based on analysis of large data sets. Yet, the pandemic has also followed a pathway consistent with the global history of disease, which relies on visual imagery of pathologised others to embody the mortal threat. How does the visual representation of embodied contagion intersect with the visual representation of the data-driven pandemic? Does the proliferation of data—from testing, contact tracing, cell-phone mobility, geographic information systems, wearable fitness trackers, online searches, telehealth encounters, and other digital residue—shape our understanding of contagion differently than previous approaches to representing infectious disease outbreaks? This chapter explores how the emergence of predictive analytics based on modelling of large data sets in healthcare has interacted with visual narratives of infection and prevention. It asks what is gained and lost when the human experience of a global pandemic is depicted through ed data visualisations.