Forecasting viral futures with USAID’s PREDICT: How data become multispecies security infrastructure

Keywords: biosecurity, surveillance, colonization, emerging infectious disease, forecasting, politics of care
Abstract Type: Virtual Paper Abstract

Abstract

Since the nineteenth century, the collection and analysis of infectious disease data has been increasingly critical for stopping spread, improving equitable access to care, and holding public and private actors accountable during pathogen emergence. At the same time, tracking and forecasting infectious disease can facilitate colonial, racial, and ableist violence by states that deploy it as part of population surveillance. Quantifying lives through infectious disease data can easily lead to the assignment of differential economic worth and costs to those lives. In turn, this can shape who lives, who dies, and how (as well as where and when). How might we navigate these tensions and pitfalls to monitor and forecast disease emergence for more equitable and caring futures? Here, I investigate this by examining how USAID’s PREDICT project enacted care and control through its work with emerging infectious disease data. PREDICT was a ten-year program of the US government (shuttered during the COVID-19 pandemic) that coordinated environmental monitoring and forecasting for emerging zoonotic viruses globally. Using semi-structured interviews and document analysis, I trace PREDICT’s network through core US partners as well as trainees and partner laboratories outside the United States. By following data within this program through collection, modelling, and application, I examine how the more-than-human relationships involved in each of these stages shape the science, governance, and care that have emerged from PREDICT. Through this work, I hope to offer insights into how different ways of forecasting outbreak perform and produce different collective futures while eclipsing or foreclosing others.