Modeling the benefits of virus discovery and pandemic virus identification

Abstract

Preventing and mitigating future zoonotic pandemics are global health priorities, but there are few quantitative estimates of how best to target interventions. Here we construct a mathematical model to evaluate the benefits of 1) virus discovery and sequencing (VDS) in animals and 2) pandemic virus identification (PVI) via laboratory characterization of pandemic potential. Drawing on historical data and expert surveys of One Health and vaccine researchers, we estimate that intensifying virus discovery efforts by three-fold could prevent between 0 and 1.46 million expected deaths per decade by improving non-pharmaceutical interventions and broad-spectrum vaccines. In contrast, because researchers estimate that there are well over a hundred pandemic-capable viruses in nature, identification through laboratory characterization would prevent 48,000 deaths per decade [10,500; 93,600], or just ∼0.62% of expected pandemic deaths. Further identifications would offer diminishing returns. Given wide-ranging survey responses and limited cost-effectiveness compared to proven global health interventions such as insecticide-treated bed nets, our model suggests that health establishments aiming to mitigate future pandemics should focus on monitoring spillover hotspots and empowering local communities to detect, sequence, and suppress nascent epidemics rather than characterizing pandemic potential in laboratories.