Modeling the Pandemic Lifecycle for Disease Control
Summary
Throughout history, infectious disease pandemics have played decisive roles in wars and economic collapse, and they continue to drive health disparities within and among nations (REF). Infectious diseases have also shaped the human genome in significant ways, with infectious disease identified as among the most important selective forces in human history. Infectious disease experts have long aimed to predict the next novel infectious disease outbreak, but they have yet to succeed. Instead, public health communities scramble to identify and contain infectious diseases after outbreaks occur. As the coronavirus pandemic reveals, bold new approaches are needed for pandemic prediction, prevention, and mitigation. Our proposal views pandemics in a network framework, scaling from the local dynamics of transmission processes to patterns of global connectivity and institutional mechanisms for pandemic prevention and control. We hypothesize that pandemics emerge via a confluence of rare events that take advantage of modern social organization to achieve wide geographic spread. It is not yet possible to characterize these early stages of pandemics with the tools and data currently available. Our team has unique access to data, approaches, and disciplines needed to investigate this hypothesis and transform understanding of the pandemic lifecycle, and thus to ultimately identify multiple contingent bottlenecks in the progression from an initial crossover infection to worldwide pandemic. With this understanding, public health authorities will be better positioned to monitor, model, and mitigate future outbreaks at crucial breakpoints so that control is possible. How can we characterize the pandemic potential of an infectious disease outbreak and ready population health models for mitigation and intervention? We will address this by characterizing transmission pathways across scales and identifying the social, ecological, and economic factors that shape these pathways, with a special focus on early-stage transmission so that control is most effective. Addressing this challenge would improve forecasting of pathogen spread, while also enabling more rapid and effective public health responses.