PIPP Phase I: Modeling the Pandemic Lifecycle for Disease Control

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Despite considerable effort, infectious disease experts are unable to predict the next major pandemic. Bold new approaches are needed for pandemic prediction, prevention, and mitigation. This research team investigates the “pandemic lifecycle” – starting from transmission on local contact networks, to regional and then international spread – with a focus on early stages of this lifecycle. During the early stages of an outbreak, an infectious disease spreads among individuals locally through contact patterns; as the outbreak grows, opportunities arise for infections to seed new communities and repeat the process of local transmission. Most transmission goes undetected in these early stages, yet this is when control is most cost-effective and most likely to succeed. The project examines how infectious disease and human knowledge interact on human contact networks, identifies methods and data needed to investigate early stages of outbreaks, and implements new approaches to predict and control outbreaks in the context of the pandemic lifecycle. Findings can help public health authorities and scientists to better model and monitor future outbreaks, with the potential to reduce disease risk, save lives, and improve economic outcomes globally. Researchers from across three institutions in the North Carolina Triangle region collaborate to investigate outbreaks using a network-centered perspective. The investigators use existing data and build on international partnerships and strengths in global health, statistical network sciences, economics, engineering, ecology and evolution, geography, and sociology to characterize outbreaks and the dissemination of infection regionally. The Phase I research activities focus on a series of Working Groups and a Pilot Study. The Working Groups are organized around fundamental – but currently unanswered – questions about the pandemic lifecycle. The Pilot Study aims to develop a simulation model to further explore these questions, and to validate and extend statistical methods to characterize early-stage transmission in relation to incomplete sampling. The ultimate goals of the project are to advance methods and knowledge, train graduate students and a postdoctoral researcher, and prepare for future implementation of these research thrusts to enhance pandemic prediction and control.This award is supported by the cross-directorate Predictive Intelligence for Pandemic Prevention Phase I (PIPP) program, which is jointly funded by the Directorates for Biological Sciences (BIO), Computer Information Science and Engineering (CISE), Engineering (ENG) and Social, Behavioral and Economic Sciences (SBE).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.