Biocomplexity Institute Leads CDC Research to Study Influenza Mitigation with Computer Modeling and Simulation

A person wearing a flu mask

September 24, 2019

Influenza seasons pose a significant threat to the nation’s health. According to the Centers for Disease Control and Prevention (CDC), influenza killed approximately 80,000 people in the United States during the 2017-2018 flu season. While vaccination is the primary and most effective way to prevent sickness and death caused by flu, the CDC reports that less than 40 percent of Americans age 18 and older typically receive a flu shot. This begs the question: what additional mitigation and prevention methods might improve the public health response and policy development for the flu? 

To help find the answer, the CDC awarded the University of Virginia’s Biocomplexity Institute a one-year contract to build a team dedicated to determining the efficacy of multiple layered interventions for pandemic and seasonal flu epidemics using computer modeling and simulation. The Smart Targeting and Optimization for the Mitigation and Prevention of Influenza (STOMP-flu) project began in August and spans through August 31, 2020.

The STOMP-flu team will conduct research, modeling, and simulation studies to answer specific operational questions about how potential practices aimed at mitigating seasonal and pandemic flu epidemics, such as antiviral treatments, temporary school closures, and the use of vaccines, among others, may help improve our nation’s response and overall health, especially during flu season.  

“Historically, the CDC has relied on traditional epidemiology analysis and real-world data to measure the population’s response to the flu pandemic. This is the first time they have worked directly with academic partners in an operational capacity to do modeling, which is the best way to answer the specific questions we’re looking at here,” said Bryan Lewis, nationally recognized epidemiologist and research associate professor from the Institute’s Network Systems Science and Advanced Computing division. “It’s remarkable to see the advancement of modeling and simulation for public health decision-making, and we’re in good company with some of the best modelers in the country to help move it forward.”

Lewis leads the STOMP-flu team as principal investigator along with Co-Principal Investigator and Model Adviser Stephen Eubank, Co-Principal Investigator and MPM Lead Srinivasan Venkatramanan, Simulation Lead Jiangzhuo Chen, Behavior Lead Mark Orr, and Software and Data Lead Mandy Wilson. As one of the original teams in the National Institutes of Health (NIH) Modeling of Infectious Disease Agent Study (MIDAS), the group brings more than a decade of team experience with influenza modeling and simulation, computational models of health behavior, forecasting infectious disease, and providing support to the federal government for outbreak response to the STOMP-flu project. 

Throughout the next year, the team will build a well-calibrated metapopulation model (MPM) on a national scale to estimate the potential impact of multiple layered interventions on pandemic and seasonal flu epidemics. In the spirit of team science, the group is working and collaborating across three teams. The first is a dedicated MPM team focused on extending an MPM to evaluate specific layered interventions. The second, an agent-based model (ABM) team, is extending an existing ABM simulation platform to represent layered interventions and lay the groundwork to model individual-level health behavior, which is crucial in planning pandemic response. Finally, the software and data team is providing support to both model teams in data management and integration. 

At the conclusion of the pilot in August 2020, the STOMP-flu team will deliver at least one published study addressing the impacts of layered interventions to pandemic influenza scenarios and a strong stable of models and techniques to answer a variety of additional operational and policy questions. 

“It has always been my goal to support public health decision-making with epidemiology at the federal level – for our work to impact the population in a direct way and have real-world consequences,” said Lewis. “It’s very exciting to get to do that and an excellent opportunity for the Biocomplexity Institute to provide service to the federal government in a real way with techniques we believe in. Ultimately, our goal is to make the country more resilient to both seasonal and potential influenza pandemics and to bolster the public health infrastructure in this country.”