COVID-19 Simulator Informs Local Policymaking: Q&A with Jagpreet Chhatwal, PhD

The COVID-19 Simulator , developed by Massachusetts General Hospital, Harvard Medical School, Boston Medical Center and Georgia Tech, was launched in April 2020 to help health policymakers and practitioners make decisions regarding policy and strategy related to the novel coronavirus pandemic. The original tool shows how lifting or continuing physical distancing measures can impact a state’s number of COVID-19 positive tests, hospitalizations and death.

Since launching, the collaborators have expanded on its offerings to help policymakers make decisions at a county level. In this Q&A, Jagpreet Chhatwal, PhD , associate director of the Institute for Technology Assessment at Mass General, describes the new simulation tools available to lawmakers, how the tools can help make opening/closing decisions and his thoughts on the outlook for the upcoming surge of the pandemic.

Q: Have you made advancements in your risk prediction process since launching the tracker?

Chhatwal: We added three new modules to the COVID-19 Simulator since its launch.

First, the simulator now provides an estimate of the proportion of the population that has been infected (diagnosed as well as undiagnosed) in each state. The COVID-19 Seroprevalence Tracker displays the current estimate of seroprevalence of antibodies in each state.

Second, we developed a new COVID-19 Outbreak Tool to detect early outbreaks in different counties. Using an AI-based approach, we can understand how fast COVID-19 is spreading in each county by predicting the COVID-19 doubling time (the number of days it takes for COVID-19 cases to double). By detecting local outbreaks, the tool allows policymakers to implement measures at the county level, such as closing restaurants in a single county, to effectively contain the pandemic.

Third, we developed COVID-19 Football Tracker that focuses on the National Football League (NFL) and National Collegiate Athletic Association (NCAA) football games. Because the NFL and NCAA made the decision to play their games amidst the ongoing COVID-19 pandemic, we developed a football tracker to can help public officials and team owners in their decision-making regarding in-person attendance. The tool provides predicted trends such as the COVID-19 doubling time and how fast COVID-19 cases are increasing in counties with NFL/NCAA stadiums that have hosted games or might host games in the future.

Q: How have these changes improved the simulator?

Chhatwal: The first version of the simulator informed how lifting or extending different physical distancing measures at various times can impact each state in terms of COVID-19 cases, hospitalizations and deaths. The new modules further provide insights into local-level COVID-19 outbreaks and how far are we from reaching herd immunity.

Q: What can the simulator tell us about the future of this pandemic in Massachusetts and the U.S.?

Chhatwal: According to our simulator, the number of COVID-19 cases and deaths are projected to increase in Massachusetts as well as in many other states under the current status quo. We may need to bring back stay-at-home orders for a short period to change the course of the pandemic and prevent deaths.

Q: What should people do to be prepared for the upcoming surge?

Chhatwal: People should continue to follow physical distancing interventions like masking and limiting social gatherings. The government needs to invest more in testing and contact tracing. If needed, states should be ready to bring back stay-at-home orders as being re-implemented in several countries in Europe.

Q: Are there any surprising insights from the modeling data?

Chhatwal: The COVID-19 Seroprevalence Tracker shows that New York, New Jersey, Louisiana and Massachusetts have higher seroprevalence of COVID-19 antibodies (15%-25%) than the rest of the country. Contrary to the message from a few political leaders, we have not achieved herd immunity in any of the states. Moreover, no state is even close to the level of 50%-70% seroprevalence needed to achieve herd immunity.