Newswise — Data modeling projections by Columbia University Mailman School of Public Health scientists evaluate potential policies to reduce new infections, hospitalizations, and deaths in coming months, including by limiting school capacity by 50 percent or capping capacity of certain industries to 25 percent during Phase Four, as well as by implementing an “adaptive PAUSE” system to re-implement social distancing rules during a rebound. The researchers have been working with the New York City Department of Health and Mental Hygiene on COVID-19 planning. Their new report is posted on Github.
Capping school capacity at 50 percent during Phase Four would cut the projected number of infections between 10 and 40 percent compared to a scenario in which schools fully reopen. A policy that keeps schools open at 100 percent capacity but caps other Phase Four industries (low-risk arts and entertainment businesses) at 25 percent capacity would cut the projected number of infections between 6 and 33 percent. Currently, New York State’s New York Forward plan has no capacity restrictions for schools.
The researchers evaluated the benefits of an adaptive PAUSE that would re-implement social distancing measures after exceeding a set threshold of COVID-19 hospitalizations and loosened again when hospitalizations decline below a second threshold for two weeks (details on the thresholds are outlined in the reports). Under most transmission scenarios, re-PAUSE would be needed to avoid overwhelming healthcare systems. When enacted, adaptive re-PAUSE would reduce COVID burden (including infections, hospitalizations, and deaths) by 16 to 49 percent compared to no rollback. Even so, the researchers project many new infections and deaths in the coming months under most scenarios.
If the city caps all industries including schools at 50 percent capacity and implements adaptive PAUSE, assuming a 10 percent reduction in transmission (early data suggest a 5-10 percent reduction thanks to the City’s new Test & Trace program), the model projects that 7.3 percent of the population would be infected, with 23,600 hospitalizations and 9,700 deaths between now and May 31, 2021. The number of weeks needed to be on PAUSE would be three weeks in the winter during the holiday season starting the week of December 27.
“We showed that keeping all industries, including schools at 50 percent capacity, plus universal mask wearing, as well as further reduction in transmission from testing and contact tracing, and social distancing, the city might be able to keep transmission at relatively low levels through the end of May 2021 with minimal time on re-PAUSE,” noted lead researcher Wan Yang, PhD, assistant professor of epidemiology at Columbia Mailman School.
The researchers have been working on modeling analyses weighing policy decisions over the last two months. In a May 26 report, they tested different timing of reopening, along with multiple factors like seasonality that could contribute to the epidemic dynamics. A wintertime seasonality similar to other human coronaviruses would likely lead to epidemic surge starting the fall and peak in December and January.
In a June 3 report, they tested different rollback policies in case of large surges in hospitalizations following re-opening. They showed that when there is already widespread community transmission, slow rollback (e.g. only closing bars) likely would not be able to slow transmission and hospitalization surge sufficiently. Rather, immediate and strictest restrictions (e.g. PAUSE in New York) would likely be needed to prevent overwhelming healthcare systems.
In the first two reports, the researchers tested phased reopening with full capacity (e.g. businesses opening at 100%) and showed that it would lead to large epidemics two to three months after reopening, as well as further surges in the winter. Based on these reports, they concluded that scaled-back liberalization of commercial social distancing along with adaptive re-PAUSE would likely both be needed to keep New York City open as long as possible.
About the Model and Its Uncertainties
During the pandemic, the Columbia Mailman School of Public Health and the New York City Department of Health and Mental Hygiene have been collaborating in generating real-time computer model projections in support of the city’s pandemic response. Weekly projections are posted on Github. In the current analysis, the researchers projected outcomes using historical data on COVID cases and deaths and mobility in New York City with various assumptions on seasonality, immunity (~3 years), social distancing (mask wearing, etc.), and transmission reductions due to contact tracing and onsite preventive measures. The projections did not account for potential increased transmission in school settings and Phase Four industries.
Study authors include Wan Yang, Sasikiran Kandula, and Jeffrey Shaman of Columbia University Mailman School of Public Health.