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Relaxing physical-distancing measures in the United States while there is still no COVID-19 vaccine or treatment could result in about the same number of infections as if distancing had never been implemented to begin with, according to a UCLA-led team of mathematicians and scientists.
The researchers compared the results of three related mathematical models of disease transmission that they used to analyze data emerging from local and national governments early in the pandemic, including one that measures the dynamic reproduction number — the average number of susceptible people infected by one previously infected person. The models all highlight the dangers of relaxing public health measures too soon.
“Distancing efforts that appear to have succeeded in the short term may have little impact on the total number of infections expected over the course of the pandemic,” says lead author Andrea Bertozzi, PhD, Distinguished Professor of Mathematics and holder of the Betsy Wood Knapp Chair for Innovation and Creativity in the UCLA College. “Our mathematical models demonstrate that relaxing these measures in the absence of pharmaceutical interventions may allow the pandemic to reemerge. It’s about reducing contact with other people, and this can be done with personal protective equipment as well as distancing.”
If distancing and shelter-in-place measures had not been taken in March and April, it is very likely the number of people infected in California, New York and elsewhere would have been dramatically higher, posing a severe burden on hospitals, Dr. Bertozzi says. But she notes that while short-term distancing can slow the spread of the disease, it may not result in fewer people becoming infected when not sustained.
Mathematically modeling and forecasting the spread of COVID-19 are critical for effective public health policy, but wide differences in precautionary approaches across the country have made it a challenge, says Dr. Bertozzi, who also is Distinguished Professor of Mechanical and Aerospace Engineering. Social distancing and wearing face masks reduce the spread of COVID-19, but people in many states have not followed distancing guidelines or worn masks — and the number of infections has continued to rise.
During the 1918 influenza pandemic, social distancing was first enforced and then relaxed in some areas. Dr. Bertozzi points to a study published in Proceedings of the National Academy of Sciences in 2007 that looked at several American cities during that pandemic where a second wave of infections occurred after public health measures were removed too early.
That study found that the timing of public health interventions had a profound influence on the pattern of the second wave of the 1918 pandemic in different cities. Cities that had introduced measures early in the pandemic achieved significant reductions in overall mortality. Larger reductions in peak mortality were achieved by those cities that extended the public health measures for longer. St. Louis, Milwaukee and Kansas City, for instance, had the most effective interventions, reducing transmission rates by 30-to-50 percent.
“During the 1918 influenza pandemic, the early relaxation of social-distancing measures led to a swift uptick in deaths in some U.S. cities,” Dr. Bertozzi says. “Our mathematical models help to explain why this effect might occur today.”
— Stuart Wolpert
“The Challenges of Modeling and Forecasting the Spread of COVID-19,” PNAS, April 15, 2020
Andrea Bertozzi, PhD