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Two US Studies Link Social Measures and Masks to COVID Control
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Mark Mascolini
Two US studies using different methods confirmed statistical links between social distancing, similar measures, and falling SARS-CoV-2 transmission or new COVID-19 cases across the country [1,2]. One study tied wearing masks to fewer COVID-19 cases [2]. Both studies appear as medRxiv preprints that have not been peer-reviewed.
Evidence from Germany suggests that wide SARS-CoV-2 testing, contact tracing, and social distancing can control the COVID-19 epidemic and even allow a gradual return to social and economic commerce [3]. Are the same measures—or at least some of them—working in the United States? Separate studies at Mount Sinai in New York City [1] and by a Chinese/US team [2] found statistical links between stay-at-home orders, social distancing, wearing masks, and COVID control. Until these studies appeared, estimates of how social measures affect the US epidemic came from modeling studies rather than actual nationwide data.
To standardize the stage of COVID-19 spread in each state, the Mount Sinai team started its statistical clock in each state and Washington, DC when each reached 500 COVID-19 cases [1]. From that point they estimated SARS-CoV-2 transmission as time-varying reproduction number (Rt) in the following week and the doubling time from 500 to 1000 cases. They assessed the impact of various social nonpharmaceutical interventions in linear and logistic regressions adjusting for population density, gross domestic product (GDP), and certain health metrics. An Rt above 1.0 means the epidemic is growing; an Rt below 1.0 means the epidemic is waning.
The analysis included 49 states and Washington, DC, 15 of which had stay-at-home orders when they reached their 500th COVID-19 case, and 34 of which did not. Compared with states without the following distancing measures, those with each measure had a significantly lower Rt: stay-at-home order preceding 500th case (beta = -0.15, 95% confidence interval [CI] -0.23 to -0.07, P < 0.001), educational facilities closure (beta = -0.17, 95% CI -0.30 to -0.05, P = 0.009), nonessential business closure (beta = -0.13, 95% CI -0.30 to -0.05, P = 0.002), and average percent time spent at home the week before (beta = -0.02, 95% CI -0.02 to -0.01, P < 0.001).
Stay-at-home states were 93% less likely to have an Rt above 1.0 (odds ratio [OR] 0.07, 95% CI 0.01 to 0.37, P = 0.004). Stay-at-home orders also correlated with a longer time to double from 500 to 1000 COVID-19 cases (OR 0.35, 95% CI 0.17 to 0.72, P = 0.004). States in the highest quartile of average percent time spent at home were 82% less likely to reach 1000 cases than states in the lowest quartile (hazard ratio 0.18, 95% CI 0.06 to 0.53, P = 0.002).
The Mount Sinai team determined that stay-at-home orders—and specifically adherence to stay-at-home orders—had the biggest impact on SARS-CoV-2 transmission. "As states aim to step down from such policies," they caution, "metrics of disease transmission should be carefully monitored to limit recurrent outbreaks."
A team of researchers in China and the United States used a different approach to gauge the impact of social directives on reining in the US COVID-19 epidemic [2]. They plumbed COVID-19 Tracking Project data [4] on US residents affected by stay-at-home and face-masking policies to calculate turning points in daily new COVID-19 cases and deaths and COVID-19 reproduction number (Rt). The analysis focused on people in 50 states and Washington, DC who had COVID-19 or died from the infection from March 1 to April 20, 2020. The researchers used multivariable piecewise log-linear regression analyses to estimate turning points in numbers of cases or deaths.
Stay-at-home orders began in the United States on March 19, 2020 in California, representing 12% of the US population, and plateaued on April 7 at 29.1 million people representing 88.6% of the population. The researchers determined that daily COVID-19 cases began to fall significantly on March 23 (P < 0.001), the day at which 10 states had implemented stay-at-home orders. Daily cases reached another downward inflection point on April 3 (P < 0.001), the day when the Centers for Disease Control and Prevention (CDC) recommended face masks for all. Additional analysis identified two downward turning points in daily COVID-19 deaths with a lag time after the new-case turning points.
Estimates of Rt started to fall on March 19, when California issued its stay-at-home order, and declined faster after the March 23 turning point. After a short plateau, Rt resumed its fall after April 3 and dropped to about or below 1.0 on April 13.
References
1. Dreher N, Spiera Z, McAuley FM, et al. Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States. medRxiv preprint. 2020. doi: https://doi.org/10.1101/2020.05.01.20088179. (This preprint report has not been peer-reviewed.)
2. Xu J, Hussain S, Wei S, et al. Associations of stay-at-home order and face-masking recommendation with trends in daily new cases and deaths of laboratory-confirmed COVID-19 in the United States. medRxiv preprint. 2020. https://doi.org/10.1101/2020.05.01.20088237. (This preprint report has not been peer-reviewed.)
3. Bennhold K, Eddy M. Germany's reopening offers hope for a semblance of normal life. New York Times. May 6, 2020. https://www.nytimes.com/2020/05/06/world/europe/germany-merkel-coronavirus-reopening.html
4. The COVID Tracking Project. 2020. https://covidtracking.com/.
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