key: cord-1049857-6mfehmv7
authors: Qureshi, Adnan I.; Suri, M. Fareed K.; Chu, Haitao; Suri, Habibullah Khan; Suri, Ayesha Khan
title: Early Mandated Social Distancing is a Strong Predictor of Reduction in Peak Daily New COVID-19 Cases
date: 2020-10-21
journal: Public Health
DOI: 10.1016/j.puhe.2020.10.015
sha: eb0375bcbb27c5be6e38674ecf0aeb51adf8b78d
doc_id: 1049857
cord_uid: 6mfehmv7

Objectives Mandated social distancing has been applied globally to reduce the spread of coronavirus disease 2019 (COVID-19). However, the beneficial effects of this community-based intervention have not been proven or quantified for the COVID-19 pandemic. Study design Regional population-level observational study. Methods Using publicly available data, we examined the effect of timing of mandated social distancing on the rate of COVID-19 cases in 119 geographic regions, derived from 41 states within the US and 78 other countries. The highest number of new COVID-19 cases per day recorded within a geographic unit was the primary outcome. The total number COVID-19 cases in regions where case numbers had reached the tail end of the outbreak was an exploratory outcome. Results We found that the highest number of new COVID-19 cases per day per million persons was significantly associated with the total number of COVID-19 cases per million persons on the day before mandated social distancing (β = 0.66, p < 0.0001). These findings suggest that if mandated social distancing is not initiated until the number of existing COVID-19 cases has doubled, the eventual peak would result in 58% more COVID-19 cases per day. Subgroup analysis on those regions where the highest number of new COVID-19 cases per day have peaked increased β to 0.85 (p < 0.0001). The total number of cases during the outbreak in a region was strongly predicted by the total number of COVID-19 cases on the day before mandated social distancing (β = 0.97, p < 0.0001). Conclusions Initiating mandated social distancing when the numbers of COVID-19 cases are low within a region significantly reduces the number of new daily COVID-19 cases and perhaps also reduces the total number of cases in the region.

Quarantine and isolation are standard procedures to avoid transmission of infectious disease from infected to non-infected persons and have been used in numerous epidemics. 1 Mandated social distancing comprises of a combination of travel restrictions, closure of nonessential group meeting venues (e.g. restaurants, schools, shops) and steps to avoid close contact at essential meeting venues (e.g. hospitals, food supply, pharmacies). Mandated social distancing is also referred to as 'societal lockdown' and will have a variable impact on the spread of disease depending upon the mode of disease transmission, and ability to identify and isolate persons infected with the disease. 2 Critical analysis of mandated social distancing in 17 cities in the US during the 1918 pandemic (caused by H1N1 influenza A virus) found that cities that mandated social distancing at an early phase of the epidemic had peak death rates 50% lower than in those cities that did not implement such early interventions. 3 Although results from the 1918 pandemic, influenzae pandemics and SARS have been used to justify mandated social distancing in various parts of the world, limited analysis of the effect of mandated social distancing on the COVID-19 pandemic are available. The value of mandated social distancing requires a critical assessment for each pandemic because of inadvertent adverse psychological and health consequences on individuals 4,5 and financial effects on society. 6 We examined the effect of timing of mandated social distancing on the rate of COVID-19 cases in 119 geographic regions, derived from 41 states within the US and 78 other countries.

Daily cumulative COVID-19 case numbers for individual regions (countries and individual states within the US) from 22 January, 2020, are publicly available. 7, 8 The start dates of mandated J o u r n a l P r e -p r o o f social distancing for different regions have been compiled and are also available. 9 For this analysis, only regions that had data for both mandated social distancing start dates and daily cumulative case volumes for COVID-19 were included. For the US, data were available for each state, thus allowing a detailed analysis. In countries other than the US, we used national mandated social distancing start dates and national COVID- 19 We used the total number of COVID-19 cases per million on the day before mandated social distancing was implemented as the independent variable and predictor for the analysis. The peak of the smoothed curve was used to determine the highest number of new COVID-19 cases per day (expressed in per million persons) and was used as the dependent variable. Due to the skewness in both the dependent and independent variables, log transformation was applied. To determine if the number of daily new cases had plateaued or was still increasing, linear regression for the previous 13 days was used. The previous 13 days was selected after visually checking the trend for all geographic regions and repeating linear regression for various intervals, ranging from 5 to 13 days. Linear positive trend for the previous 13 days (12-25 April) correlated best with visual interpretation of an upward trend. For regions where the average (over the last 5 days) daily new case volume had trended down to less than 20% of the peak daily new case volume (considered here as reaching the tail end of the epidemic), linear regression analysis was performed to predict the overall number of new COVID-19 cases per million from the total number of COVID-19 cases per million persons on the day before mandated social distancing after log transformation of both variables.

Initiation dates of mandated social distancing were available for 85 countries and 42 US states.

Daily COVID-19 case volume data were available for 183 countries and all 52 US states. Both Results of the linear regression analyses with different models are reported in Table 1 . In Model A, the highest number of new COVID-19 cases per day was significantly associated with the total number of COVID-19 cases on the day before mandated social distancing (β = 0.66, p < 0.0001). Model B improved the adjusted R 2 from 0.59 to 0.72, but did not change the β for total number of COVID-19 cases on the day before mandated social distancing. Subgroup analyses on those regions where the daily new COVID-19 cases had already peaked, increased β for the total number of COVID-19 cases on the day before mandated social distancing to 0.85 for both the unadjusted and adjusted models (p < 0.0001).

Similar results from analyses for states within the US are reported in Table 2 (Table 2) .

Internationally, there was a strong association between the highest number of new COVID-19 cases per day and the total number of COVID-19 cases on the day before mandated social distancing both in the unadjusted and adjusted models ( Table 3 ). This association was stronger for countries where the number of new COVID-19 cases per day had already plateaued (β = 0.88, p < 0.0001).

Addition of individual elements of mandated social distancing (e.g. closure of educational institutes, public transport, restaurants and other shops) did not affect the association between the highest number of new COVID-19 cases per day and the total number of COVID-19 cases on the day before mandated social distancing. Visually, Australia appeared to have plateaued; however, based on a positive trend over the last 13 days of regression, it was classified as not plateaued. The analysis of plateaued regions was repeated after manual addition of Australia and no change in the above results was noticed.

For 17 regions (including 3 states within the US), the daily new case volume reduced to less than 20% of the peak daily new case volume. Log-transformed total number of cases was strongly predicted by the total number of COVID-19 cases on the day before mandated social distancing (adjusted R 2 0.87, F = 112, β = 0.97, p < 0.0001).

This study confirmed the benefit and provided a quantitative estimate of the value of 

Province found that 59 (12.6%) of the 468 patients developed symptoms before the potential source developed symptoms, suggesting that transmission occurred in the prodromal period. 28 There have been small case studies highlighting that COVID-19 can be acquired from patients who are and will remain asymptomatic. 29-31 The estimated proportion of asymptomatic COVID-19 was 17.9% based on screening of travellers on board a cruise ship 32 and 30.8% from data of Japanese citizens evacuated from Wuhan. 33 However, the viral loads in the upper respiratory specimens appeared to be similar in symptomatic and asymptomatic persons. 34 It is possible that the beneficial effect of mandated social distancing may to related to reducing contact between asymptomatic individuals infected with SARS-CoV-2. Another unique aspect of SARS-

CoV-2 is its ability to persist on various surfaces and thus be transmitted by indirect contact from high-touch surfaces. 35,36 SARS-CoV-2 can persist on plastic, stainless steel, copper and cardboard, and viable virus has been detected up to 72 hours after application to these surfaces. The longest viability was on stainless steel and plastic; the estimated median half-life of SARS-CoV-2 is approximately 5.6 hours on stainless steel and 6.8 hours on plastic. Therefore, the mandated social distancing is likely to reduce contamination and transmission from hightouch surfaces within society.

One of the limitations of the current model is the variability in policies pertaining to mandated social distancing and compliance to the policies in various geographic regions. Mandated social distancing has several facets, which include: special precautions on travel on public transit, rideshares, or taxis; only operating essential businesses, such as grocery stores, gas stations and banks; closure of non-essential businesses; using drive-thru, curbside pick-up or delivery services; prohibiting events and gatherings of more than 10 people; maintaining distance (approximately 6 feet or 2 meters) from others when possible; avoid eating or drinking at restaurants, bars or food courts; closing of schools and non-essential factories and work places;

and limiting the number of patrons at retail shops. Compliance with mandated social distancing is an important factor in determining success of the intervention. 1 There is also variability in exposure risk reduction within a given population, as each individual does not have the same chance of coming in contact with others. 26 There appears to be a difference exposure risk according to age of the individuals 37 and population structure such as number of households, workplaces, schools and community groups. 38 Differences in age and population structure between geographic regions may also confound the results.

There is also a confounding effect of case identification and isolation, and robustness of testing for asymptomatic individuals, which may vary in different geographic units in the current analysis. The Center for Disease Control and Prevention (CDC) concluded that the degree to which COVID-19 cases might go undetected or unreported varies in geographic regions because testing practices differ widely and might contribute significantly to the observed variations. 39, 40 For example, the state of New York (excluding New York City) reported administering 4.9 tests J o u r n a l P r e -p r o o f per 1000 population, which was higher than the national average of 1.6 (CDC, unpublished data, 25 March, 2020). The confounding effect of contact tracing and isolation was not analysed in the current study. There was variability between geographic regions in implementation of contact tracing and isolation. Contact tracing and isolation was also affected by the number of COVID-19 cases within a geographic region and may not be possible if the number of new cases exceeds a certain threshold due to limitations in resources. The socioeconomic status and location (urban versus rural) also influence access to health care and thus case identification and may alter the differences between various geographic regions.

The variability in the highest number of new cases per day that was not explained in the statistical models of the current study is likely due to variability in mandating social distancing in different regions. Although most of the organisations were closed during mandated social distancing, certain businesses, like meat and poultry processing facilities, were recognised as critical for infrastructure and permitted to continue work with precautions. Outbreaks in such places resulted in increasing numbers of new cases per day that is not explained by the current model. 41, 42 It is also noted that in some regions (excluded from the analysis), the highest number of new cases per day plateaued prior to mandated social distancing. This suggests that there may be other mechanisms that can reduce the number of new cases in certain regions.

There were certain analyses that could not be performed for all the regions included in the current study as the pandemic is ongoing, with changing numbers of COVID-19 cases. In subgroup analysis, it was clear that the relationship was strongest when the highest number of new cases per day had reached its peak. Some regions were still in the period where the number of new cases per day is continuing to increase. It is also important to note that the total number of COVID-19 cases in a region can only be determined after the pandemic subsides. In total, only 17 regions in the current analysis were thought to be at the tail end of the pandemic Another issue is the re-emergence of COVID-19 (termed as the 'second wave') with relaxation of the mandated social distancing policy. Estimation of the impact of relaxation of the mandated social distancing policy is confounded by a staged and heterogenous set of policies, which make it difficult to identify a distinct effect. However, the differences in relaxation policies between regions may be correlated with regional re-emergence of COVID-19 to identify the most effective strategy for relaxation and termination of mandated social distancing.

The value of mandated social distancing in reducing the spread of COVID-19 has been questioned at multiple levels due to widespread inadvertent effects on individuals' wellbeing and the financial consequences on society. This study demonstrates that initiating mandated social distancing when smaller numbers of COVID-19 cases are present will reduce the highest number of new cases per day and perhaps even the overall total number of COVID-19 cases in the region, highlighting the importance of this community-based intervention. 

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None declared.J o u r n a l P r e -p r o o f