Objective Social distancing is one of the main non-pharmaceutical interventions used in the control of the COVID-19 pandemic. This scoping review aims to synthesise research findings on the effectiveness of different types and levels of social distancing measures in the earlier stage of COVID-19 pandemic without the confounding effect of mass vaccination.
Design Scoping review.
Data sources MEDLINE, Embase, Global Health and four other databases were searched for eligible studies on social distancing for COVID-19 published from inception of the databases to 30 September 2020.
Study selection and data extraction Effectiveness studies on social distancing between individuals, school closures, workplace/business closures, public transport restrictions and partial/full lockdown were included. Non-English articles, studies in healthcare settings or not based on empirical data were excluded.
Results After screening 1638 abstracts and 8 additional articles from other sources, 41 studies were included for synthesis of findings. The review found that the outcomes of social distancing measures were mainly indicated by changes in Rt, incidence and mortality, along with indirect indicators such as daily contact frequency and travel distance. There was adequate empirical evidence for the effect of social distancing at the individual level, and for partial or full lockdown at the community level. However, at the level of social settings, the evidence was moderate for school closure, and was limited for workplace/business closures as single targeted interventions. There was no evidence for a separate effect of public transport restriction.
Conclusions In the community setting, there was stronger evidence for the combined effect of different social distancing interventions than for a single intervention. As fatigue of preventive behaviours is an issue in public health agenda, future studies should analyse the risks in specific settings such as eateries and entertainment to implement and evaluate measures which are proportionate to the risk.
- Infection control
- Public health
Data availability statement
Data are available on reasonable request. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Strengths and limitations of this study
First scoping review to synthesise findings on the effectiveness of social distancing measures for COVID-19 at individual, community and national levels and social settings assessed by different outcome parameters.
This review analyses the level of evidence for different types and levels of social distancing measures.
Findings in varied outcome parameters could not be compared directly.
Non-English literature was excluded from this review.
Social distancing is one of the main non-pharmaceutical interventions (NPIs) to control the outbreak of COVID-19 worldwide. Social distancing, also known as physical distancing, is based on the premise that the rate of transmission of infectious diseases will decrease if people in communities stay at home from work or school, avoid large gatherings and refrain from having physical contact with each other. WHO guidelines describe social distancing measures at the individual level (eg, keeping at least one metre from each other) and the community level including stay-at-home recommendation/ordinances and measures in specific socioeconomic settings (eg, workplace, schools, eateries, entertainment and parties).1 2 At the national or regional levels, lockdown (also called ‘community quarantine’ to restrict movement of population groups) may be imposed as an extreme form of social distancing,3 4 where it can be a total or partial lockdown to restrict key socioeconomic activities.5
Despite the fact that social distancing measures have become a crucial strategy globally in mitigating COVID-19 pandemic, the evidence for their effectiveness is just slowly accruing. Earlier studies applied mathematical modelling to predict effectiveness of social distancing measures.6–9 Recent studies evaluated the outcomes retrospectively using empirical data and reported the outcomes within specific parameters. A study which analysed data from 149 countries suggested that implementation of different social distancing interventions was associated with an overall reduction in COVID-19 incidence of 13% (incident rate ratio, IRR 0.87, 95% CI 0.85 to 0.89).10 It concluded that data from 11 countries indicated similar overall effectiveness (pooled IRR 0.85, 95% CI 0.81 to 0.89) when school closures, workplace closures and restrictions on mass gatherings were in place.10 The European Centre for Disease Prevention and Control (ECDC) also estimated the effectiveness of different types of social distancing in Europe. While most were based on prediction modelling, some retrospective analyses showed that lockdown reduced Rt from around 2.7 to 0.6 in the UK.11 Given different types, variations and combinations of social distancing measures were implemented at different levels in different jurisdictions and pandemic contexts, it is important to study what parameters and methods were used and what outcomes were measured in various research studies. This is critical in a protracted pandemic after continuing restrictions to individual movement and socioeconomic life, which have led to fatigue in preventive behaviours. In this context, targeted measures which have been evaluated to be proportionate to the risks should motivate continuing preventive behaviours.
This study aims to synthesise research findings on the effectiveness of different types and levels of social distancing measures during earlier stage of the COVID-19 pandemic. The study was conducted as a scoping review to include a broad range of outcome parameters and study designs. This enables a better understanding of the effectiveness of the spectrum of social distancing measures in controlling the COVID-19 pandemic.
The scoping review method was applied to include a range of parameters relating to effectiveness of social distancing measures during the COVID-19 pandemic. In contrast to a systematic review which answers a specific and narrow question, a scoping review aims to explore a set of emerging and diverse themes to synthesise the current evidence, clarify conceptual parameters and identify gaps for further research.12–14
Inclusion criteria for this review were studies that described: (1) effectiveness or outcomes of social distancing measures targeting the general public; (2) social distancing measures including those between individuals; targeted measures including closures of schools, workplaces, restaurants, bars and other social settings; stay-at-home recommendation/ ordinances, community quarantine and lockdown; and (3) quantitative research, secondary data analysis, modelling studies based on empirical data and review articles.
Exclusion criteria were: (1) qualitative studies, commentaries, mini-reviews without search strategies, editorials, conference presentations, dissertations and book chapters); (2) non-English articles; (3) studies in healthcare settings, such as those on healthcare workers, hospital patients and elderly nursing homes; (4) studies on the impact of social distancing measures on non-COVID-19 disease management and psychosocial health of the public and (5) hypothetical/stimulation models predicting future trends of incidence.
Search strategies and study selection
Seven electronic databases including AMED, Embase, Global Health, MEDLINE, Ovid Nursing Database, APA PsycINFO, Social Work Abstracts were searched by an experienced team member in scoping and systematic reviews. The search period was from the inception of the databases to 30 September 2020. To enhance sensitivity, syntax of “COVID*“.m_titl. AND social distan*.ab and “COVID*".m_titl. AND physical distan*.ab were used as search strategies to cover both terms of social distancing and physical distancing. Additional syntax of “SARS-CoV-2*".m_titl. and (social distan* or physical distan*).ab. were used to search for articles using the keyword ‘SARS-CoV-2’. Details are shown in the online supplemental file 1. Furthermore, backward searches from the reference lists of the articles were conducted to locate additional articles and reports. The search and selection process followed the Joanna Briggs Institute Methods Manual for scoping reviews, and the reporting was guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Extension for Scoping Reviews (PRISMA-ScR).15 Two reviewers independently screened the titles and abstracts to assess their eligibility. Full texts of potential citations were retrieved for detailed examination. Selection discrepancies were settled through discussions between these two reviewers. Any outstanding disagreements were resolved by consulting the third member. We did not conduct risk of bias assessment, which is consistent with recommendations from the Joanna Briggs Institute Scoping Review Methods Manual and PRISMA-ScR,15 as different from a systematic review, a scoping review aims to provide an overview of the existing evidence comprehensively, regardless of risk of bias of included studies.15
Data extraction and synthesis
For each study included, texts under the headings of ‘results’ or ‘findings’ were extracted and analysed by two reviewers. The analysis was performed by one reviewer and verified by a second reviewer. The two reviewers reached consensus on the outcomes reported and their classification to corresponding types of social distancing and effectiveness indicators.
Patient and public involvement statement
It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research.
Study selection and characteristics
We screened 1638 abstracts from our electronic search on the databases with 2 additional research reports identified from governmental websites. Of the 120 full texts retrieved for further assessment, 35 articles fulfilled our eligibility criteria. In addition, 6 relevant studies were identified from the reference lists of the articles through backward searches. Hence, in total, 41 studies were included in this review. Figure 1 presents results of the literature search and classification flow, and table 1 provides detailed characteristics of the selected articles.
There were 38 research studies and 3 reviews. Fourteen studies reported data from North America, another 13 from Asia, 12 from Europe, 3 from South America and 2 from Australia. There were also 3 global studies which reported data from over 50 countries in multiple regions. According to the classification by World Bank, 63.5% of the studies were from high-income countries/regions; 30.8% and 5.8% were from middle-income and low-income countries/regions, respectively.
Table 2 summarises the key findings based on the following effectiveness indicators: (1) Infectivity: Rt, effective reduction number; (2) Incidence: infection incidence, ratio of incidence rate, attack rate or bed occupancy rate; (3) Mortality or fatality rate; (4) Effect time: action and effect duration, time of reaching peak; (5) Attendance percentage of location, daily vehicles miles, daily contact frequency, mobility of leaving home, or travel distance. A description of each type of intervention is also given. A tick “✓” is put if no detailed elaboration was provided in the reviewed articles.
Social distancing at individual level
Social distancing was usually achieved by prohibition of mass gathering in public areas and/ or maintaining certain physical distance between people. Most studies reported a relationship between the transmission risk and the level of social distancing. A meta-analysis including seven studies on COVID-19 concluded that physical distancing of 1 m or more was effective in reducing the transmission risk by five times and the protective impact was double for every extra metre.16 Similarly, based on the chronological data on interventions in 41 countries between January and May 2020, Brauner et al17 estimated that Rt reduced by 36%, 28% and 12% when gatherings were limited to 10, 100 and 1000 people, respectively. Furthermore, studies found how mobility changed according to different social distancing measures. A study by Weill et al18 in the US.Afound that median distance travelled, retail and recreation locations visited by a mobile device per day showed a sharp decrease in March 2020 after implementation of social distancing measures in the country, with the percentage of the population completely staying at home doubled. Similar results showed that a decline in visits to non-essential businesses following the implementation of social distancing was associated with a reduction in estimated Rt.19 In the analysis of 211 US counties, visits to nonessential businesses reduced by 50% and 70% contributed to a 45% decline in Rt and a drop of Rt to a threshold of 1.0, respectively, indicating that the larger the drop in nonessential business visits, the more significance in the reduction of a Rt.19 Another US study by Clipman et al,20 in Maryland, found that a history of COVID-19 infection was significantly less likely among the public who always practised social distancing (adjusted OR for indoor social distancing, 0.32 (95% CI 0.10 to 0.99]; adjusted OR for outdoor social distancing, 0.10 (95% CI 0.03 to 0.33)), giving indications of the effect of mobility on the pandemic. It was consistent with the inference by Lemaitre et al21 who found a strong support for changes in R0 following the mobility decline before implementation of school closure, underlining the importance of behaviour changes on the reductions in transmission. However, social distancing in different settings may have different impact. The UK Scientific Advisory Group for Emergencies (SAGE) meeting report22 suggested that stopping contact from different households would provide moderate impact by reducing Rt of 0.1–0.2 but the impact of physical distancing on outdoor gathering was minimal (Rt reduction <0.05) since good ventilation was usually observed.
Social distancing at level of community settings
School closure may have benefits during the pandemic, but the effectiveness was mixed when considering level of closures and the unexpected link between school closure and reopening. Rivkees’s23 study in Florida of the USA found that closing schools resulted in a 40%–55% reduction in average distance travelled compared with preoutbreak levels. Moreover, Auger et al24 found that the primary and secondary school closure in the USA between March and May 2020 was associated with decreased COVID-19 incidence (adjusted relative change per week, −62%) and mortality (−58%). On the other hand, the SAGE report22 suggested that closing secondary schools and further education could have greater impact, even though a moderate Rt drop of 0.1–0.5 was associated with mass school closure, as mature students worked in daytime and linked up infection pathways between workplace and households. It was also observed that states closing schools earlier, when cumulative incidence of COVID-19 was low, had the largest relative reduction in incidence and mortality, although there might be confounding effects from other interventions.25 Contrary to expected impacts of school closures, observational data in ECDC review suggested that reopening schools had not been associated with significant increases of community transmission.11 In other studies26 27 that focused on the various measures used in educational and children care centre settings after reopening, the results showed a low incidence rate in these settings. There was a decreasing trend of both the average outbreak numbers and the cases per outbreak by school measures and might be partially due to the extensive measures. However, the specific impact of reduction of face-to-face attendance in classrooms was not assessed.28
Workplace measures include work-from-home arrangement, measures in working environment and closure of businesses. The SAGE report22 suggested a moderate impact of work from home measure, with a reduction of Rt between 0.2 and 0.4. Brauner et al17 estimated that a 29% Rt reduction was likely to follow with closing most of non-essential businesses, while closing high risk businesses, for example, bars and restaurants would be associated with a Rt decline of 20%. Although there was limited empirical data on the impact of closure of businesses, reduced visits to nonessential businesses in the USA was associated with a drop in Rt.19
Public transport restriction
Public transport restriction refers to suspension/limitation of intracity or intercity public transportation. The SAGE report22 suggested a low to moderate impact following the 5 mile travel restriction, especially when local outbreak was widespread. It might be because crowding in public transport was low and mandated face mask policy had already been implemented. However, Islam’s study10 showed no difference in reduction with or without the suspension of public transportation. On the other hand, ECDC review showed contradictory results, with a modelling study indicating a strong association with reduction of Rt while other studies did not show any impact unless introduced with other NPIs such as social distancing and behavioural changes.11 Therefore, it is difficult to relate observed changes in transmission dynamics to this single measure of public transport restriction.
Social distancing at national/regional level
Combination of interventions: partial lockdown
While the studies mentioned above focused on the effect of single type of intervention, many studies showed the effect of a combination of interventions, which could be regarded as a partial lockdown. A study by Siedner et al25 in the USA found that the mean daily COVID-19 case growth rate fell by 0.9% per day, starting 4 days after implementation of the first statewide social distancing measures including cancellation of public events, travel restriction, school and workplace closures. In a study by Randhawa et al,29 the SARS-CoV-2 positivity rate in Seattle-area outpatient clinics and emergency departments declined from the peak range of 14.3%–17.6% to 3.8%–3.9% after statewide physical distancing measures, such as shutdown of bars/restaurants, implementation of social gathering limits and stay-home orders. A drop of 2% in daily COVID-19-attributed mortality growth rate was also observed 7 days after the measures were implemented. Similarly, a study by Wan et al30 in Mainland China excluding Hubei (province of Wuhan) found that Rt had dropped sharply from 3.34 on 20 January 2020 to 0.89 on 31 January 2020 after implementing integrated control strategies. In Du’s study31 of 58 cities in China, also with a remarkable Rt reduction, at 54.3%, demonstrated the effectiveness after the implementation of multiple types of interventions.
A full lockdown can be viewed as a combination of all measures. Islam et al10 reported a combination of 4 measures, including restrictions on mass gatherings, school closures, workplace closures, and lockdowns in 32 countries, were associated with decreasing incidence of COVID-19 (pooled IRR 0.87, 95% CI 0.84 to 0.91). Similar declining incidence was observed when public transport closure was added (pooled IRR 0.85, 95% CI 0.82 to 0.88; n=72 countries). Other than incidence reduction, bed occupancy could also be benefited from lockdown measures. In Lino’s study,4 before the lockdown, the bed occupancy rate for referred COVID-19 cases in a tertiary hospital in Fortaleza of Brazil was over 100% in the beginning of May and reached nearly 140% after 10 days. The rates decreased to below 100% and 85% at 14 and 23 days, respectively, after the lockdown.
There was more evidence showing the effect of lockdown with various indicators. Zhang et al32 found that an average daily number of contacts per survey participant significantly dropped from 14.6 to 2 and 18.8 to 2.3 in Wuhan and Shanghai, respectively, during the lockdown period, consistent with the respective trends of mobility data declining at 86.9% and 74.5%. Pan et al33 analysed data from Wuhan and found that the Rt gradually reduced from greater than 3 in January 2020 to less than 1 in February 2020 and fell further to less than 0.3 in March 2020 after the city lockdown. Lim et al34 studied 9 Southeast Asian countries found a large variation in social distancing policies across countries, leading to marked differences in the reduction in Rt, with the biggest decrease in Malaysia from 3.68 to 1.53 and the smallest decrease in Laos from 1.55 to 1.20. Similarly, a brief report from Rivkees and Roberson23 showed that the stay-at-home order in Florida of the USA, after the first month of implementation, resulted in a 74%–82% reduction in person-to-person encounters, 55% in visits to non-essential venues and 45% in overall distance travelled. After 2 months of implementing stay-at-home order, the average distance travelled within the state was also found to decrease by 25%–40%. Further, a modelling study of Brauner et al17 gathering data of 41 countries using NPIs estimated that stay-at-home orders (with exemptions) reduced the mean percentage of Rt by 10%. Moreover, in a SAGE report,22 it was suggested that country lockdown was impactful and could reduce Rt from 2.7 to 0.6 while 2–3 week short stay-at-home order had moderate impact in reducing Rt to below 1. As with all other measures, the earlier the stay-at-home order was implemented, the higher the impact.
Implementation timing and impact on the pandemic curve
Nearly all findings found that a timely implementation of measures could reduce the transmission risk significantly. The relationships between the timing and the change in rates of daily conﬁrmed cases were analysed in a time series. Marschner35 used Australia data to back-project that there would be a fivefold increase in total infections if social distancing measures were delayed by 1 week. Consistently, in Du et al’s study,31 a 1-day delay in implementing the first intervention was expected to prolong an outbreak by 2.41 days. However, earlier lockdown, simulated by Islam et al,10 showed a larger reduction in COVID-19 incidence compared with a delayed one after other social distancing interventions were initiated. Another empirical study based on the Oxford COVID-19 Government Response Tracker36 tracked Rt temporally for 2 weeks following the 100th reported case in 140 countries and observed the median timing of implementation of measures across countries. The study found that lockdown measures and travel bans can be considered early if they were implemented around 2 weeks before the 100th case and a week before detecting the first case, respectively.36
In addition, social distancing measures had a progressive control impact on the growth rates of daily confirmed cases, with Courtemanche et al37 showing reductions of 5.4%, 6.8%, 8.2% and 9.1% after 1–5 days, 6–10 days, 11–15 days and 16–20 days, respectively, following the roll-out of the measures. The timing effect was further illustrated by Thu et al38 that social distancing interventions took 1–4 weeks to have an effect on the decline in number of infected cases among the 10 countries studied. Countries with higher growth rates at the beginning might have greater difficulties in controlling the transmission, and vice versa for those countries with initial lower growth rates. For example, China, Iran and Turkey, promulgating the most stringent level of social distancing measures, with initial infection growth rates apparently lower at around 60%–70%, had the highest decline rates at 71%, 51.8% and 50.8%, respectively, while the USA and the UK, having the highest initial growth rates (99.9%), experienced significantly lower decline rates of 14.8% and 25.9%, respectively. The result suggested that social distancing measures could be more effective when introduced earlier under situations with low growth rates.
This scoping review covered a board range of social distancing interventions and outcome indicators. A comparison of the key findings of different levels of measures is shown in table 3. Outcomes were mainly indicated by changes in Rt, incidence and mortality, along with indirect indicators such as daily contact frequency and travel distance. Based on changes in Rt, incidence and mortality, there was adequate empirical evidence for the effect of social distancing at the individual level, and for partial or full lockdown at the community level. However, for targeted measures in social settings, the evidence was moderate and inconsistent for school closure, and limited for workplace/business closures. There was no evidence for the effect of public transport restriction alone.
Many studies reported the combined effects of different social distancing interventions which were usually implemented as a package of 3–5 measures. Observed impact of a single measure in a social setting was scarcely reported or only demonstrated with modelling. For example, Islam et al10 reported that among 149 countries studied, 118 countries implemented 5 measures while 29 countries used 3 to 4 interventions, with only one country introducing 2 measures and the remaining one implementing a single measure. In addition, even though the lockdown, in this review, was shown to have the highest reduction in Rt, it had been implemented as multiple measures.
Apart from types of interventions, the relationship between implementation time points and the effect were also investigated. Lam et al39 observed an early public health measure promulgation was able to contain the epidemic in Hong Kong, without initiating extreme measures such as a city-wide lockdown. Other studies suggested that the effect time variation might be due to the different times and levels of promulgating the social distancing measures, making the effectiveness apparently different.38 It could be demonstrated in the comparison between countries that the stronger the level of social distancing, the faster it took to reduce the number of daily confirmed cases.38 Furthermore, high initial infection incidence due to late implementation of measures would reduce the effectiveness of measures.38 All these results indicated a need for a rapid response and stringent measures to win the battle.
In addition to the types, levels and timing of social distancing measures highlighted in this review, the effectiveness of measures was also affected by contextual factors such as compliance, social belief and cultural factors. Low public compliance may be a key explanation when interventions showed no sign of flattening of the epidemic curve. The compliance issue was further supported by Cruz’s study40 in examining the Social Distancing Index, a social distancing adoption index used by the Brazilian government found that it needed to be larger than 55% to reduce the daily death number. Moreover, social belief such as awareness of disease information might cultivate a sense of self-imposed initiation of handwashing, wearing protectives, keeping a distance from people and reducing outdoor activities. Cultural factors may also have an influence on public gatherings, although it was too complicated for a quantitative evaluation of the timing, magnitudes and processes that were prevalent in a region. Cultural factors were studied in Huynh’s study41 illustrating that countries with higher Uncertainty Avoidance Index (UAI) predicted a smaller proportion of people gathering in public such as in grocery and retail stores, pharmacies stores, recreation areas, public transport and workplaces, whereas countries in the northern European such as Finland, Sweden and Norway with lower UAI people were unlikely to follow social distancing measures. Furthermore, Islam’s study10 observed greater case reduction associated with those countries with a higher gross domestic product (GDP) per capita, a higher proportion of population aged 65 years or above, and stronger preparedness for the pandemic measured by the country health security index. Therefore, cultural determinants are likely to play an important role in compliance with preventive behaviours.
Knowledge gap for future research
Due to the heterogeneity of the outcomes adopted in the studies, it is difficult to render direct comparison of the changes in Rt and incidence. Consistent inclusion of these outcomes in studies of similar kinds may allow systematic review and meta-analysis in further studies.
Few studies have investigated the effect of closure of entertainment and eatery settings. The SAGE report22 suggested that closures of gyms, bars and restaurants were useful since there were environmental risks linked to higher probability of touch surfaces, higher aerosol generation and breathing rates due to aerobic activities. Specifically, the risk in bars and pubs was likely to be higher than many other indoor settings due to close proximity of people, long exposure duration, no wearing of face coverings and talking loudly. Some venues were poorly ventilated, especially in winter. In addition, consumption of alcohol impacts on customers’ behaviours. More empirical evidence focusing on the dynamic interaction of the environment, customer behaviours and transmission risks would be beneficial.
Some researchers proposed strategies need to be demonstrated by empirical evidence. A circuit breaker, proposed in the SAGE report,22 referring to as the 2–3 weeks short-time lockdown, could put the epidemic curve back by about 28 days or more. Based on historical evidence from the 1918 influenza pandemic, Correia et al42 argued that regions taking earlier and aggressive social distancing measures grew faster economically in the postpandemic period although there were adverse effects on the economy during the pandemic. Thus, predicting the recovery in an economy or a community based on the effectiveness of each intervention would be a continuing concern.
Fatigue of pandemic prevention was seen everywhere during the course of COVID-19 pandemic which may exacerbate the peaks and resurgence following the relaxation of measures and undermine the public acceptance to the advice from authorities. Governments with good risk communication with the public, hinging on engagement, communication and feedback, would be essential to help individuals assess and reduce their own risks appropriately. Abel et al43 reported that social distancing might lead to depression and anxiety in some people, which in turn would have an impact on social stability. Psychological impacts were not only observed on patients, healthcare workers but also on the overall population. However, Kim and Su44 suggested we should routinely provide psychological support instead of stopping social distancing measures. Future studies should explore the longer-term strategies for risk communication and risk analysis in specific settings to minimise public fatigue in compliance with social distancing mandates. Response measures should be proportional to the risk in different settings.
Our search period was up to 30 September 2020 when vaccine was not available for population use. For mass vaccination programmes which were implemented in most countries after December 2020.45 The reported number of cases per population was under 2.3% across countries. Including unreported asymptomatic cases, population immunity should still be insignificant during this period. However, this study period may have an advantage in excluding the confounding effect of population immunity and mass vaccination on the effects of social distancing measures. Future studies should explore whether the effect of social distancing declines as the degree of population immunity increases.
Although a lot of information on the measures taken was collected from government websites, measures implemented in small localities or regional areas were not widely publicised or difficult to access, resulting in relevant studies being limited. Moreover, there was a wide variation of testing accessibility and for the criteria who should be tested, in different countries. Similarly, the points of time of promulgation and severity level of interventions were different among countries. Therefore, the cumulative confirmed cases might not reflect the actual situation in the population and were not accurate for comparisons. Using a time series analysis referencing to the date of death but not to the date of testing might be under a possible variation of case reporting and might delay the reporting process for as long as 15 days. Another concern is that some studies used mobile devices for imputing people attendance changes in specific times and locations. The drawback was the characteristics of those persons using mobile devices such as age and gender were unknown. The data only tracked mobile devices but not persons, who might have multiple devices (eg, a phone and a tablet), or might not take their devices when they left home. Hence, the results might not reflect the actual mobility patterns. Finally, our review excluded non-English literature. The English literature of COVID-19 might be biased towards countries with good research capacity and interests in publishing their findings for an international audience.
Our review showed that the outcomes of social distancing measures were mainly measured by changes in Rt, incidence and mortality. There was empirical evidence for the effect of social distancing between individuals, and for partial or full lockdowns. However, the evidence was moderate for the separate effect of school closure and limited for workplace/business closures. There was no evidence for the separate effect of public transport restriction. In the community setting, there was more evidence for the combined effect of different social distancing interventions than for a single intervention. Apart from the effectiveness of the interventions, public compliance is another important issue. COVID-19 has been changing our lives and a new norm may emerge as we have to live with new variants of the virus, which may develop to a situation similar to that of the seasonal influenza, where a total elimination is not the goal. Fatigue of preventive behaviours is on the top of the public health agenda. Community compliance with social distancing measures is related to the population’s attitude to government policies, access/awareness of trustful sources of information, the initiations and maintenance of self-protective measures. Therefore, risk communication and risk analysis continue to be of cornerstone of public health measures and to address research gaps for implementing effective measures which are targeted and proportionate to the risk in different settings.
Data availability statement
Data are available on reasonable request. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Patient consent for publication
Ethical approval was obtained from the Survey and Behavioural Research Ethics Committee of the Chinese University of Hong Kong (Ref no. SBRE-19-595).
The Centre for Health Systems and Policy Research funded by The Tung Foundation is acknowledged for the support throughout the conduct of this study.
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
KSS and TSML are joint first authors.
Contributors EKY designed the study, applied for the grant and made major contributions to writing the manuscript. VCHC, EKY, KSS and CTH managed the review methodology. TSML, KSS and YSL conducted the review and data synthesis. TSML, KSS, EKY, CHKY and CTH wrote the first draft of the manuscript. All authors read, revised and approved the final manuscript. EKY is responsible for the overall content as guarantor.
Funding This study was funded by Commissioned Research on the Novel Coronavirus Disease (Ref.: COVID190105) of the Health and Medical Research Fund, Food and Health Bureau, Hong Kong SAR Government.
Disclaimer The funder had no role in the study design, collection, analysis, and interpretation of data, or in writing the manuscript.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.