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Optimal strategies for COVID-19 prevention from global evidence achieved through social distancing, stay at home, travel restriction and lockdown: a systematic review

Abstract

Background

Coronavirus disease (COVID-19) is a global public health agenda with high level of pandemicity. There is no effective treatment, but prevention strategies can alter the pandemic. However, the effectiveness of existing preventive measures and strategies is inconclusive. Therefore, this study aimed to review evidence related to COVID-19 prevention achieved through social distancing, stay at home, travel ban and lockdown in order to determine best practices.

Methods/design

This review has been conducted in accordance with the PRISMA and Cochrane guideline. A systematic literature search of articles archived from major medical databases (MEDLINE, SCOPUS, CINAHL, PsycINFO, and Web of Science) and Google scholar was done. Observational and modeling researches published to date with information on COVID-19 prevention like social distancing, stay at home, travel ban and lockdown were included. The articles were screened by two experts. Risk of bias of included studies was assessed through ROBINS-I tool and the certainty of evidence was graded using the GRADE approach for the main outcomes. The findings were presented by narration and in tabular form.

Results

A total of 25 studies was included in the review. The studies consistently reported the benefit of social distancing, stay at home, travel restriction and lockdown measures. Mandatory social distancing reduced the daily growth rate by 9.1%, contacts by 7–9 folds, median number of infections by 92% and epidemic resolved in day 90. Travel restriction and lockdown averted 70.5% of exported cases in china and doubling time was increased from 2 to 4 days. It reduced contacts by 80% and decreased the initial R0, and the number of infected individuals decreased by 91.14%. Stay at home was associated with a 48.6 and 59.8% reduction in weekly morbidity and fatality. Obligatory, long term and early initiated programs were more effective.

Conclusion

Social distancing, stay at home, travel restriction and lockdown are effective to COVID-19 prevention. The strategies need to be obligatory, initiated early, implemented in large scale, and for a longer period of time. Combinations of the programs are more effective. However, the income of individuals should be guaranteed and supported.

Peer Review reports

Background

The emerging Coronavirus disease 2019 (COVID-19) is becoming a global public health agenda with high level of infectiousness and mortality [1,2,3]. It is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [2]. The disease novel coronavirus (formerly) was first identified in December 2019 in Wuhan, China, and has since spread globally and become a global pandemic [3,4,5,6]. The disease spread rapidly around the world, nearing 6 million confirmed cases and hundreds of thousands of deaths reported within a few months [5, 6]. Thirteen percent of the closed cohort and 2–5% of the total cohort were reportedly dead [5,6,7,8,9].

The full spectrum of COVID-19 ranges from subclinical infection to severe illnesses. More than 80% of cases remain asymptomatic and 15% of cases present with mild, self-limiting respiratory tract illness. While, the remaining 5% of individuals present with severe and complicated conditions such as: pneumonia, multi-organ failure, and death [1,2,3, 6,7,8]. Both asymptomatic and symptomatic cases can easily transmit the disease through direct and indirect contacts. Person-to-person transmissions primarily occur during close contact and with contaminated objects. It is most contagious during the first 3 days after the onset of symptoms [2, 7,8,9,10].

Different countries around the world have taken different preventive measures to try and keep the pandemic under public health control. Most countries implemented either of the following general strategies: complete or partial lockdown, travel ban, maintaining social distancing, frequent hand washing, maintaining physical distance, quarantine, covering coughs, and avoiding contamination of face with unwashed hands [1, 2, 7]. While, others were implemented none of these interventions or implemented in different ways [2,3,4,5,6]. Yet, the most efficient method is unclear [3,4,5,6,7].

Most of the recommended measures designed to prevent the infection were based on recommendations from researches conducted for SARS and MERS. Also the implementation strategies were based on the economic capacity of the specific country and the extent of the epidemic. This means, different countries implemented different preventive strategies differently. There is limited evidence on the effectiveness of these interventions implemented in different settings, in which the effect is not researched well [6,7,8,9].

There are a limited number of studies and to the extent of our search there is no a conclusive systematic review on the preventive aspects and effectiveness of COVID-19 infection through social distancing, stay at home, travel ban and lockdown strategies. The findings were inconclusive, in some studies certain prevention mechanisms shown to have minimal effects, while in other studies different preventive mechanisms have better effect than expected particularly for social distancing. On the other hand, some studies have reported that, integration of interventions is more effective than specific prevention strategies [1, 2, 4, 9].

Therefore, we aimed to conduct a comprehensive systematic review to determine the optimal preventive strategies achieved through social distancing, stay at home, travel ban and lockdown strategies. Hence, the synthesized analysis will be important to bring conclusive evidence. Hence, policy makers and other stakeholder will have clear evidence to make decisions in the preventive strategies of COVID-19 at the local and national context.

Objectives

To bring optimal evidence that can support the local and national COVID-19 prevention program, through a systematic review of researches conducted on evaluation of global strategies for COVID-19 prevention through social distancing, stay at home, travel ban and lockdown measures. We aimed to answer issues related to strategic implementation and effectiveness in the prevention of the disease or death. The following key questions were considered:

  • What is the optimal strategy in the implementation of social distancing, stay at home, travel ban and lockdown measures in different settings?

  • Are social distancing, stay at home, travel ban and lockdown measures effective to control the COVID-19 outbreak?

  • How and when these strategies should be applied to control the COVID-19 outbreak?

Methods and materials

The reviews were conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses: guidance for reporting of systematic reviews and Meta analyses) [11] and Cochrane hand book of systematic review [12] through a systematic literature search of articles published to date. We used researches conducted throughout the glob containing information on COVID-19 prevention through social distancing, stay at home, travel ban and lockdown. The review was conducted in accordance with the protocol developed prior to the actual research. However, the protocol was not published. We gave more emphasis on the publication of the research as it is important for designing interventions.

Eligibility criteria for the review

Researches conducted to assess the effectiveness of social distancing, stay at home, travel ban and lockdown measures for the prevention of COVID-19 were selected based on their evidence of reported outcomes relevance for decision making at local, national and international level.

Types of studies

In these reviews we included non-randomized observational studies conducted on COVID-19 prevention. In addition, we also included modelling (mathematical and/or epidemiological) studies, to supplement the existing evidence, as researches conducted on COVID-19 prevention are very limited.

We included Cohort studies, Case-control studies, Time series, Case series and Mathematical modelling studies conducted anywhere, any area and any setting reported in English language. Whereas; commentaries, letter to editor, case reports and governmental reports were excluded.

Types of participants

The participants were loosely selected. For each prevention method different participants were included. These include: individuals who have contact a confirmed or suspected case of COVID-19, or individuals who live in areas with COVID-19 outbreak; or individuals considered to be high risk for COVID-19/suspected cases, or confirmed/probable cases of COVID-19 infection. The number of participants varies according to the individual researches. We excluded individuals who have other symptomatic respiratory disease confirmed by tests.

Types of interventions

We included different types of interventions including: social distancing, stay at home, travel ban and lockdown measures for COVID-19 prevention applied specifically or in combination, either voluntary or mandatory and in different settings, either at a facility or in the community. In comparative studies the intervention were compared with the non-applied groups or other comparison groups. We excluded preventive interventions other than social distancing, stay at home, travel ban and lockdown measures.

Types of outcome measures

to decide whether a certain measure is optimal or effective for COVID-19 prevention, we used effectiveness measurements applied at different settings including: effect on incidence, disease burden, mortality reduction and epidemic control. We did not address secondary outcomes such as psychological impact, economic impact and social impact.

Literature search strategy

We searched the MEDLINE, SCOPUS, CINAHL, PsycINFO, and Web of Science databases for studies published to date. Articles containing information on different prevention strategies (social distancing, stay at home, travel ban and lockdown) and studies assessing their effectiveness were retained for the review. A combination of free-text search terms, Medical Subject Headings, and database-specific subject headings search strategy was used for multiple electronic databases. In addition, we searched gray literatures, pre-prints and coronavirus resource centers and reference lists of systematic reviews were screened for additional relevant citations. The combination of search terms was used with (AND, OR, NOT) Boolean (Search) Operators.

  1. 1.

    Coronavirus Infections

  2. 2.

    SARS COv2

  3. 3.

    COVID-19

  4. 4.

    Novel corona

  5. 5.

    Prevention/ control

  6. 6.

    Social distancing

  7. 7.

    Stay home/stay at home

  8. 8.

    Travel bans/restriction

  9. 9.

    Lockdown Boundary control

  10. 10.

    1 or 2 or 3 or 4 or 5 and 6 and 7 or 8 or 9 or 10

The search operation used in the Medline.

#1 exp. coronavirus/

#2 ((corona* or CORONA* or SARS*) adj1 (virus* or viral* or virinae*)).ti,ab,kw.

#3 (coronavirus* or beta-coronavirus* or coronovir* or coronavirinae* or Coronavirus* or Coronovirus* or Wuhan* or Hubei* or Huanan or “2019-nCoV” or 2019nCoV or nCoV2019 or “nCoV-2019” or “COVID-19” or COVID19 or Ncov or “n-cov” or “SARS-CoV-2” or “SARSCoV-2” or “SARSCoV2” or “SARS-CoV2” or SARSCov19 or “SARS-Cov19” or “SARSCov-19” or “SARS-Cov-19” or “middle east respiratory syndrome” or “middle-east respiratory syndrome” or Ncovor or Ncorona* or Ncorono* or NcovWuhan* or NcovHubei* or NcovChina* or NcovChinese*).ti,ab,kw.

#4 (((coronavirus* adj2 (prevention* or control*)) or “socialdistancing*” or “lockdown*” or “travelristriction*” or stayhome*”) adj

#5 “severe acute respiratory syndrome*”.ti,ab,kw.

#6 or/1–5

#7 limit 5 to yr = “2019 -Current”

Data collection and analysis

Study selection process

Team of researchers (TG, MG, KL, BM, SS and MS) screened all titles and abstracts based on predefined eligibility criteria set at the protocol. Two authors (TG and MG) among the team independently screened the titles and abstracts of records retrieved during the initial search, and decided by consensus or by involving third author (MS) whenever agreements were not reached. After that, the review team (TG, MG, KL, BM, SS and MS) retrieved the full texts of all included abstracts. Two review authors (TG and MG) screened all full-text publications independently decisions were reached by consensus or by involving a third review author (MS).

Data extraction and management

Titles and abstracts retained from the primary electronic search were thoroughly assessed for possibility of reporting the intended outcome and for eligibility. Two authors (TG and MG) have extracted data from the included studies into standardized tables and a third author (KL) has checked the data for completeness and correctness based on the pre-sated eligibility criteria. Finally, from the retained researches the necessary information was extracted based on the structured format which includes: author, title, study participants, study design, sample size, study setting, type of intervention, length of intervention, year of publication, effect of intervention measures, type of model (for modeling studies) and results or main outcomes.

Quality assessment (risk of bias) in included studies

The quality and risk of bias in included studies was assessed through the Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) tool [13]. The first author (TG) rated the risk of bias for each study; the second author (MG) checked the ratings and third author (KL) was consulted to solve disagreements. For each study; the study design, study participants, the outcome, the presence of bias was assessed based on the eligibility criteria and quality assessment checklist. On the other hand, modelling studies were assessed by the best practice recommendations of the International Society for Pharmaco-economics and Outcomes (ISPOR) and the Society for Medical Decision making (SMDM) for dynamic mathematical transmission models tools [14].

Data synthesis and analysis

The qualitative part was systematically reviewed and presented in accordance with the Cochrane guideline. We synthesized results of quantitative measures narratively and in tabular form. Because of the heterogeneity of available primary studies, we did not consider quantitative analyses (meta-analysis).

Certainty of the evidence evaluation

The certainty of evidence was assessed using the GRADE approach [15] for the main outcomes and reported in standard terms using tables. One of the researchers (TG) assessed the certainty through assessments of risk of bias, indirectness, inconsistency, imprecision, and publication bias and classified in to four. A high certainty rating means the estimated effect lies close to the true effect; moderate certainty means the estimated effect is probably close to the true effect; a low certainty rating suggests that the estimated effect might substantially differ from the true effect; and very low certainty means that the estimated effect is probably markedly different from the true effect.

Results

Studies included

Figure 1 presents the PRISMA flow diagram for studies selected in the search process. Initially we identified 1765 potentially relevant citations in the form of title, abstract, bibliography and full text research from the selected databases using the electronic search system. After removal of duplicates and initial screening, 112 articles were selected for further screening and evaluation via full text. In the screening process, we found that 87 research titles were not relevant for the systematic review and removed for different reasons. 33 research was removed because the outcome was measured on SARS and MERS; 39 studies removed due to difference in intervention (prevention method other than the specified interventions), 11 studies removed due to the design difference and 4 studies removed due to other reasons. Thus, the review was conducted on 25 studies [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40] that full filled the eligibility criteria and retained for final synthesis.

Fig. 1
figure 1

Flow chart for study search, selection and screening for the review

Study characteristics

Table 1 Presents the details of survey characteristics and summary results of the included studies. The selected 25 studies [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40] were published between January 13, 2020 and June 05, 2020. Ten of these studies [16,17,18, 23, 27, 28, 30, 34, 38, 39] were conducted in china, 6 in USA [20,21,22, 25, 31, 37], 2 in UK [32, 36], 5 globally and at least in two countries [19, 28, 29, 33, 35], and the last 3 researches conducted in Ethiopia [24], Nigeria [26] and France [40] one in each country. The included studies comprised 11 observational and event studies [16,17,18,19,20,21,22,23,24,25,26] and 14 modeling (SIR, SEIR and Stochastic) studies [27,28,29,30,31,32,33,34,35,36,37,38,39,40]. Twelve studies [19,20,21,22,23, 28,29,30,31,32,33,34, 36, 37] conducted on the effect of social distancing, seven studies [16,17,18, 26, 27, 38, 39] observed the effect of travel restriction, border control and lockdown strategies, four studies [23, 24, 35, 36] assessed non pharmacological interventions and more than one of the aforementioned prevention strategies, and the remaining one study evaluated the effect of stay at home strategy [25]. Most of these studies were community based studies and national simulation studies.

Table 1 Characteristics of included studies and summery of result

Quality assessment of included studies

Presented in Tables 2 and 3 is a summary of the risk of bias assessment of included non-randomized studies and quality rating of the modelling studies respectively. All of the observational studies have moderate risk of bias in overall assessment. Whereas, twelve of the modeling studies were rated as no concerns to minor concerns and the other two studies as major concerns [29] and moderate concerns [32].

Table 2 Risk of bias assessment of observational studies based on ROBINS-I
Table 3 Quality rating of the modeling studies based on three best practice recommendations from ISPOR

COVID 19 prevention strategies

Social distancing strategies

With duplicates we included five observational studies [19,20,21,22,23] and nine modeling studies [28,29,30,31,32,33,34, 36, 37] that assessed the effect of social distancing with or without other preventive programs. Three of the observational studies were conducted in USA [20,21,22], one in china [23] and the remaining one study was conducted in Scandinavia countries (Sweden, Denmark and Norway) [19]. While the modeling studies were conducted in globally, USA, China and UK.

One of the retrospective study has been conducted in USA [22] to evaluate the impact of strong social distancing measures on the growth rate of confirmed COVID-19 and found that, government-imposed social distancing measures reduced the daily growth rate by 5.4% after 1–5 days, 6.8% after 6–10 days, 8.2% after 11–15 days, and 9.1% after 16–20 days. Another study conducted in USA [20] reported that the effect of social distancing on decreasing transmission is not appreciable for nine to 12 days after implementation of social distancing; however, after 9–12 days the effect was very high.

The other three retrospective studies conducted to evaluate the effect of social distancing complimented with stay at home policy [21], traffic control [23] and lockdown policy [19] reported that, the measures enhance the effectiveness of social distancing. According to the studies, traffic control and social distancing were complementary, and their combined effect played a better role in epidemic prevention [23]. Also implementation of safer at home policies facilitate social distancing and reduce incidence of disease by two third [21]. However, these measures were not functional everywhere. Similarly, a study in Scandinavia [19] indicated that the lockdown measures strongly reduced the number of hospitalizations and intensive care patients.

The modeling studies conducted globally and in specific countries that assessed the effect of social distancing alone or integrated in reducing incidence, mortality, epidemic peak time and cost effectiveness consistently reported that social distancing is effective in all outcomes. Early initiation and large scale control measure and government initiated social controls were very effective in controlling the disease [28,29,30,31,32,33,34, 36, 37]. However, social distancing and travel restriction measures implemented for longer period of time may affect employment and economy of a country, hence, may not be affordable to developing countries [28].

One of the community based SIR modeling study conducted in China [30] indicated that daily contacts were reduced by 7–9 fold during the COVID-19 social distancing period. With strict policies, social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. Another community based stochastic modeling simulation [32] also reported that, with perfect social distancing policies the epidemic can be controlled in 90 days and mortality is reduced much more. In case, if social distancing not works and average contacts per day per person is 16, the number of infected individuals exceeds the healthcare capacity of the system very early [29].

According to the finding of Alexander Chudik et al. [28] mandated policies can be very useful in flattening the epidemic curve, but is costly and voluntary social distancing is insufficient in controlling the disease. Also one-time interventions were insufficient [31]. Hence, a strategic social network-based contact reduction is important [33]. Similarly, a community based study conducted in Wuhan, china [34] reported that physical distancing measures and work at home initiated early reduced the median number of infections by more than 92 and 24% in mid-2020 and end-2020, respectively. In addition to these finding three studies reported that implementing the program for longer period of time and integrating with other programs such as stepping down measures are very effective [34, 36, 37].

Travel restriction and lockdown strategies

Of the nine researches [16,17,18, 23, 26, 27, 38,39,40] assessing the effect of travel ban and lockdown with or without other strategies, five are observational studies [16,17,18, 23, 26] conducted in China and Nigeria. Whereas, among the four modeling studies [27, 38,39,40] three were conducted in china and one in France. These studies consistently reported the benefit of travel restriction and lockdown strategies to control COVID 19.

One of the studies [16] assessed the effect of human mobility and control measures in china, reported that travel restrictions are particularly useful in the early stage of an outbreak before wide spread distribution of the disease. Also the combination of interventions implemented in China was successful in mitigating spread and reducing local transmission of COVID-19. Another study concluded travel lockdowns enforced by the Chinese government averted 70.5% of exported cases and it was most effective at early stage of the epidemic. From another community based retrospective study doubling time was increased from 2 days to 4 days after imposing lockdown [18]. Others also reported the positive effect of social distancing such as school and business closure and integration of all preventive measures [23, 26].

The lockdown strategy reduced contacts by 80% and decreased the initial reproductive number from 3.0 [95% CI: 2.8, 3.2] to 0.68 [95% CI: 0.62–0.73]) [40]. According to another modeling study, with travel restriction, the number of infected individuals can be decreased by 91.14% in Beijing [38]. The other two studies basically indicated the potential effect of early intervention and combination of different interventions [27, 39].

Stay at home strategies

Three observational studies that aimed to assess the effect of stay at home measures in Ethiopia [24] and USA [21, 25] reported the benefit of stay at home measures. A study by James H [25] aimed to measure the effect of stay at home measure in USA found that, it was associated with a 30.2% reduction in weekly cases after 1 week, a 40.0% reduction after 2 weeks, and a 48.6% reduction after 3 weeks. In addition to this, stay-at-home orders were associated with a 59.8% reduction in weekly fatalities after 3 weeks, and reduced confirmed cases by 390,000 [25]. Another two studies also reported that individuals are stay at home to prevent the infection and the effect was tremendous [21, 24].

Discussion

This study aimed to find out optimal strategies for COVID-19 prevention from global evidence achieved through social distancing, stay at home, and travel ban and lockdown measures by reviewing existing literatures. The review identified and systematically synthesized the findings of 25 studies [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40] conducted abroad to bring the best available evidence that policy makers and implementers can use in the process of infection prevention.

The studies consistently reported the benefit of social distancing, stay at home, and travel ban and lockdown measures for the prevention of COVID-19. Social distancing measures achieved through reducing contacts can tremendously reduce the reproductive number, increases the doubling time, reduces the duration of epidemics, and decrease the incidence and associated mortality at community level and individual level. Obligatory social distancing measures that are initiated in early stages of the epidemic and implemented for longer period of time were very effective [19,20,21,22,23, 28,29,30,31,32,33,34, 36, 37]. Implementation of these strategies along with other previously identified strategies [41] can be optimally applied in different settings.

The effect of each intervention varies depending on the extent to which the intervention was applied. In intensive interventions, the effect of social distancing is evident after 12 days of implementation and the effectiveness increases by implementing for long period of time [20]. Also strengthening and mandatory implementation of social distancing measures reduced the daily growth rate by 5.4–9.1% within 20 days [22]. This evidence is in line with the finding of other reviews and modeling studies conducted to assess the effectiveness of social distancing measures in the prevention of SARS, MERS and COVID-19 [40, 42, 43]. Integration of programs such as lockdown and travel ban along with social distancing and with other interventions enhances the effectiveness of the program. Although, travel restriction and lockdown were very important measures to control the epidemic, early initiation, larger coverage and integration with other program were very important to alter the epidemic. However, intermittent social distancing measures and travel restrictions were ineffective in most of cases and in some countries they found to have a limited effect [24, 31]. In line with this review finding, a researcher [35] reported that adding social distancing of people 70 years or older for 4 months with the existing combination of case isolation and voluntary quarantine for 3 months increase the percentage of prevented death from 31 to 49%.. Thus, the combination of case isolation, household quarantine, social distancing of the entire population, and school and university closures are the most effective combinations of measures that could reduce the reproduction number close to one and effective to prevent COVID 19 [17, 35, 36].

The present systematic review indicates that social distancing, staying at home and lockdowns are very efficient to prevent COVID-19 infections. However, these strategies harm economic activities unless work is performed remotely through telecommuting and the use of robots [44, 45]. AI and robotics have been used to solve practical problems during the COVID-19 pandemic and they can also be viewed as part of the optimal strategies to prevent COVID-19 infections. Semi-autonomous robots have been utilized for the cleaning and sterilization in hospitals and to deliver food, medication and equipment. In particular, robots have been used to implement social distancing requirements in Singapore and to deliver food to residents staying at home in the UK [45]. Unfortunately, job automation and autonomous robots have a downside and can lead to mass unemployment. Therefore, Dr. Andrew Johnson and Dr. Katherine Roberto have recently suggested that an unconditional basic income (UBI) could help people financially during the pandemic, especially those who cannot work [44,45,46,47]. UBI could be an effective safety net, especially when combined with retraining programs to teach people the necessary skills to work remotely and/or from home.

On the other hand measures undertaken to close borders, restrict travels and air transportation were important to control the disease [16, 38]. Most countries throughout the world were implemented this interventions in the early phases of the epidemic and found to contributed to control the epidemic. As evidenced in china, Lockdown was averted more than two third of exported cases and the epidemic doubling time was increased [16, 17]. Also, the lockdown strategy reduced contacts by 80% and significantly decreased the initial reproductive number from 3.0 to 0.68. With all these cumulative mechanisms the numbers of infected cases were reduced by 91.14% in Beijing [38]. As evidenced from previous studies, travel restriction can reduce the number of susceptible individuals and number of newly infected cases [41].

However, this strategy can’t be implemented for longer period of time due to economic reasons. Researches indicated that implementing travel restriction and lockdown for longer period of time reduces individual’s wage, income and challenges the global economy [44, 46]. On the other hand companies that applied digital marketing were profitable [44]. Application of remote working and digital marketing assisted with artificial intelligence and robotic technologies reduced the potential economic impact of the lockdown [44, 45]. But automation of all works with these technologies reduces human retention and results in unemployment [44, 47]. Therefore the economic impact of digitalization and application of artificial intelligence and robotics for the prevention of COVID 19 remained a point of discussion and debate [44,45,46,47].

Stay at home strategy was one of the most effective and optimal strategy in the prevention of COVID 19 infection in most countries [24, 25]. It can halt the incidence and mortality by half, if implemented strictly [25]. This strategy is commonly implemented in combination with travel restriction, quarantine and isolation in order to increase the effect of prevention measures [24, 25, 36]. However, the effectiveness of stay at home strategies can be reduced by the time when it was initiated, how strict it is and how long it was in practice [24,25,26,27].

The most important challenge in implementation of stay at home strategy has been the economic burden of the program [44,45,46,47]. Unless the government is able to fulfill the basic needs, supply demands and remote working is arranged it is quite difficult to implement the program for longer period of time. In countries where digitalization is not advanced and applications of technologies were limited, the stay home program has been removed after short time [42,43,44]. The economic challenge ascribed to stay at home program can’t be carried by low and middle income countries. It can challenge even to the developed states [45,46,47].

Optimally designed strategies such as social distancing, stay at home, travel ban and lockdown measures can significantly prevent COVID-19 epidemics in different settings. Optimal implementation of these strategies includes early initiation of obligatory and large scale programs implemented for prolonged period of time. However, this optimization depends on the government’s capacity to cope the economic burden. Optimization of strategies that integrates all or some of the above strategies highly improves the effectiveness of the program. Also all the countries have been implemented different strategies, the optimization of the program and the effectiveness was different in different countries [1,2,3, 38,39,40,41]. Carrying the economic burden of these intervention was the main challenges and some of the challenges can be reduced by application of digital technologies, AI, robotics and by arranging remote work [44,45,46,47].

Limitation

This review included a wide variety of study designs (observational and model studies), hence, it failed to include meta-analysis (statistical measures). Modeled studies also assume different scenarios, where it may not be true in the general cases. Also the review has included only publications reported in English language and open accesses resources. The study don’t analysed the economic burden of the selected interventions and the potential effect of implementing other strategies that optimize the prevention program such as application of AI, Robotic and digitalization.

Conclusion and recommendation

Social distancing, stay at home, travel ban and lockdown measures are effective for COVID-19 prevention, particularly combined together. Obligatory implementation and early initiation of combination of travel restriction, lockdown, stay at home and social distancing programs, implemented for longer period of time are very effective in the prevention of COVID 19 infection. Applications of digital technologies enhance the implementation of the program. However, these strategies harm economic activities unless work is performed remotely through telecommuting and the use of robots. Unconditional basic income could be an effective safety net, especially when combined with retraining programs to teach people the necessary skills to work remotely and/or from home. Therefore, the health care system should consider high level implementation in obligatory and longtime restriction of movement in accordance with the economic stand of the specific country.

Availability of data and materials

Please contact author for data requests.

Abbreviations

COVID-19:

Coronavirus disease 2019

MERS:

Middle East respiratory syndrome

SARS:

Severe acute respiratory syndrome

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

R0:

Basic reproduction number

SEIR:

Susceptible-exposed-infected-recovered

WHO:

World Health Organization

References

  1. World Health Organization (WHO). Naming the coronavirus disease (COVID-19) and the virus that causes it”. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technicalguidance/naming-the-coronavirus-disease-(covid-2019)-and-the-virus-that-causes-it

  2. World Health Organization (WHO). Rolling updates on coronavirus diseases (COVID-19). Available from www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-theyhappen

  3. Guan W, Ni Z-Y, Hu Y, Liang W-H, Ou C-Q, He J-X, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708–20. https://doi.org/10.1056/NEJMoa2002032.

    Article  CAS  PubMed  Google Scholar 

  4. World Health Organization. Novel coronavirus (2019-nCOV). Situation Report 51. 2020 [Available from: https://www.who.int/docs/default-source/ coronaviruse/situation-reports/20200311-sitrep-51-covid-19.pdf?sfvrsn=1ba62 e57_10.

  5. Cao B, Wang Y, Wen D, Liu W, Wang J, Fan G, et al. A trial of lopinavir– ritonavir in adults hospitalized with severe covid-19. N Engl J Med. 2020;382(19):1787–99. https://doi.org/10.1056/NEJMoa2001282.

    Article  PubMed  Google Scholar 

  6. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan. China Lancet. 2020;395(10223):497–506. https://doi.org/10.1016/S0140-6736(20)30183-5.

    Article  CAS  PubMed  Google Scholar 

  7. Chan JF, Yuan S, Kok K-H, To KK-W, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating personto-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514–23. https://doi.org/10.1016/S0140-6736(20)30154-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8(4):420–2. https://doi.org/10.1016/S2213-2600(20)30076-X.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Baden LR, Rubin EJ. Covid-19—the search for effective therapy. N Engl J Med. 2020;382(19):1851–2. https://doi.org/10.1056/NEJMe2005477.

    Article  PubMed  Google Scholar 

  10. World Health Organization. Coronavirus disease (COVID-19) outbreak 2020 [Available from: https://www.who.int/emergencies/diseases/novelcoronavirus-2019.

  11. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1. https://doi.org/10.1186/2046-4053-4-1.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA. Cochrane handbook for systematic reviews of interventions version 6.0 (updated July 2019). Cochrane; 2019. Available athttps://training.cochrane.org/handbook/archive/v6.

  13. Sterne JAC, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomized studies of interventions. BMJ. 2016;355:i4919. https://doi.org/10.1136/bmj.i4919.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Caro JJ, Briggs AH, Siebert U, Kuntz KM. ISPOR-SMDM modeling good research practices task force. Modeling good research practices--overview: a report of the ISPOR-SMDM modeling good research practices task Force-1. Med Decis Mak. 2012;32(5):667–77. https://doi.org/10.1177/0272989X12454577.

    Article  Google Scholar 

  15. Morgan RL, Thayer KA, Bero L, et al. GRADE: Assessing the quality of evidence in environmental and occupational health. Environ Int. 2016;92–93:611–6. https://doi.org/10.1016/j.envint.2016.01.004.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Kraemer MUG, Yang CH, Gutierrez B, et al. The effect of human mobility and control measures on the COVID-19 epidemic in China. medRxiv. 2020:2020.03.02.20026708. https://doi.org/10.1101/2020.03.02.20026708.

  17. Wells CR, Sah P, Moghadas SM, Pandey A, Shoukat A, Wang Y, et al. Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak. Proc Natl Acad Sci U S A. 2020;117(13):7504–9. https://doi.org/10.1073/pnas.2002616117.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lau H, Khosrawipour V, Kocbach P, et al. The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China. J Travel Med. 2020;27(3):taaa037. https://doi.org/10.1093/jtm/taaa037.

    Article  PubMed  Google Scholar 

  19. Juranek S, Zoutman F. The Effect of Social Distancing Measures on Intensive Care Occupancy: Evidence on COVID-19 in Scandinavia. Working paper, 2020, retrieved from https://hdl.handle.net/11250/2652920.

  20. Badr HS, et al. Social distancing is effective at mitigating COVID-19 transmission in the United States. medRxiv. 2020:05.07.20092353. https://doi.org/10.1101/2020.05.07.20092353.

  21. Brodeur A, et al. On the effects of COVID-19 safer-at-home policies on social distancing, car crashes and pollution. In: IZA DP; 2020. p. 13255.

    Google Scholar 

  22. Courtemanche C, Garuccio J, Le A, Pinkston J, Yelowitz A. Strong social distancing measures in the united states reduced the covid-19 growth rate. Health Aff (Millwood). 2020. https://doi.org/10.1377/hlthaff.2020.00608 [published online ahead of print, 2020 May 14].

  23. Lin S, Huang J, He Z, Zhan D. Which measures are effective in containing COVID-19? Empirical Research Based on Prevention and Control Cases in China. medRxiv. 2020. https://doi.org/10.1101/2020.03.28.20046110 (Preprint).

  24. Kebede Y, Yitayih Y, Birhanu Z, Mekonen S, Ambelu A. Knowledge, perceptions and preventive practices towards COVID-19 early in the outbreak among Jimma university medical center visitors, Southwest Ethiopia. PLoS One. 2020;15(5):e0233744. Published 2020 May 21. https://doi.org/10.1371/journal.pone.0233744.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Fowler JH, Hill SJ, Levin R, Obradovich N. The Effect of Stay-at-Home Orders on COVID-19 Cases and Fatalities in the United States. medRxiv. 2020:04.13.20063628. https://doi.org/10.1101/2020.04.13.20063628.

  26. Ekienabor E. Coronavirus (Covid-19): The Lockdown Strategy in Nigeria; 2020. p. 2020050201. https://doi.org/10.20944/preprints202005.0201.v1.

    Book  Google Scholar 

  27. Chinazzi M, Davis JT, Ajelli M, Gioannini C, Litvinova M, Merler S, et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science. 2020;368(6489):395–400. https://doi.org/10.1126/science.aba9757.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chudik A, Pesaran M.H, and Rebucci A, Voluntary and Mandatory Social Distancing: Evidence on COVID-19 Exposure Rates from Chinese Provinces and Selected Countries (April 15, 2020). Johns Hopkins Carey Business School Research Paper No. 20–03. Available at SSRN: https://ssrn.com/abstract=3576703 or doi: https://doi.org/10.2139/ssrn.3576703

  29. William Broniec, Sungeun An, Spencer Rugaber & Ashok K. Goel. Using VERA to explain the impact of social distancing on the spread of COVID-19. 2020 arXiv200313762B.

    Google Scholar 

  30. Zhang J, Litvinova M, Liang Y, et al. Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China. medRxiv. 2020:2020.03.19.20039107. https://doi.org/10.1101/2020.03.19.20039107.

  31. Kissler S, Tedijanto C, Lipsitch M, Grad Y. Social distancing strategies for curbing the COVID-19 epidemic; 2020.

    Book  Google Scholar 

  32. Cano OB, Morales SC, Bendtsen C. COVID-19 Modelling: the Effects of Social Distancing. medRxiv. 2020:03.29.20046870. https://doi.org/10.1101/2020.03.29.20046870.

  33. Block P, Hoffman M, Raabe IJ, Dowd JB, Rahal C, Kashyap R, et al. Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Nat Hum Behav. 2020;4(6):588–96. https://doi.org/10.1038/s41562-020-0898-6.

    Article  PubMed  Google Scholar 

  34. Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM, Davies N, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health. 2020;5(5):e261–70. https://doi.org/10.1016/S2468-2667(20)30073-6 [published correction appears in lancet public health].

    Article  PubMed  PubMed Central  Google Scholar 

  35. Eubank S, Eckstrand I, Lewis B, Venkatramanan S, Marathe M, Barrett CL, et al. Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand. Bull Math Biol. 2020;82(4):52. https://doi.org/10.1007/s11538-020-00726-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Adam J. Kucharski et al. Effectiveness of isolation, testing, contact tracing and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study. doi: https://doi.org/10.1101/2020.04.23.20077024.

  37. Kennedy DM, Zambrano GJ, Wang Y, Neto OP. Modeling the effects of intervention strategies on COVID-19 transmission dynamics. J Clin Virol. 2020;128:104440. https://doi.org/10.1016/j.jcv.2020.104440.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Tang B, Wang X, Li Q, et al. Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions. J Clin Med. 2020;9(2):462. https://doi.org/10.3390/jcm9020462.

    Article  PubMed Central  Google Scholar 

  39. Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. J Thorac Dis. 2020;12(3):165–74. https://doi.org/10.21037/jtd.2020.02.64.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Di Domenico L, Pullano G, Sabbatini CE, Boëlle P, Colizza V. Expected impact of lockdown in Île-de-France and possible exit strategies. medRxiv. 2020. https://doi.org/10.1101/2020.04.13.20063933.

  41. Girum T, Lentiro K, Geremew M, Migora B, Shewamare S. Global strategies and effectiveness for COVID-19 prevention through contact tracing, screening, quarantine, and isolation: a systematic review. Trop Med Health. 2020;48(1):91. https://doi.org/10.1186/s41182-020-00285-w.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Nussbaumer-Streit B, Mayr V, AIulia D, Chapman A, Persad E, Klerings I, et al. Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review. Cochrane Database Syst Rev. 2020;(4):CD013574. https://doi.org/10.1002/14651858.CD013574.

  43. Chu DK, Akl EA, Duda S, et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis [published online ahead of print, 2020 Jun 1]. Lancet. 2020;S0140–6736(20):31142–9. https://doi.org/10.1016/S0140-6736(20)31142-9.

    Article  Google Scholar 

  44. Zhao Z, Ma Y, Mushtaq A, Rajper A, Shehab M, Heybourne A, et al. Applications of robotics, artificial intelligence, and digital technologies during COVID-19: a review. Disaster Med Public Health Prep. 2021:1–11. https://doi.org/10.1017/dmp.2021.9.

  45. Coombs C. Will COVID-19 be the tipping point for the intelligent automation of work? Int J Inf Manag. 2020;55:102182. https://doi.org/10.1016/j.ijinfomgt.2020.102182.

    Article  Google Scholar 

  46. del Rio-Chanona RM, Mealy P, Pichler A, Lafond F, Farmer JD. Supply and demand shocks in the COVID-19 pandemic: an industry and occupation perspective. Oxford Review of Economic Policy. 2020;graa033. Published 2020 Aug 29. https://doi.org/10.1093/oxrep/graa033.

  47. Johnson AF, Roberto KJ. The COVID-19 pandemic: Time for a universal basic income?. Public administration and development : a journal of the Royal Institute of Public Admin Dev, Oct. 2020;40:2032-5. https://doi.org/10.1002/pad.1891.

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Girum, T., Lentiro, K., Geremew, M. et al. Optimal strategies for COVID-19 prevention from global evidence achieved through social distancing, stay at home, travel restriction and lockdown: a systematic review. Arch Public Health 79, 150 (2021). https://doi.org/10.1186/s13690-021-00663-8

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