Table 1 Characteristics of included studies and summery of result
| Â | Â | Study characteristics and summery report |
|---|---|---|
1 | Author/s & title [16] | Moritz U., et al. The effect of human mobility and control measures on the COVID-19 epidemic in China |
Population size (N) | Population of China | |
Country | China | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. | |
Study detail | Real-time mobility data from Wuhan and detailed case data including travel history was used to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. | |
Interventions | Diagnostic testing; clinical management; rapid isolation of suspected cases, confirmed cases, and contacts; and restrictions on mobility. | |
Results | ➢ Travel restrictions are particularly useful in the early stage of an outbreak. ➢ Travel restrictions may be less effective once the outbreak is more widespread. ➢ The combination of interventions implemented in China was clearly successful in mitigating spread and reducing local transmission of COVID-19. ➢ In this work it was not possible to definitively determine the impact of each intervention. | |
2 | Author/s & title [17] | Chad R. Wells, et al. Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak |
Population size (N) | Global population | |
Country | China | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To estimate the impact control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. | |
Study detail | Daily incidence data of COVID-19 outbreak within mainland China from December 8, 2019 to February 15, 2020, as well as airline network data was used to predict the number of exported cases with and without measures of travel restriction and screening. | |
Interventions | Border measures, including travel lockdown, contact tracing at the epicenter, and airport screening | |
Results | ➢ Travel lockdowns enforced by the Chinese government averted 70.5% of exported cases. ➢ At early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response. | |
3 | Author/s & title [18] | Hien Lau, et al. The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China |
Population size (N) | China domestic Air passengers | |
Country | China | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To evaluate whether rigorous lockdown measures as implemented by China have the potential to slow down the virus’ spread. | |
Study detail | China domestic air traffic and passenger data before and after the lockdown was used to evaluate whether rigorous lockdown measures as implemented by China have the potential to slow down the virus’ spread. | |
Interventions | Lockdown | |
Results | ➢ A significant increase in doubling time from 2 days to 4 days after imposing lockdown. ➢ A further increase is detected after changing diagnostic and testing methodology to 19.3. ➢ A significantly decreased growth rate and increased doubling time of cases was observed, which is most likely due to Chinese lockdown measures. | |
4 | Author/s & title [19] | Steffen Juranek and Floris T. Zoutman. The effect of social distancing measures on intensive care occupancy: evidence on COVID-19 in Scandinavia |
Population size (N) | Population of Sweden, Denmark and Norway | |
Country | Sweden, Denmark and Norway | |
Setting | Community based | |
Design | An event study (Sweden as control group, whereas Denmark and Norway each function as a treatment group) | |
Objectives | To understand the effectiveness of social distancing on the spread of COVID-19. | |
Study detail | A case study was conducted to compare the effect on the health care system of the strict lockdown measures by Denmark and Norway with the more lenient approach (social distancing) of Sweden. | |
Interventions | Social distancing and lockdown | |
Results | ➢ Without lockdown, Denmark would have seen 107% more patients in ICU at the peak, and 134% more overall hospitalizations. ➢ At the end of the sample, cumulative deaths would have been 167% higher. ➢ Following the Swedish approach would have resulted in more than twice as many hospitalizations and intensive care patients at the peak, potentially bringing Denmark and Norway close to their maximum capacity. ➢ Compared to the more lenient approach of Sweden, the lockdown measures strongly reduce the number of hospitalizations and intensive care patients per capita | |
5 | Author/s & title [20] | Hamada S. Badr, et al. Social distancing is effective at mitigating COVID-19 transmission in the United States |
Population size (N) | Population of USA | |
Country | USA | |
Setting | Community based, health care | |
Design | Retrospective | |
Objectives | To represent social distancing behavior derived from mobile phone data and examine its relationship with COVID-19 case reports at the county level. | |
Study detail | Epidemiological data on cases and deaths for each US state were used | |
Interventions | Social distancing | |
Results | ➢ The effect of social distancing on decreasing transmission is not perceptible for nine to twelve days after implementation. ➢ The strong relationship between social distancing and outbreak case growth rates suggest that a return to ‘normal’ interaction patterns will result in an increase in case growth rates, which may appear 9–12 days after behavioral changes ensue. ➢ However, under these changes, additional precautions such as hand washing, wearing masks and self-isolation when sick may help to lessen the case growth rates. | |
6 | Author/s & title [21] | Abel Brodeur, et al. On the effects of COVID-19 safer-at-home policies on social distancing, car crashes and pollution |
Population size (N) | USA | |
Country | USA | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To understand the effects safer-at-home policies on social distancing, travel and pollution. | |
Study detail | Data from reports across USA were obtained to understand the effects safer-at-home policies on social distancing, travel and pollution. | |
Interventions | Safer-at-home | |
Results | ➢ Safer-at home policies are successful in encouraging social distance. ➢ A 50% reduction in vehicular collisions; an approximately 25% reduction in particulate matter (PM2.5) concentrations; and a reduction of the incidence of county-days with an air quality index of code yellow or above by two-thirds. | |
7 | Author/s & title [22] | Charles Courtemanche, et al. Strong social distancing measures in the United States reduced the COVID-19 growth rate |
Population size (N) | Population of USA | |
Country | USA | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To evaluate the impact of these measures on the growth rate of confirmed COVID-19 cases across USA. | |
Study detail | An event-study regression with multiple treatments was adopted to estimate the relationship between social distancing policies and the exponential growth rate of confirmed COVID-19 cases of US obtained from March 1, 2020 to April 27, 2020, a sample size of 182,004. | |
Interventions | SIPOs, public school closures, bans on large social gatherings, and closures of entertainment-related businesses. | |
Results | ➢ Government-imposed social distancing measures reduced the daily growth rate by 5.4 percentage points after 1–5 days, 6.8 after 6–10 days, 8.2 after 11–15 days, and 9.1 after 16–20 days. ➢ Holding the amount of voluntary social distancing constant, more than 35 times greater spread without any of the four measures (35 million) | |
8 | Author/s & title [23] | Shanlang Lin, et al. Which measures are effective in containing COVID-19? |
Population size (N) | Population of china | |
Country | China | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To theoretically explain the impact mechanism of traffic control and social distancing measures on the spread of the epidemic, and empirically tests the effect of the two measures in China at the present stage using econometric approach | |
Study detail | To theoretically explain the impact mechanism of the interventions on the spread of the epidemic, and empirically tests the effect of the two measures using econometric approach based on panel data of 279 prefecture-level cities from January 1 to February 10, 2020′. | |
Interventions | Traffic control and social distancing | |
Results | ➢ The effect of social distancing is better than traffic control. ➢ The two measures are complementary, and their combined effect will play a better role in epidemic prevention. ➢ Traffic control and social distancing do not work everywhere. ➢ Traffic control only play a role in cities with large GDP and population size, but not in cities with low GDP population size. ➢ In cities with lower population size, social distancing becomes inoperative. | |
9 | Author/s & title [24] | Yohannes Kebede, et al. Knowledge, perceptions and preventive practices towards COVID-19 early in the outbreak among Jimma university medical center visitors, Southwest Ethiopia |
Population size (N) | Health center visitors | |
Country | Ethiopia | |
Setting | Health facility based | |
Design | Cross-sectional | |
Objectives | To assess knowledge, perceptions, and practices that inform communication and community engagement efforts in the fight against COVID-19 among community members who visited Jimma University Medical Center (JUMC) in Jimma town, Southwest Ethiopia. | |
Study detail | A cross sectional survey was conducted in Jimma university medical center during March 22–28, 2020 based on a sample size of 247 visitors. | |
Interventions | Stay home with other interventions | |
Results | To protect themselves from COVID-19, 1.6% individuals started to stay home, engaged in frequent hand washing with water and soap (77.3%), stopped shaking hands while giving greeting (53.8%), avoiding physical proximity (33.6%) and avoiding going to crowed places (33.2%). | |
10 | Author/s & title [25] | James H. Fowler, et al. The effect of stay-at-home orders on COVID-19 cases and fatalities in the United States |
Population size (N) | Population of USA | |
Country | USA | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To estimate the effect of stay-at-home orders using a difference-in- differences design that accounts for unmeasured local variation in factors like health systems and demographics and for unmeasured temporal variation in factors like national mitigation actions and access to tests. | |
Study detail | Data on stay-at-home orders, COVID-19 confirmed cases, rates of testing, and fatalities by day and county throughout the United States were used to estimate the effect of stay-at-home orders. | |
Interventions | Stay at home | |
Results | ➢ Stay-at-home associated with a 30.2% (11.0 to 45.2) reduction in weekly cases after one week, a 40.0% (23.4 to 53.0) reduction after two weeks, and a 48.6% (31.1 to 61.7) reduction after three weeks. ➢ Stay-at-home orders are also associated with a 59.8% (18.3 to 80.2) reduction in weekly fatalities after three weeks. ➢ Stay-at-home orders reduced confirmed cases by 390,000 (170,000 to 680,000) and fatalities by 41,000 (27,000 to 59,000) within the first three weeks in localities where they were implemented. | |
11 | Author/s & title [26] | Ekienabor Ehijiele. Coronavirus (Covid-19): the lockdown strategy in Nigeria |
Population size (N) | Population of Nigeria | |
Country | Nigeria | |
Setting | Community based | |
Design | Retrospective | |
Objectives | To investigate the effect of the lockdown strategy in curbing the spread of the COVID-19 virus in Nigeria. | |
Study detail | Data obtained from secondary sources were used to investigate the effect of the lockdown strategy in curbing the spread of the COVID-19 virus in Nigeria. | |
Interventions | Lockdown | |
Results | ➢ Daily relative risk increases in cases, and daily relative risk increase in mortality. ➢ The observed growth in cases where in areas where active measures were not taken. ➢ Halt in business activities has rendered many penniless and unable to provide for themselves basic amenities. ➢ There is need to implement community-level measures of social distancing which may include closing schools, need for individuals with COVID-19 case or respiratory symptoms be properly taken care of, trace and quarantine those who must have come in contact with affected persons and introducing stay at home palliatives for the general public. | |
12 | Author/s & title [27] | Matteo Chinazzi, et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak |
Population size (N) | Global Population | |
Country | China | |
Setting | Community based | |
Design | Global metapopulation disease transmission modeling | |
Objectives | To project the impact of travel limitations on the national and international spread of the epidemic. | |
Study detail | Global metapopulation disease transmission model was used to project the impact of travel ban on the basis of internationally reported cases. | |
Interventions | Travel restrictions/ban | |
Results | ➢ The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in mainland China but had a more marked effect on the international scale, where case importations were reduced by nearly 80% until mid-February. ➢ Sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community. | |
13 | Author/s & title [28] | Alexander Chudik, et al. Voluntary and mandatory social distancing: evidence on COVID-19 exposure rates from Chinese provinces and selected countries |
Population size (N) | China and some European countries | |
Country | China and some European countries | |
Setting | Community based | |
Design | Mathematical Modeling, SIR | |
Objectives | To evaluate social distancing polices impact on both the COVID-19 epidemic and the associated employment costs. | |
Study detail | A standard SIR model was fitted in order to evaluate the impact of alternative mitigation or containment policies on both the epidemic and the so-called recession curves, and to empirically compare their implementation across countries. | |
Interventions | Voluntary and mandatory social distancing | |
Results | ➢ Mandated policies can be very useful in fattening the epidemic curve, but is costly in terms of employment loss. ➢ Voluntary policies are relatively ineffective. ➢ Self-isolation can affect the epidemic curve, but only when it is close to its peak. | |
14 | Author/s & title [29] | William Broniec, et al. Using VERA to explain the impact of social distancing on the spread of COVID-19 |
Population size (N) | General population | |
Country | Global | |
Setting | Community based/Simulation | |
Design | VERA_Epidemiology, SIR Modeling | |
Objectives | To describe the use of VERA to develop SIR model for the spread of COVID-19 and its relationship with healthcare capacity. | |
Study detail | SIR model was developed based on VERA to express the impact of social distancing on the spread of the disease but also the management of the impact of the disease on the healthcare capacity based on sample population of 10,000 people | |
Interventions | Social distancing | |
Results | ➢ Simulation results with 16 average contacts per day per person, the number of infected individuals exceeds the healthcare capacity of the system very early under these conditions. ➢ Simulation results with 12 average contacts per day per person, the number of infected individuals exceeds the healthcare capacity of the system after 20 days under these conditions. ➢ Reducing the Average contacts per day per person hypothetically suggest that people are reducing social contact somewhat, but not substantially. | |
15 | Author/s & title [30] | Juanjuan Zhang, et al. Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China |
Population size (N) | Wuhan and Shanghai | |
Country | China | |
Setting | Community based | |
Design | SIR modeling | |
Objectives | To disentangle how transmission is affected by age differences in the biology of COVID-19 infection and disease, and altered mixing patterns due to social distancing. | |
Study detail | Contact surveys data for Wuhan and Shanghai before and during the outbreak were analyzed using SIR model. | |
Interventions | Social distancing | |
Results | ➢ Daily contacts were reduced 7–9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. ➢ Social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. ➢ While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. | |
16 | Author/s & title [31] | Stephen Kissler, et al. Social distancing strategies for curbing the COVID-19 epidemic |
Population size (N) | Population of USA | |
Country | USA | |
Setting | Community based | |
Design | Mathematical modeling, SEIR | |
Objectives | To assess the amount of social distancing needed to curb the SARS-CoV-2 epidemic in the context of seasonally varying transmission. | |
Study detail | SEIR model was fitted using simulated data. | |
Interventions | Social distancing | |
Results | ➢ One-time interventions will be insufficient to maintain COVID-19 prevalence within the critical care capacity of the United States. ➢ Intermittent distancing measures can maintain control of the epidemic, but without other interventions, these measures may be necessary into 2022. ➢ Increasing critical care capacity could reduce the duration of the SARS-CoV-2 epidemic while ensuring that critically ill patients receive appropriate care. | |
17 | Author/s & title [32] | Bendtsen Cano, et al. COVID-19 modelling: the effects of social distancing |
Population size (N) | 60 million | |
Country | UK | |
Setting | Community based, simulation | |
Design | Stochastic modeling | |
Objectives | To represent the disease dynamics of Covi-19 and the efficacy of social distancing. | |
Study detail | Markov chain model was applied to represent the disease dynamics of Covi-19 and the efficacy of social distancing based on 60 million simulation. | |
Interventions | Social distancing | |
Results | ➢ In the case of perfect social distancing (R0 = 0) the mortality rate is only 0.04% (21,474 dead) and the epidemic is resolved by day 90 with the number of people sick peaking on day 70. ➢ In the case of a more relaxed social distancing with (R0 = 0.5) the mortality rate is 0.13% (79,781 dead) without having the epidemic resolved by day 250 and with the number of people sick peaking on day 71. ➢ A somewhat stricter social distancing with R0 = 0.25 would resolve the epidemic by day 189 and lead to 32,998 dead. ➢ If the social distancing is relaxed to R0 = 0.75 a much later peak in the number of people sick on day 112 and also a much larger mortality rate of 0.55% (330,964 dead). | |
18 | Author/s & title [33] | Per Block, et al. Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world |
Population size (N) | General population | |
Country | Global | |
Setting | Community based | |
Design | Stochastic simulation | |
Objectives | To evaluate the effectiveness of three distancing strategies designed to keep the curve flat and aid compliance in a post-lockdown world. | |
Study detail | Stochastic infection curve was simulated which incorporate core elements from infection models, ideal-type social network models and statistical relational event models. | |
Interventions | Three distancing strategies (limiting interaction to a few repeated contacts akin to forming social bubbles; seeking similarity across contacts; and strengthening communities via triadic strategies) | |
Results | A strategic social network-based reduction of contact strongly enhances the effectiveness of social distancing measures while keeping risks lower. | |
19 | Author/s & title [34] | Kiesha Prem, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. |
Population size (N) | Population of Wuhan | |
Country | China | |
Setting | Community based | |
Design | SEIR modeling, case study | |
Objectives | To estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic. | |
Study detail | A mathematical model was used to quantify the potential impacts of physical distancing policies, relying on Wuhan as a case study. | |
Interventions | Physical distancing | |
Results | ➢ Physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92 and 24% in mid-2020 and end-2020, respectively. ➢ Effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic. | |
20 | Author/s & title [35] | Neil M. Ferguson, et al. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand |
Population size (N) | Population of UK and USA | |
Country | UK and USA | |
Setting | Community based | |
Design | Mathematical modeling | |
Objectives | To assess the potential role of a number of public health measures -so-called non-pharmaceutical interventions (NPIs) aimed at reducing contact rates in the population and thereby reducing transmission of the virus. | |
Study detail | An individual-based simulation model which is developed to support influenza pandemic was modified to explore scenarios for COVID-19. | |
Interventions | Non-pharmaceutical interventions | |
Results | ➢ To reduce R0 to close to 1 or below, a combination of case isolation, social distancing of the entire population and either household quarantine or school and university closure are required. ➢ Optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. | |
21 | Author/s & title [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 |
Population size (N) | Population of UK | |
Country | UK | |
Setting | Community based | |
Design | Mathematical modeling | |
Objectives | To understand what combination of measures-including novel digital tracing approaches and less intensive physical distancing-may be required to reduce transmission of SARS-CoV-2. | |
Study detail | Using a model of individual-level transmission stratified by setting (household, work, school, other) based on BBC pandemic data from 40,162 UK participants, the impact of a range of different testing, isolation, tracing and physical distancing scenarios were simulated. | |
Interventions | Isolation, testing, contact tracing and physical distancing | |
Results | ➢ Combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone (50–60% compared to 2–30%). ➢ If limits are placed on gatherings outside of home/school/work, then manual contact tracing of acquaintances only could have a similar effect on transmission reduction as detailed contact tracing. ➢ High proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective R0 that is below one in the absence of other measures. | |
22 | Author/s & title [37] | Deanna M. Kennedy, et al. Modeling the effects of intervention strategies on COVID-19 transmission dynamics |
Population size (N) | Population of USA | |
Country | USA | |
Setting | Community based | |
Design | Mathematical modeling study, SUEIHCDR | |
Objectives | To model the effects of continuous, intermittent, and stepping-down social distancing (SD) strategies and personal protection measures on COVID-19 transmission dynamics. | |
Study detail | A SUEIHCDR model was employed to model the effects of continuous, intermittent, and stepping-down social distancing (SD) strategies and personal protection measures on COVID-19 transmission dynamics, model results were based on an average of 5000 runs/simulations. | |
Interventions | Social distancing | |
Results | ➢ The stepping-down (SD) strategy was the best long-term SD strategy to minimize the peak number of active COVID-19 cases and associated deaths. ➢ The stepping-down strategy also resulted in a reduction in total time required to SD over a two-year period by 6.5% compared to an intermittent or constant SD strategy. ➢ An 80-day SD time-window was statistically more effective in maintaining control over the COVID-19 pandemic than a 40-day window. | |
23 | Author/s & title [38] | Biao Tang, et al. Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions |
Population size (N) | Population of China | |
Country | China | |
Setting | Community based, health care | |
Design | Mathematical Modeling, R0 = 6.47 | |
Objectives | To estimate the basic reproduction number by means of mathematical modeling for determining the potential and severity of an outbreak and providing critical information for identifying the type of disease interventions and intensity based on data obtained from laboratory confirmed Covid-19 cases in mainland china. | |
Study detail | A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and intervention measures. | |
Interventions | Contact tracing, quarantine and isolation | |
Results | ➢ Interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk. ➢ With travel restriction (no imported exposed individuals to Beijing), the number of infected individuals in seven days will decrease by 91.14% in Beijing, compared with the scenario of no travel restriction. | |
24 | Author/s & title [39] | Zifeng Yang, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions |
Population size (N) | Population of china | |
Country | China | |
Setting | Community based | |
Design | Mathematical Modeling, SEIR and an artificial intelligence (AI) approach | |
Objectives | To predict the epidemic progression of COVID-19. | |
Study detail | A modified susceptible-exposed-infected-removed (SEIR) epidemiological model was used that incorporates the domestic migration data before and after January 23 and the most recent COVID-19 epidemiological data to predict the epidemic progression. | |
Interventions | Strict controls on travel, quarantine and extensive monitoring of suspected cases | |
Results | ➢ A five-day delay in implementation would have increased epidemic size in mainland China three-fold. ➢ Lifting the Hubei quarantine would lead to a second epidemic peak in Hubei province in mid- March and extend the epidemic to late April. | |
25 | Author/s & title [40] | Laura Di Domenico, et al. Expected impact of lockdown in ÃŽle-de-France and possible exit strategies |
Population size (N) | Population of France | |
Country | France | |
Setting | Community based | |
Design | A stochastic discrete age-structured epidemic modeling | |
Objectives | To (i) assess the current epidemic situation, (ii) evaluate the expected impact of the lockdown implemented in France on March 17, 2020, and (iii) estimate the effectiveness of possible exit strategies. | |
Study detail | A stochastic discrete age-structured epidemic model based on demographic and age profile data of France were considered. | |
Interventions | Lockdown with other interventions | |
Results | ➢ Prior to lockdown R0 is estimated at 3.0 [2.8, 3.2] (95% CI) and the population infected by COVID-19 as of April 5 to be in the range 1 to 6%. ➢ The average number of contacts is predicted to be reduced by 80% during lockdown, leading to a substantial reduction of the reproductive number (RLD = 0.68 [0.62–0.73]). ➢ Lifting the lockdown with no exit strategy would lead to a second wave largely overwhelming the healthcare system. ➢ Extensive case-finding, testing and isolation are required to envision social distancing strategies that gradually relax current constraints (larger fraction of individuals going back to work, progressive reopening of activities), while keeping schools closed and seniors isolated. |