Travel-related control measures to contain the COVID-19 pandemic: a rapid review.

In late 2019, first cases of coronavirus disease 2019, or COVID-19, caused by the novel coronavirus SARS-CoV-2, were reported in Wuhan, China. Subsequently COVID-19 spread rapidly around the world. To contain the ensuing pandemic, numerous countries have implemented control measures related to international travel, including border closures, partial travel restrictions, entry or exit screening, and quarantine of travellers. To assess the effectiveness of travel-related control measures during the COVID-19 pandemic on infectious disease and screening-related outcomes. We searched MEDLINE, Embase and COVID-19-specific databases, including the WHO Global Database on COVID-19 Research, the Cochrane COVID-19 Study Register, and the CDC COVID-19 Research Database on 26 June 2020. We also conducted backward-citation searches with existing reviews. We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across national borders during the COVID-19 pandemic. We also included studies concerned with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) as indirect evidence. Primary outcomes were cases avoided, cases detected and a shift in epidemic development due to the measures. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. One review author screened titles and abstracts; all excluded abstracts were screened in duplicate. Two review authors independently screened full texts. One review author extracted data, assessed risk of bias and appraised study quality. At least one additional review author checked for correctness of all data reported in the 'Risk of bias' assessment, quality appraisal and data synthesis. For assessing the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, ROBINS-I for observational ecological studies and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed certainty of evidence with GRADE, and the review author team discussed ratings. We included 40 records reporting on 36 unique studies. We found 17 modelling studies, 7 observational screening studies and one observational ecological study on COVID-19, four modelling and six observational studies on SARS, and one modelling study on SARS and MERS, covering a variety of settings and epidemic stages. Most studies compared travel-related control measures against a counterfactual scenario in which the intervention measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of travel restrictions, or a combination of measures. There were concerns with the quality of many modelling studies and the risk of bias of observational studies. Many modelling studies used potentially inappropriate assumptions about the structure and input parameters of models, and failed to adequately assess uncertainty. Concerns with observational screening studies commonly related to the reference test and the flow of the screening process. Studies on COVID-19 Travel restrictions reducing cross-border travel Eleven studies employed models to simulate a reduction in travel volume; one observational ecological study assessed travel restrictions in response to the COVID-19 pandemic. Very low-certainty evidence from modelling studies suggests that when implemented at the beginning of the outbreak, cross-border travel restrictions may lead to a reduction in the number of new cases of between 26% to 90% (4 studies), the number of deaths (1 study), the time to outbreak of between 2 and 26 days (2 studies), the risk of outbreak of between 1% to 37% (2 studies), and the effective reproduction number (1 modelling and 1 observational ecological study). Low-certainty evidence from modelling studies suggests a reduction in the number of imported or exported cases of between 70% to 81% (5 studies), and in the growth acceleration of epidemic progression (1 study). Screening at borders with or without quarantine Evidence from three modelling studies of entry and exit symptom screening without quarantine suggests delays in the time to outbreak of between 1 to 183 days (very low-certainty evidence) and a detection rate of infected travellers of between 10% to 53% (low-certainty evidence). Six observational studies of entry and exit screening were conducted in specific settings such as evacuation flights and cruise ship outbreaks. Screening approaches varied but followed a similar structure, involving symptom screening of all individuals at departure or upon arrival, followed by quarantine, and different procedures for observation and PCR testing over a period of at least 14 days. The proportion of cases detected ranged from 0% to 91% (depending on the screening approach), and the positive predictive value ranged from 0% to 100% (very low-certainty evidence). The outcomes, however, should be interpreted in relation to both the screening approach used and the prevalence of infection among the travellers screened; for example, symptom-based screening alone generally performed worse than a combination of symptom-based and PCR screening with subsequent observation during quarantine. Quarantine of travellers Evidence from one modelling study simulating a 14-day quarantine suggests a reduction in the number of cases seeded by imported cases; larger reductions were seen with increasing levels of quarantine compliance ranging from 277 to 19 cases with rates of compliance modelled between 70% to 100% (very low-certainty evidence). With much of the evidence deriving from modelling studies, notably for travel restrictions reducing cross-border travel and quarantine of travellers, there is a lack of 'real-life' evidence for many of these measures. The certainty of the evidence for most travel-related control measures is very low and the true effects may be substantially different from those reported here. Nevertheless, some travel-related control measures during the COVID-19 pandemic may have a positive impact on infectious disease outcomes. Broadly, travel restrictions may limit the spread of disease across national borders. Entry and exit symptom screening measures on their own are not likely to be effective in detecting a meaningful proportion of cases to prevent seeding new cases within the protected region; combined with subsequent quarantine, observation and PCR testing, the effectiveness is likely to improve. There was insufficient evidence to draw firm conclusions about the effectiveness of travel-related quarantine on its own. Some of the included studies suggest that effects are likely to depend on factors such as the stage of the epidemic, the interconnectedness of countries, local measures undertaken to contain community transmission, and the extent of implementation and adherence.

Burns J ，Movsisyan A ，Stratil JM ，Coenen M ，Emmert-Fees KM ，Geffert K ，Hoffmann S ，Horstick O ，Laxy M ，Pfadenhauer LM ，von Philipsborn P ，Sell K ，Voss S ，Rehfuess E ... -  《Cochrane Database of Systematic Reviews》

International travel-related control measures to contain the COVID-19 pandemic: a rapid review.

In late 2019, the first cases of coronavirus disease 2019 (COVID-19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers. To assess the effectiveness of international travel-related control measures during the COVID-19 pandemic on infectious disease transmission and screening-related outcomes. We searched MEDLINE, Embase and COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO Global Database on COVID-19 Research to 13 November 2020. We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across international borders during the COVID-19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID-19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements. Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel-related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross-border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low-certainty evidence for a reduction in COVID-19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low-certainty evidence that cross-border travel controls can slow the spread of COVID-19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure-based screening or test-based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure-based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate-certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low-certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low-certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low-certainty evidence), although all but one study observed this proportion to be less than 54%. For test-based screening, one modelling study provided very low-certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low-certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low- to low-certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low-certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low- to low-certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low-certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine. With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross-border travel and quarantine of travellers, there is a lack of 'real-world' evidence. The certainty of the evidence for most travel-related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure-based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure-based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel-related control measures from a societal perspective.

Burns J ，Movsisyan A ，Stratil JM ，Biallas RL ，Coenen M ，Emmert-Fees KM ，Geffert K ，Hoffmann S ，Horstick O ，Laxy M ，Klinger C ，Kratzer S ，Litwin T ，Norris S ，Pfadenhauer LM ，von Philipsborn P ，Sell K ，Stadelmaier J ，Verboom B ，Voss S ，Wabnitz K ，Rehfuess E ... -  《Cochrane Database of Systematic Reviews》

Measures implemented in the school setting to contain the COVID-19 pandemic.

In response to the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the impact of coronavirus disease 2019 (COVID-19), governments have implemented a variety of measures to control the spread of the virus and the associated disease. Among these, have been measures to control the pandemic in primary and secondary school settings. To assess the effectiveness of measures implemented in the school setting to safely reopen schools, or keep schools open, or both, during the COVID-19 pandemic, with particular focus on the different types of measures implemented in school settings and the outcomes used to measure their impacts on transmission-related outcomes, healthcare utilisation outcomes, other health outcomes as well as societal, economic, and ecological outcomes.  SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and the Educational Resources Information Center, as well as COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO COVID-19 Global literature on coronavirus disease (indexing preprints) on 9 December 2020. We conducted backward-citation searches with existing reviews. We considered experimental (i.e. randomised controlled trials; RCTs), quasi-experimental, observational and modelling studies assessing the effects of measures implemented in the school setting to safely reopen schools, or keep schools open, or both, during the COVID-19 pandemic. Outcome categories were (i) transmission-related outcomes (e.g. number or proportion of cases); (ii) healthcare utilisation outcomes (e.g. number or proportion of hospitalisations); (iii) other health outcomes (e.g. physical, social and mental health); and (iv) societal, economic and ecological outcomes (e.g. costs, human resources and education). We considered studies that included any population at risk of becoming infected with SARS-CoV-2 and/or developing COVID-19 disease including students, teachers, other school staff, or members of the wider community.  DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles, abstracts and full texts. One review author extracted data and critically appraised each study. One additional review author validated the extracted data. To critically appraise included studies, we used the ROBINS-I tool for quasi-experimental and observational studies, the QUADAS-2 tool for observational screening studies, and a bespoke tool for modelling studies. We synthesised findings narratively. Three review authors made an initial assessment of the certainty of evidence with GRADE, and several review authors discussed and agreed on the ratings. We included 38 unique studies in the analysis, comprising 33 modelling studies, three observational studies, one quasi-experimental and one experimental study with modelling components. Measures fell into four broad categories: (i) measures reducing the opportunity for contacts; (ii) measures making contacts safer; (iii) surveillance and response measures; and (iv) multicomponent measures. As comparators, we encountered the operation of schools with no measures in place, less intense measures in place, single versus multicomponent measures in place, or closure of schools. Across all intervention categories and all study designs, very low- to low-certainty evidence ratings limit our confidence in the findings. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the model structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to deviations from intended interventions or missing data. Across all categories, few studies reported on implementation or described how measures were implemented. Where we describe effects as 'positive', the direction of the point estimate of the effect favours the intervention(s); 'negative' effects do not favour the intervention.  We found 23 modelling studies assessing measures reducing the opportunity for contacts (i.e. alternating attendance, reduced class size). Most of these studies assessed transmission and healthcare utilisation outcomes, and all of these studies showed a reduction in transmission (e.g. a reduction in the number or proportion of cases, reproduction number) and healthcare utilisation (i.e. fewer hospitalisations) and mixed or negative effects on societal, economic and ecological outcomes (i.e. fewer number of days spent in school). We identified 11 modelling studies and two observational studies assessing measures making contacts safer (i.e. mask wearing, cleaning, handwashing, ventilation). Five studies assessed the impact of combined measures to make contacts safer. They assessed transmission-related, healthcare utilisation, other health, and societal, economic and ecological outcomes. Most of these studies showed a reduction in transmission, and a reduction in hospitalisations; however, studies showed mixed or negative effects on societal, economic and ecological outcomes (i.e. fewer number of days spent in school). We identified 13 modelling studies and one observational study assessing surveillance and response measures, including testing and isolation, and symptomatic screening and isolation. Twelve studies focused on mass testing and isolation measures, while two looked specifically at symptom-based screening and isolation. Outcomes included transmission, healthcare utilisation, other health, and societal, economic and ecological outcomes. Most of these studies showed effects in favour of the intervention in terms of reductions in transmission and hospitalisations, however some showed mixed or negative effects on societal, economic and ecological outcomes (e.g. fewer number of days spent in school). We found three studies that reported outcomes relating to multicomponent measures, where it was not possible to disaggregate the effects of each individual intervention, including one modelling, one observational and one quasi-experimental study. These studies employed interventions, such as physical distancing, modification of school activities, testing, and exemption of high-risk students, using measures such as hand hygiene and mask wearing. Most of these studies showed a reduction in transmission, however some showed mixed or no effects.   As the majority of studies included in the review were modelling studies, there was a lack of empirical, real-world data, which meant that there were very little data on the actual implementation of interventions. Our review suggests that a broad range of measures implemented in the school setting can have positive impacts on the transmission of SARS-CoV-2, and on healthcare utilisation outcomes related to COVID-19. The certainty of the evidence for most intervention-outcome combinations is very low, and the true effects of these measures are likely to be substantially different from those reported here. Measures implemented in the school setting may limit the number or proportion of cases and deaths, and may delay the progression of the pandemic. However, they may also lead to negative unintended consequences, such as fewer days spent in school (beyond those intended by the intervention). Further, most studies assessed the effects of a combination of interventions, which could not be disentangled to estimate their specific effects. Studies assessing measures to reduce contacts and to make contacts safer consistently predicted positive effects on transmission and healthcare utilisation, but may reduce the number of days students spent at school. Studies assessing surveillance and response measures predicted reductions in hospitalisations and school days missed due to infection or quarantine, however, there was mixed evidence on resources needed for surveillance. Evidence on multicomponent measures was mixed, mostly due to comparators. The magnitude of effects depends on multiple factors. New studies published since the original search date might heavily influence the overall conclusions and interpretation of findings for this review.

Krishnaratne S ，Littlecott H ，Sell K ，Burns J ，Rabe JE ，Stratil JM ，Litwin T ，Kreutz C ，Coenen M ，Geffert K ，Boger AH ，Movsisyan A ，Kratzer S ，Klinger C ，Wabnitz K ，Strahwald B ，Verboom B ，Rehfuess E ，Biallas RL ，Jung-Sievers C ，Voss S ，Pfadenhauer LM ... -  《Cochrane Database of Systematic Reviews》

Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review.

Coronavirus disease 2019 (COVID-19) is a rapidly emerging disease classified as a pandemic by the World Health Organization (WHO). To support the WHO with their recommendations on quarantine, we conducted a rapid review on the effectiveness of quarantine during severe coronavirus outbreaks. To assess the effects of quarantine (alone or in combination with other measures) of individuals who had contact with confirmed or suspected cases of COVID-19, who travelled from countries with a declared outbreak, or who live in regions with high disease transmission. An information specialist searched the Cochrane COVID-19 Study Register, and updated the search in PubMed, Ovid MEDLINE, WHO Global Index Medicus, Embase, and CINAHL on 23 June 2020. Cohort studies, case-control studies, time series, interrupted time series, case series, and mathematical modelling studies that assessed the effect of any type of quarantine to control COVID-19. We also included studies on SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome) as indirect evidence for the current coronavirus outbreak. Two review authors independently screened abstracts and titles in duplicate. Two review authors then independently screened all potentially relevant full-text publications. One review author extracted data, assessed the risk of bias and assessed the certainty of evidence with GRADE and a second review author checked the assessment. We used three different tools to assess risk of bias, depending on the study design: ROBINS-I for non-randomised studies of interventions, a tool provided by Cochrane Childhood Cancer for non-randomised, non-controlled studies, and recommendations from the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) for modelling studies. We rated the certainty of evidence for the four primary outcomes: incidence, onward transmission, mortality, and costs. We included 51 studies; 4 observational studies and 28 modelling studies on COVID-19, one observational and one modelling study on MERS, three observational and 11 modelling studies on SARS, and three modelling studies on SARS and other infectious diseases. Because of the diverse methods of measurement and analysis across the outcomes of interest, we could not conduct a meta-analysis and undertook a narrative synthesis. We judged risk of bias to be moderate for 2/3 non-randomized studies of interventions (NRSIs) and serious for 1/3 NRSI. We rated risk of bias moderate for 4/5 non-controlled cohort studies, and serious for 1/5. We rated modelling studies as having no concerns for 13 studies, moderate concerns for 17 studies and major concerns for 13 studies. Quarantine for individuals who were in contact with a confirmed/suspected COVID-19 case in comparison to no quarantine Modelling studies consistently reported a benefit of the simulated quarantine measures, for example, quarantine of people exposed to confirmed or suspected cases may have averted 44% to 96% of incident cases and 31% to 76% of deaths compared to no measures based on different scenarios (incident cases: 6 modelling studies on COVID-19, 1 on SARS; mortality: 2 modelling studies on COVID-19, 1 on SARS, low-certainty evidence). Studies also indicated that there may be a reduction in the basic reproduction number ranging from 37% to 88% due to the implementation of quarantine (5 modelling studies on COVID-19, low-certainty evidence). Very low-certainty evidence suggests that the earlier quarantine measures are implemented, the greater the cost savings may be (2 modelling studies on SARS). Quarantine in combination with other measures to contain COVID-19 in comparison to other measures without quarantine or no measures When the models combined quarantine with other prevention and control measures, such as school closures, travel restrictions and social distancing, the models demonstrated that there may be a larger effect on the reduction of new cases, transmissions and deaths than measures without quarantine or no interventions (incident cases: 9 modelling studies on COVID-19; onward transmission: 5 modelling studies on COVID-19; mortality: 5 modelling studies on COVID-19, low-certainty evidence). Studies on SARS and MERS were consistent with findings from the studies on COVID-19. Quarantine for individuals travelling from a country with a declared COVID-19 outbreak compared to no quarantine Very low-certainty evidence indicated that the effect of quarantine of travellers from a country with a declared outbreak on reducing incidence and deaths may be small for SARS, but might be larger for COVID-19 (2 observational studies on COVID-19 and 2 observational studies on SARS). The current evidence is limited because most studies on COVID-19 are mathematical modelling studies that make different assumptions on important model parameters. Findings consistently indicate that quarantine is important in reducing incidence and mortality during the COVID-19 pandemic, although there is uncertainty over the magnitude of the effect. Early implementation of quarantine and combining quarantine with other public health measures is important to ensure effectiveness. In order to maintain the best possible balance of measures, decision makers must constantly monitor the outbreak and the impact of the measures implemented. This review was originally commissioned by the WHO and supported by Danube-University-Krems. The update was self-initiated by the review authors.

Nussbaumer-Streit B ，Mayr V ，Dobrescu AI ，Chapman A ，Persad E ，Klerings I ，Wagner G ，Siebert U ，Ledinger D ，Zachariah C ，Gartlehner G ... -  《Cochrane Database of Systematic Reviews》

Universal screening for SARS-CoV-2 infection: a rapid review.

Coronavirus disease 2019 (COVID-19) is caused by the novel betacoronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Most people infected with SARS-CoV-2 have mild disease with unspecific symptoms, but about 5% become critically ill with respiratory failure, septic shock and multiple organ failure. An unknown proportion of infected individuals never experience COVID-19 symptoms although they are infectious, that is, they remain asymptomatic. Those who develop the disease, go through a presymptomatic period during which they are infectious. Universal screening for SARS-CoV-2 infections to detect individuals who are infected before they present clinically, could therefore be an important measure to contain the spread of the disease. We conducted a rapid review to assess (1) the effectiveness of universal screening for SARS-CoV-2 infection compared with no screening and (2) the accuracy of universal screening in people who have not presented to clinical care for symptoms of COVID-19. An information specialist searched Ovid MEDLINE and the Centers for Disease Control (CDC) COVID-19 Research Articles Downloadable Database up to 26 May 2020. We searched Embase.com, the CENTRAL, and the Cochrane Covid-19 Study Register on 14 April 2020. We searched LitCovid to 4 April 2020. The World Health Organization (WHO) provided records from daily searches in Chinese databases and in PubMed up to 15 April 2020. We also searched three model repositories (Covid-Analytics, Models of Infectious Disease Agent Study [MIDAS], and Society for Medical Decision Making) on 8 April 2020. Trials, observational studies, or mathematical modelling studies assessing screening effectiveness or screening accuracy among general populations in which the prevalence of SARS-CoV2 is unknown. After pilot testing review forms, one review author screened titles and abstracts. Two review authors independently screened the full text of studies and resolved any disagreements by discussion with a third review author. Abstracts excluded by a first review author were dually reviewed by a second review author prior to exclusion. One review author independently extracted data, which was checked by a second review author for completeness and accuracy. Two review authors independently rated the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for diagnostic accuracy studies and a modified form designed originally for economic evaluations for modelling studies. We resolved differences by consensus. We synthesized the evidence in narrative and tabular formats. We rated the certainty of evidence for days to outbreak, transmission, cases missed and detected, diagnostic accuracy (i.e. true positives, false positives, true negatives, false negatives) using the GRADE approach. We included 22 publications. Two modelling studies reported on effectiveness of universal screening. Twenty studies (17 cohort studies and 3 modelling studies) reported on screening test accuracy. Effectiveness of screening We included two modelling studies. One study suggests that symptom screening at travel hubs, such as airports, may slightly slow but not stop the importation of infected cases (assuming 10 or 100 infected travellers per week reduced the delay in a local outbreak to 8 days or 1 day, respectively). We assessed risk of bias as minor or no concerns, and certainty of evidence was low, downgraded for very serious indirectness. The second modelling study provides very low-certainty evidence that screening of healthcare workers in emergency departments using laboratory tests may reduce transmission to patients and other healthcare workers (assuming a transmission constant of 1.2 new infections per 10,000 people, weekly screening reduced infections by 5.1% within 30 days). The certainty of evidence was very low, downgraded for high risk of bias (major concerns) and indirectness. No modelling studies reported on harms of screening. Screening test accuracy All 17 cohort studies compared an index screening strategy to a reference reverse transcriptase polymerase chain reaction (RT-PCR) test. All but one study reported on the accuracy of single point-in-time screening and varied widely in prevalence of SARS-CoV-2, settings, and methods of measurement. We assessed the overall risk of bias as unclear in 16 out of 17 studies, mainly due to limited information on the index test and reference standard. We rated one study as being at high risk of bias due to the inclusion of two separate populations with likely different prevalences. For several screening strategies, the estimates of sensitivity came from small samples. For single point-in-time strategies, for symptom assessment, the sensitivity from 12 cohorts (524 people) ranged from 0.00 to 0.60 (very low-certainty evidence) and the specificity from 12 cohorts (16,165 people) ranged from 0.66 to 1.00 (low-certainty evidence). For screening using direct temperature measurement (3 cohorts, 822 people), international travel history (2 cohorts, 13,080 people), or exposure to known infected people (3 cohorts, 13,205 people) or suspected infected people (2 cohorts, 954 people), sensitivity ranged from 0.00 to 0.23 (very low- to low-certainty evidence) and specificity ranged from 0.90 to 1.00 (low- to moderate-certainty evidence). For symptom assessment plus direct temperature measurement (2 cohorts, 779 people), sensitivity ranged from 0.12 to 0.69 (very low-certainty evidence) and specificity from 0.90 to 1.00 (low-certainty evidence). For rapid PCR test (1 cohort, 21 people), sensitivity was 0.80 (95% confidence interval (CI) 0.44 to 0.96; very low-certainty evidence) and specificity was 0.73 (95% CI 0.39 to 0.94; very low-certainty evidence). One cohort (76 people) reported on repeated screening with symptom assessment and demonstrates a sensitivity of 0.44 (95% CI 0.29 to 0.59; very low-certainty evidence) and specificity of 0.62 (95% CI 0.42 to 0.79; low-certainty evidence). Three modelling studies evaluated the accuracy of screening at airports. The main outcomes measured were cases missed or detected by entry or exit screening, or both, at airports. One study suggests very low sensitivity at 0.30 (95% CI 0.1 to 0.53), missing 70% of infected travellers. Another study described an unrealistic scenario to achieve a 90% detection rate, requiring 0% asymptomatic infections. The final study provides very uncertain evidence due to low methodological quality. The evidence base for the effectiveness of screening comes from two mathematical modelling studies and is limited by their assumptions. Low-certainty evidence suggests that screening at travel hubs may slightly slow the importation of infected cases. This review highlights the uncertainty and variation in accuracy of screening strategies. A high proportion of infected individuals may be missed and go on to infect others, and some healthy individuals may be falsely identified as positive, requiring confirmatory testing and potentially leading to the unnecessary isolation of these individuals. Further studies need to evaluate the utility of rapid laboratory tests, combined screening, and repeated screening. More research is also needed on reference standards with greater accuracy than RT-PCR. Given the poor sensitivity of existing approaches, our findings point to the need for greater emphasis on other ways that may prevent transmission such as face coverings, physical distancing, quarantine, and adequate personal protective equipment for frontline workers.

Viswanathan M ，Kahwati L ，Jahn B ，Giger K ，Dobrescu AI ，Hill C ，Klerings I ，Meixner J ，Persad E ，Teufer B ，Gartlehner G ... -  《Cochrane Database of Systematic Reviews》