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Travel-related control measures to contain the COVID-19 pandemic: a rapid review.
Cochrane Database Syst Rev. 2020 10 05; 10:CD013717.CD

Abstract

BACKGROUND

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.

OBJECTIVES

To assess the effectiveness of travel-related control measures during the COVID-19 pandemic on infectious disease and screening-related outcomes.

SEARCH METHODS

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.

SELECTION CRITERIA

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.

DATA COLLECTION AND ANALYSIS

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.

MAIN RESULTS

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).

AUTHORS' CONCLUSIONS

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.

Authors+Show Affiliations

Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany.Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.Institute for Medical Information Processing, Biometry and Epidemiology, IBE, LMU Munich, Munich, Germany. Pettenkofer School of Public Health, Munich, Germany.

Pub Type(s)

Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't
Systematic Review

Language

eng

PubMed ID

33502002

Citation

Burns, Jacob, et al. "Travel-related Control Measures to Contain the COVID-19 Pandemic: a Rapid Review." The Cochrane Database of Systematic Reviews, vol. 10, 2020, p. CD013717.
Burns J, Movsisyan A, Stratil JM, et al. Travel-related control measures to contain the COVID-19 pandemic: a rapid review. Cochrane Database Syst Rev. 2020;10:CD013717.
Burns, J., Movsisyan, A., Stratil, J. M., Coenen, M., Emmert-Fees, K. M., Geffert, K., Hoffmann, S., Horstick, O., Laxy, M., Pfadenhauer, L. M., von Philipsborn, P., Sell, K., Voss, S., & Rehfuess, E. (2020). Travel-related control measures to contain the COVID-19 pandemic: a rapid review. The Cochrane Database of Systematic Reviews, 10, CD013717. https://doi.org/10.1002/14651858.CD013717
Burns J, et al. Travel-related Control Measures to Contain the COVID-19 Pandemic: a Rapid Review. Cochrane Database Syst Rev. 2020 10 5;10:CD013717. PubMed PMID: 33502002.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Travel-related control measures to contain the COVID-19 pandemic: a rapid review. AU - Burns,Jacob, AU - Movsisyan,Ani, AU - Stratil,Jan M, AU - Coenen,Michaela, AU - Emmert-Fees,Karl Mf, AU - Geffert,Karin, AU - Hoffmann,Sabine, AU - Horstick,Olaf, AU - Laxy,Michael, AU - Pfadenhauer,Lisa M, AU - von Philipsborn,Peter, AU - Sell,Kerstin, AU - Voss,Stephan, AU - Rehfuess,Eva, Y1 - 2020/10/05/ PY - 2021/1/27/entrez PY - 2021/1/28/pubmed PY - 2021/2/4/medline SP - CD013717 EP - CD013717 JF - The Cochrane database of systematic reviews JO - Cochrane Database Syst Rev VL - 10 N2 - BACKGROUND: 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. OBJECTIVES: To assess the effectiveness of travel-related control measures during the COVID-19 pandemic on infectious disease and screening-related outcomes. SEARCH METHODS: 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. SELECTION CRITERIA: 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. DATA COLLECTION AND ANALYSIS: 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. MAIN RESULTS: 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). AUTHORS' CONCLUSIONS: 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. SN - 1469-493X UR - https://www.unboundmedicine.com/medline/citation/33502002/Travel_related_control_measures_to_contain_the_COVID_19_pandemic:_a_rapid_review_ L2 - https://doi.org/10.1002/14651858.CD013717 DB - PRIME DP - Unbound Medicine ER -