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Meta-Analysis
. 2021 Mar 25;3(3):CD013717.
doi: 10.1002/14651858.CD013717.pub2.

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

Jacob Burns  1   2 , Ani Movsisyan  1   2 , Jan M Stratil  1   2 , Renke Lars Biallas  1   2 , Michaela Coenen  1   2 , Karl Mf Emmert-Fees  3 , Karin Geffert  1   2 , Sabine Hoffmann  1   2 , Olaf Horstick  4 , Michael Laxy  3   5 , Carmen Klinger  1   2 , Suzie Kratzer  1   2 , Tim Litwin  6 , Susan Norris  1   2   7 , Lisa M Pfadenhauer  1   2 , Peter von Philipsborn  1   2 , Kerstin Sell  1   2 , Julia Stadelmaier  8 , Ben Verboom  1   2 , Stephan Voss  1   2 , Katharina Wabnitz  1   2 , Eva Rehfuess  1   2
Affiliations
Meta-Analysis

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

Jacob Burns et al. Cochrane Database Syst Rev. .

Abstract

Background: 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.

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

Search methods: 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.

Selection criteria: 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.

Data collection and analysis: 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.

Main results: 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.

Authors' conclusions: 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.

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Conflict of interest statement

Jacob Burns: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Ani Movsisyan: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Jan M Stratil: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Renke L Biallas: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Michaela Coenen: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Karl Emmert‐Fees: none known

Karin Geffert: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Sabine Hoffman: none known

Olaf Horstick: none known

Michael Laxy: none known

Carmen Klinger: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Suzie Kratzer: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Tim Litwin: the Institute for Medical Biometry and Statistics (IMBI) at the University of Freiburg received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Susan Norris: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Lisa M Pfadenhauer: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Peter von Philipsborn: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Kerstin Sell: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Julia Stadelmaier: the Institute for Evidence in Medicine at the University of Freiburg received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Ben Verboom: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Stephan Voss: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Katherina Wabnitz: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Eva Rehfuess: the Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the WHO for the conduct of this review. The WHO provided input which informed the review protocol and scope. The WHO did not exert any influence on how findings were interpreted. The role of the WHO is clearly specified in the review itself. The Chair for Public Health and Health Services Research at the Institute for Medical Information Processing, Biometry and Epidemiology received funding from the German Federal Ministry of Education and Research (BMBF) as part of the COVID‐19 evidence ecosystem (CEOsys) project. No other conflicts of interest are known.

Figures

1
1
Systematic review PRISMA flow diagram
2
2
Summary of the proportions of cases detected by the measure from observational studies. Measures portrayed include exit and/or entry screening (top panel) and PCR tests (middle panel), as well as for combined measures exit and/or entry screening with quarantine and further screening, in the form of symptom observation and/or PCR tests (bottom panel). Notes: Yamahata 2020 employed a form of symptom screening aboard a cruise ship, thus representing a very different context than all other studies. Ng 2020 employed a delayed PCR test on day 3. Lagier 2020 and Lio 2020 employed a PCR test on arrival and on day 2, respectively, however given that they did not identify cases they are not portrayed in this figure. The five evacuation flights assessed in Shaikh Abdul Karim 2020 had very different COVID‐19 prevalences, with no cases associated with three flights, but with 2/104 and 80/124 on the remaining two flights.
See this image and copyright information in PMC

Update of

References

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    1. Pinotti F, Di Domenico L, Ortega E, Mancastroppa M, Pullano G, Valdano E, et al. Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study. PLoS medicine 2020;17(7):e1003193. - PMC - PubMed
Quilty 2020 {published data only}
    1. Quilty BJ, Clifford S, Flasche S, Eggo RM, CCMID nCoV Working Group. Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV). Eurosurveillance 2020;25(5):2. [DOI: ] - PMC - PubMed
Russell TW 2020 {published data only}
    1. Russell TW, Wu JT, Clifford S, Edmunds WJ, Kucharski AJ, Jit M. Effect of internationally imported cases on internal spread of COVID-19: a mathematical modelling study. Lancet Public Health 2021;6(1):e12-20. - PMC - PubMed
Russell WA 2020 {published data only}
    1. Russell WA, Buckeridge DL. Effectiveness of quarantine and testing to prevent COVID-19 transmission from arriving travelers. medRxiv 2020.
Ryu 2020 {published data only}
    1. Ryu S, Ali ST, Lim JS, Chun BC. Estimation of the excess COVID-19 cases in Seoul, South Korea by the students arriving from China. International Journal of Environmental Research and Public Health 2020;17:3113. [DOI: ] - PMC - PubMed
Shaikh Abdul Karim 2020 {published data only}
    1. Shaikh Abdul Karim S, Md Tahir FA, Mohamad UK, Abu Bakar M, Mohamad KN, Suleiman M, et al. Experience repatriation of citizens from epicentre using commercial flights during COVID-19 pandemic. International Journal of Emergency Medicine 2020;13(1):50. - PMC - PubMed
Shi 2020 {published data only}
    1. Shi S, Tanaka S, Ueno R, Gilmour S, Tanoue Y, Kawashima T, et al. Travel restrictions and SARS-CoV-2 transmission: an effective distance approach to estimate impact. Bulletin of the World Health Organization 2020;98(8):518-29. - PMC - PubMed
Sruthi 2020 {published data only}
    1. Sruthi CK, Biswal MR, Saraswat B, Joshi H, Prakash MK. How policies on restaurants, bars, nightclubs, masks, schools, and travel influenced Swiss COVID-19 reproduction ratios. medRxiv 2020.
Steyn 2020 {published data only}
    1. Steyn N, Plank MJ, James A, Binny RN, Hendy S, Lustig A. Managing the risk of a COVID-19 outbreak from border arrivals. medRxiv 2020. - PMC - PubMed
Taylor 2020 {published data only}
    1. Taylor R, McCarthy CA, Patel V, Moir R, Kelly L, Snary E. The risk of introducing SARS-CoV-2 to the UK via international travel in August 2020. medRxiv 2020.
Utsunomiya 2020 {published data only}
    1. Utsunomiya YT, Utsunomiya AT, Torrecilha RB, Paulan SC, Milanesi M, Garcia JF. Growth rate and acceleration analysis of the COVID-19 pandemic reveals the effect of public health measures in real time. Frontiers in Medicine 2020;7:247. [DOI: 10.3389/fmed.2020.00247] - DOI - PMC - PubMed
Wells 2020 {published data only}
    1. 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. Proceedings of the National Academy of Sciences of the United States of America 2020;117(13):7504-9. [DOI: ] - PMC - PubMed
Wilson 2020 {published data only}
    1. Wilson N, Baker MG, Eichner M. Estimating the impact of control measures to prevent outbreaks of COVID-19 associated with air travel into a COVID-19-free country: a simulation modelling study. medRxiv 2020. [DOI: 10.1101/2020.06.10.20127977] - DOI - PMC - PubMed
Wong J 2020 {published data only}
    1. Wong J, Abdul Aziz ABZ, Chaw L, Mahamud A, Griffith MM, Lo YR, et al. High proportion of asymptomatic and presymptomatic COVID-19 infections in air passengers to Brunei. Journal of Travel Medicine 2020;27(5):taaa066. - PMC - PubMed
Wong MC 2020 {published data only}
    1. Wong MC, Ng RW, Chong KC, Lai CK, Huang J, Chen Z, et al. Stringent containment measures without complete city lockdown to achieve low incidence and mortality across two waves of COVID-19 in Hong Kong. BMJ Global Health 2020;5(10). - PMC - PubMed
Yamahata 2020 {published data only}
    1. Tsuboi M, Hachiya M, Noda S, Iso H, Umeda T. Epidemiology and quarantine measures during COVID-19 outbreak on the cruise ship Diamond Princess docked at Yokohama, Japan in 2020: a descriptive analysis. Global Health & Medicine 2020;2(2):102-6. [DOI: 10.35772/ghm.2020.01037] - DOI - PMC - PubMed
    1. Yamahata Y, Shibata A. Preparation for quarantine on the cruise ship Diamond Princess in Japan due to COVID-19. JMIR Public Health and Surveillance 2020;6(2):e18821. [DOI: ] - PMC - PubMed
Yang 2020 {published data only}
    1. Yang T, Liu Y, Deng W, Zhao W, Deng J. SARS-Cov-2 trajectory predictions and scenario simulations from a global perspective: a modelling study. Scientific Reports 2020;10(1):18319. - PMC - PubMed
Zhang C 2020 {published data only}
    1. Zhang C, Qian LX, Hu JQ. COVID-19 pandemic with human mobility across countries. Journal of the Operations Research Society of China 2020 Aug 3 [Epub ahead of print].
Zhang L 2020 {published data only}
    1. Zhang L, Yang H, Wang K, Zhan Y, Bian L. Measuring imported case risk of COVID-19 from inbound international flights - A case study on China. Journal of Air Transport Management 2020;89:101918. - PMC - PubMed
Zhong 2020 {published data only}
    1. Zhong L, Diagne M, Wang W, Gao J. Country distancing reveals the effectiveness of travel restrictions during COVID-19. medRxiv 2020.

References to studies excluded from this review

Adiga 2020 {published data only}
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Aravindakshan 2020 {published data only}
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Batista 2020 {published data only}
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Bell 2004 {published data only}
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Benkouiten 2013 {published data only}
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Benkouiten 2014 {published data only}
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Benkouiten 2015 {published data only}
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Borracci 2020 {published data only}
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Branas 2020 {published data only}
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Brauer 2008 {published data only}
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Camitz 2006 {published data only}
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Channapathi 2020 {published data only}
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Cowling 2020 {published data only}
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Dandekar 2020 {published data only}
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Daon 2020 {published data only}
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Dell'Omodarme 2005 {published data only}
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Dursun 2020 {published data only}
    1. Dursun ZB, Ulu-Kilic A, Alabay S, Benli AR, Celik I. COVID-19 among Turkish citizens returning from abroad. Travel Medicine and Infectious Disease 2020;37:101860. - PMC - PubMed
Eksin 2020 {published data only}
    1. Eksin C, Ndeffo-Mbah M, Weitz JS. Reacting to outbreaks at neighboring localities. medRxiv 2020. [DOI: 10.1101/2020.04.24.20078808] - DOI - PMC - PubMed
Erandi 2020 {published data only}
    1. Erandi KK, Mahasinghe AC, Perera SS, Jayasinghe S. Effectiveness of the strategies implemented in Sri Lanka for controlling the COVID-19 outbreak. Journal of Applied Mathematics 2020;2020:2954519.
Espinoza 2020 {published data only}
    1. Espinoza B, Castillo-Chavez C, Perrings C. Mobility restrictions for the control of epidemics: when do they work? SSRN 2020. [DOI: 10.2139/ssrn.3496928] - DOI - PMC - PubMed
Fang 2020 {published data only}
    1. Fang Y, Nie Y, Penny M. Transmission dynamics of the COVID-19 outbreak and effectiveness of government interventions: a data-driven analysis. Journal of Medical Virology 2020. [DOI: 10.1002/jmv.25750] - DOI - PMC - PubMed
Fouquet 2020 {published data only}
    1. Fouquet R, O'Garra T. The behavioural, welfare and environmental effects of air travel reductions during and beyond COVID-19. SSRN 2020. [DOI: ]
Fredj 2020 {published data only}
    1. Fredj HB, Cherif F. Novel corona virus disease infection in Tunisia: mathematical model and the impact of the quarantine strategy. Chaos Solitons & Fractals 2020;138:109969. - PMC - PubMed
Gardner 2016 {published data only}
    1. Gardner LM, Chughtai AA, MacIntyre CR. Risk of global spread of Middle East respiratory syndrome coronavirus (MERS-CoV) via the air transport network. Journal of Travel Medicine 2016;23(6):taw063. [DOI: 10.1093/jtm/taw063] - DOI - PMC - PubMed
Gatto 2020 {published data only}
    1. Gatto M, Bertuzzo E, Mari L, Miccoli S, Carraro L, Casagrandi R, et al. Spread and dynamics of the COVID-19 epidemic in Italy: effects of emergency containment measures. Proceedings of the National Academy of Sciences of the United States of America 2020. [DOI: 10.1073/pnas.2004978117] - DOI - PMC - PubMed
Gautret 2013a {published data only}
    1. Gautret P, Benkouiten S, Salaheddine I, Parola P, Brouqui P. Preventive measures against MERS-CoV for Hajj pilgrims. Lancet Infectious Diseases 2013;13(10):829-31. - PMC - PubMed
Gautret 2013b {published data only}
    1. Gautret P, Charrel R, Belhouchat K, Drali T, Benkouiten S, Nougairede A, et al. Lack of nasal carriage of novel corona virus (HCoV-EMC) in French Hajj pilgrims returning from the Hajj 2012, despite a high rate of respiratory symptoms. Clinical Microbiology & Infection 2013;19(7):E315-7. - PMC - PubMed
Gautret 2014 {published data only}
    1. Gautret P, Charrel R, Benkouiten S, Belhouchat K, Nougairede A, Drali T, et al. Lack of MERS coronavirus but prevalence of influenza virus in French pilgrims after 2013 Hajj. Emerging Infectious Diseases 2014;20(4):728-30. - PMC - PubMed
German 2015 {published data only}
    1. German M, Olsha R, Kristjanson E, Marchand-Austin A, Peci A, Winter AL, et al. Acute respiratory infections in travelers returning from MERS-CoV-affected areas. Emerging Infectious Diseases 2015;21(9):1654-6. - PMC - PubMed
Gill 2020 {published data only}
    1. Gill BS, Jayaraj VJ, Singh S, Ghazali MS, Cheong YL, Md Iderus NH, et al. Modelling the effectiveness of epidemic control measures in preventing the transmission of COVID-19 in Malaysia. International Journal of Environmental Research and Public Health 2020;17(15):5509. - PMC - PubMed
Godin 2021 {published data only}
    1. Godin A, Xia Y, Buckeridge DL, Mishra S, Douwes-Schultz D, Shen Y, et al. The role of case importation in explaining differences in early SARS-CoV-2 transmission dynamics in Canada - a mathematical modeling study of surveillance data. International Journal of Infectious Diseases 2021;102:254-9. - PMC - PubMed
Griffiths 2016 {published data only}
    1. Griffiths K, Charrel R, Lagier JC, Nougairede A, Simon F, Parola P, et al. Infections in symptomatic travelers returning from the Arabian peninsula to France: a retrospective cross-sectional study. Travel Medicine & Infectious Disease 2016;14(4):414-6. - PMC - PubMed
Gunthe 2020 {published data only}
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Hossain 2020 {published data only}
    1. Hossain MP, Junus A, Zhu X, Jia P, Wen TH, Pfeiffer D, et al. The effects of border control and quarantine measures on the spread of COVID-19. Epidemics 2020;32:100397. - PMC - PubMed
Hossein 2020 {published data only}
    1. Hossein RT, Shahriari S, Azad AK, Vafaee F. Real-time time-series modelling for prediction of COVID-19 spread and intervention assessment. medRxiv 2020. [DOI: 10.1101/2020.04.24.20078923] - DOI
Huang 2020 {published data only}
    1. Huang L, Li L, Dunn L, He M. Taking account of asymptomatic infections in modeling the transmission potential of the COVID-19 outbreak on the Diamond Princess cruise ship. medRxiv 2020. - PMC - PubMed
Hufnagel 2004 {published data only}
    1. Hufnagel L, Brockmann D, Geisel T. Forecast and control of epidemics in a globalized world. Proceedings of the National Academy of Sciences of the United States of America 2004;101(42):15124-9. - PMC - PubMed
Jia 2020 {published data only}
    1. Jia JS, Lu X, Yuan Y, Xu G, Jia J, Christakis NA. Population flow drives spatio-temporal distribution of COVID-19 in China. Nature 2020;582(7812):389-94. - PubMed
Johansson 2011 {published data only}
    1. Johansson MA, Arana-Vizcarrondo N, Biggerstaff BJ, Staples JE, Gallagher N, Marano N. On the treatment of airline travelers in mathematical models. PLoS ONE 2011;6(7):e22151. - PMC - PubMed
Joo 2019 {published data only}
    1. Joo H, Maskery BA, Berro AD, Rotz LD, Lee YK, Brown CM. Economic impact of the 2015 MERS outbreak on the Republic of Korea's tourism-related industries. Health Security 2019;17(2):100-8. - PMC - PubMed
Jungerman 2017 {published data only}
    1. Jungerman MR, Vonnahme LA, Washburn F, Alvarado-Ramy F. Federal travel restrictions to prevent disease transmission in the United States: an analysis of requested travel restrictions. Travel Medicine & Infectious Disease 2017;18:30-5. - PMC - PubMed
Kong 2020 {published data only}
    1. Kong XS, Liu F, Wang HB, Yang RF, Chen DB, Wang XX, et al. Epidemic prevention and control measures in China significantly curbed the epidemic of COVID-19 and influenza. medRxiv 2020. [DOI: 10.1101/2020.04.09.20058859] - DOI
Kraemer 2020 {published data only}
    1. Kraemer MU, Yang CH, Gutierrez B, Wu CH, Klein B, Pigott DM, et al. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 2020;368(6490):493-7. - PMC - PubMed
Krisztin 2020 {published data only}
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Lai CC 2020 {published data only}
    1. Lai CC, Hsu CY, Jen HH, Yen MF, Chan CC, Chen HH. Bayesian approach for modelling the dynamic of COVID-19 outbreak on the Diamond Princess Cruise Ship. medRxiv 2020.
Lai S 2020a {published data only}
    1. Lai S, Bogoch I, Ruktanonchai N, Watts A, Lu X, Yang W, et al. Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study. medRxiv 2020. [DOI: ]
Lai S 2020b {published data only}
    1. Lai S, Ruktanonchai NW, Carioli A, Ruktanonchai C, Floyd J, Prosper O, et al. Assessing the effect of global travel and contact reductions to mitigate the COVID-19 pandemic and resurgence. medRxiv 2020. [DOI: 10.1101/2020.06.17.20133843] - DOI - PMC - PubMed
Lai S 2020c {published data only}
    1. Lai S, Ruktanonchai NW, Zhou L, Prosper O, Luo W, Floyd JR, et al. Effect of non-pharmaceutical interventions to contain COVID-19 in China. Nature 2020;04:04. [DOI: ] - PMC - PubMed
Lam 2020 {published data only}
    1. Lam HY, Lam TS, Wong CH, Lam WH, Leung CM, Au KW, et al. The epidemiology of COVID-19 cases and the successful containment strategy in Hong Kong - January to May 2020. International Journal of Infectious Diseases 2020;21:21. [DOI: ] - PMC - PubMed
Lau 2004 {published data only}
    1. Lau JT, Yang X, Tsui HY, Pang E. SARS related preventive and risk behaviours practised by Hong Kong-mainland China cross border travellers during the outbreak of the SARS epidemic in Hong Kong. Journal of Epidemiology & Community Health 2004;58(12):988-96. - PMC - PubMed
Lee 2020 {published data only}
    1. Lee VJ, Chiew CJ, Khong WX. Interrupting transmission of COVID-19: lessons from containment efforts in Singapore. Journal of Travel Medicine 2020;27(3):18. - PMC - PubMed
Li H 2020 {published data only}
    1. Li H, Sun K, Persing DH, Tang YW, Shen D. Real-time screening of specimen pools for coronavirus disease 2019 (COVID-19) infection at Sanya Airport, Hainan Island, China. Clinical Infectious Diseases 2020 Sep 30 [Epub ahead of print]. - PMC - PubMed
Lin YC 2020 {published data only}
    1. Lin YC, Chen MY, Liu MC, Lin YJ, Lin Yu-H, Kuo JS, et al. Quarantine measures for coronavirus disease 2019 on a cruise ship, Taiwan, February 2020. International Journal of Infectious Diseases 2020;99:298-300. - PMC - PubMed
Lin YH 2020 {published data only}
    1. Lin YH, Huang JY, Yu KD, Lu CM, Lee WP, Huang JJ, et al. Border quarantine measures and achievement of COVID-19 control in Taiwan. Epidemiology Bulletin 2020;36(15):87-8.
Li R 2020 {published data only}
    1. Li R, Chen B, Zhang T, Ren Z, Song Y, Xiao Y, et al. Global COVID-19 pandemic demands joint interventions for the suppression of future waves. Proceedings of the National Academy of Sciences of the United States of America 2020;117(42):26151-7. - PMC - PubMed
Liu 2011 {published data only}
    1. Liu X, Chen X, Takeuchi Y. Dynamics of an SIQS epidemic model with transport-related infection and exit-entry screenings. Journal of Theoretical Biology 2011;285(1):25-35. - PubMed
Liu F 2020 {published data only}
    1. Liu F, Wang M, Zheng M. Effects of COVID-19 lockdown on global air quality and health. The Science of the Total Environment 2020;755(Pt 1):142533. - PMC - PubMed
Liu Q 2020 {published data only}
    1. Liu Q, Lu H, Chen R. Effect of a bundle of intervention strategies for the control of COVID-19 in Henan, a neighboring province of Wuhan, China. Wiener Klinische Wochenschrift 2020;132(13-14):396-399. [DOI: 10.1007/s00508-020-01688-9] - DOI - PMC - PubMed
Luna 2007 {published data only}
    1. Luna LK, Panning M, Grywna K, Pfefferle S, Drosten C. Spectrum of viruses and atypical bacteria in intercontinental air travelers with symptoms of acute respiratory infection. Journal of Infectious Diseases 2007;195(5):675-9. - PMC - PubMed
Ma 2017 {published data only}
    1. Ma X, Liu F, Liu L, Zhang L, Lu M, Abudukadeer A, et al. No MERS-CoV but positive influenza viruses in returning Hajj pilgrims, China, 2013-2015. BMC Infectious Diseases 2017;17:715. - PMC - PubMed
Maeno 2016 {published data only}
    1. Maeno Y. Detecting a trend change in cross-border epidemic transmission. Physica A 2016;457:73-81. - PMC - PubMed
Magalis 2020 {published data only}
    1. Magalis BR, Ramirez-Mata A, Zhukova A, Mavian C, Marini S, Lemoine F, et al. Differing impacts of global and regional responses on SARS-CoV-2 transmission cluster dynamics. bioRxiv 2020.
Malmberg 2020 {published data only}
    1. Malmberg H, Britton T. Inflow restrictions can prevent epidemics when contact tracing efforts are effective but have limited capacity. Journal of The Royal Society Interface 2020;17(170):20200351. - PMC - PubMed
Marcelino 2012 {published data only}
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Myers 2020 {published data only}
    1. Myers JF, Snyder RE, Porse CC, Tecle S, Lowenthal P, Danforth ME, et al. Identification and monitoring of international travelers during the initial phase of an outbreak of COVID-19 - California, February 3-March 17, 2020. MMWR - Morbidity & Mortality Weekly Report 2020;69(19):599-602. - PubMed
Ng 2020a {published data only}
    1. Ng TCV, Cheng HY, Chang HH, Liu CC, Yang CC, Jian SW, et al. Effects of case- and population-based COVID-19 interventions in Taiwan. medRxiv 2020.
Nikolaou 2020 {published data only}
    1. Nikolaou P, Dimitriou L. Identification of critical airports for controlling global infectious disease outbreaks: stress-tests focusing in Europe. Journal of Air Transport Management 2020;85:101819. - PMC - PubMed
Niwa 2020 {published data only}
    1. Niwa M, Hara Y, Sengoku S, Kodama K. Effectiveness of social measures against COVID-19 outbreaks in selected Japanese regions analyzed by system dynamic modeling. International Journal of Environmental Research and Public Health 2020;17(17):6238. - PMC - PubMed
Pan 2020 {published data only}
    1. Pan W, Tyrovolas S, Vazquez IG, Raj R, Fernandez D, Zaitchik B, et al. COVID-19: Effectiveness of non-pharmaceutical interventions in the United States before phased removal of social distancing protections varies by region. medRxiv 2020.
Pitman 2005 {published data only}
    1. Pitman RJ, Cooper BS, Trotter CL, Gay NJ, Edmunds WJ. Entry screening for severe acute respiratory syndrome (SARS) or influenza: policy evaluation. BMJ 2005;331(7527):1242-3. - PMC - PubMed
Pullano 2020 {published data only}
    1. Pullano G, Valdano E, Scarpa N, Rubrichi S, Colizza V. Population mobility reductions during COVID-19 epidemic in France under lockdown. medRxiv 2020. [DOI: 10.1101/2020.05.29.20097097] - DOI - PMC - PubMed
Quilty 2020b {published data only}
    1. Quilty BJ, Diamond C, Liu Y, Gibbs H, Russell TW, Jarvis CI, et al. The effect of inter-city travel restrictions on geographical spread of COVID-19: evidence from Wuhan, China. medRxiv 2020. [DOI: 10.1101/2020.04.16.20067504] - DOI
Rajabi 2020 {published data only}
    1. Rajabi A, Mantzaris AV, Mutlu EC, Garibay I. Investigating dynamics of COVID-19 spread and containment with agent-based modeling. medRxiv 2020.
Ruktanonchai 2020 {published data only}
    1. Ruktanonchai NW, Floyd JR, Lai S, Ruktanonchai CW, Sadilek A, Rente-Lourenco P, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe. Science 2020;369(6510):1465-70. - PMC - PubMed
Ryu 2019 {published data only}
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Shah 2020 {published data only}
    1. Shah NH, Sheoran N, Jayswal EN, Shukla D, Shukla N, Shukla J, et al. Modelling COVID-19 transmission in the United States through interstate and foreign travels and evaluating impact of governmental public health interventions. medRxiv 2020. [DOI: 10.1101/2020.05.23.20110999] - DOI - PMC - PubMed
Shumway 2020 {published data only}
    1. Shumway B, Ibrahim D, Moss W. Monitoring returning travelers during the early weeks of the COVID-19 pandemic: one US county's experience. American Journal of Public Health 2020;110(7):962-3. - PMC - PubMed
Sriwijitalai 2020b {published data only}
    1. Sriwijitalai W, Wiwanitkit V. Positive screening for Wuhan novel coronavirus infection at international airport: what's the final diagnosis for positive cases. International Journal of Preventive Medicine 2020;11:30. - PMC - PubMed
Summan 2020 {published data only}
    1. Summan A, Nandi A. Timing of non-pharmaceutical interventions to mitigate COVID-19 transmission and their effects on mobility: a cross-country analysis. medRxiv 2020. [DOI: 10.1101/2020.05.09.20096420] - DOI - PMC - PubMed
Sun 2013 {published data only}
    1. Sun G, Abe N, Sugiyama Y, Nguyen QV, Nozaki K, Nakayama Y, et al. Development of an infection screening system for entry inspection at airport quarantine stations using ear temperature, heart and respiration rates. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine & Biology Society 2013;2013:6716-9. - PubMed
Thomas 2014 {published data only}
    1. Thomas HL, Zhao H, Green HK, Boddington NL, Carvalho CF, Osman HK, et al. Enhanced MERS coronavirus surveillance of travelers from the Middle East to England. Emerging Infectious Diseases 2014;20(9):1562-4. - PMC - PubMed
Valba 2020 {published data only}
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References to other published versions of this review

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