Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review

Efficacité des mesures de restriction des déplacements dans le confinement rapide de la grippe humaine: une revue systématique.

La eficacia de las restricciones a los viajes en la contención rápida de la gripe humana: una revisión sistemática

فعالية القيود على السفر في الاحتواء السريع للأنفلونزا البشرية: استعراض منهجي

出行限制对快速控制人类流感的有效性:系统回顾

Эффективность ограничений на поездки в целях предотвращения быстрого распространения гриппа человека: систематический обзор

Ana LP Mateus Harmony E Otete Charles R Beck Gayle P Dolan Jonathan S Nguyen-Van-Tam About the authors

Abstract

Objective

To assess the effectiveness of internal and international travel restrictions in the rapid containment of influenza.

Methods

We conducted a systematic review according to the requirements of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Health-care databases and grey literature were searched and screened for records published before May 2014. Data extraction and assessments of risk of bias were undertaken by two researchers independently. Results were synthesized in a narrative form.

Findings

The overall risk of bias in the 23 included studies was low to moderate. Internal travel restrictions and international border restrictions delayed the spread of influenza epidemics by one week and two months, respectively. International travel restrictions delayed the spread and peak of epidemics by periods varying between a few days and four months. Travel restrictions reduced the incidence of new cases by less than 3%. Impact was reduced when restrictions were implemented more than six weeks after the notification of epidemics or when the level of transmissibility was high. Travel restrictions would have minimal impact in urban centres with dense populations and travel networks. We found no evidence that travel restrictions would contain influenza within a defined geographical area.

Conclusion

Extensive travel restrictions may delay the dissemination of influenza but cannot prevent it. The evidence does not support travel restrictions as an isolated intervention for the rapid containment of influenza. Travel restrictions would make an extremely limited contribution to any policy for rapid containment of influenza at source during the first emergence of a pandemic virus.

Résumé

Objectif

Évaluer l'efficacité des mesures de restriction des déplacements internes et internationaux dans le confinement rapide de la grippe.

Méthodes

Nous avons effectué une revue systématique selon les exigences de l'énoncé des items préférables pour rendre compte des revues systématiques ou des méta-analyses (PRISMA). Nous avons effectué des recherches dans les bases de données sur les soins de la santé et la littérature grise et nous avons passé au crible les documents publiés avant mai 2014. L'extraction des données et les évaluations du risque de partialité ont été effectuées par deux chercheurs de manière indépendante. Nous avons fait la synthèse des résultats sous forme narrative.

Résultats

Le risque global de partialité dans les 23 études incluses était faible à modéré. Les mesures de restrictions des déplacements internes et les mesures de restriction aux frontières internationales ont retardé la propagation des épidémies de grippe d'une semaine et de deux mois, respectivement. Les mesures de restriction des déplacements internationaux ont retardé la propagation et le pic de l'épidémie de périodes variant de quelques jours à quatre mois. Les mesures de restriction des déplacements ont réduit de moins de 3% l'incidence des nouveaux cas. L'impact était réduit lorsque des mesures de restriction ont été mises en œuvre plus de six semaines après la notification de l'épidémie ou lorsque le niveau de transmissibilité était élevé. L'impact des mesures de restriction des déplacements serait minime dans les centres urbains où il existe une population dense et des réseaux de transport. Nous n'avons trouvé aucune preuve que les restrictions de déplacement confineraient la grippe dans une zone géographique définie.

Conclusion

Les mesures étendues de restriction des déplacements peuvent retarder la propagation de la grippe, mais ne peuvent pas l'empêcher. Les données probantes n'étayent pas les restrictions de déplacement en tant qu'intervention isolée pour le confinement rapide de la grippe. Les restrictions de déplacement n'apporteraient qu'une contribution extrêmement limitée à toute politique de confinement rapide de la grippe à la source lors de la première apparition d'un virus pandémique.

Resumen

Objetivo

Evaluar la eficacia de las restricciones a los viajes internos e internacionales en la contención rápida de la gripe.

Métodos

Se realizó una revisión sistemática de acuerdo con la declaración de los requisitos de los elementos de información preferidos para revisiones sistemáticas y meta-análisis. Se examinaron y se realizaron búsquedas de los registros publicados antes de mayo de 2014 en las bases de datos de asistencia sanitaria y en la literatura gris. Dos investigadores llevaron a cabo la extracción de datos y las evaluaciones de riesgo de sesgo de forma independiente. Los resultados se resumieron de forma narrativa.

Resultados

El riesgo general de sesgo en los 23 estudios seleccionados fue de bajo a moderado. Las restricciones a los viajes internos y las restricciones fronterizas internacionales retrasaron la propagación de las epidemias de gripe, al menos una semana y dos meses, respectivamente. Las restricciones a los viajes internacionales retrasaron la difusión, así como el pico de la epidemia por periodos que oscilan entre unos pocos días y cuatro meses. Las restricciones de viajes redujeron la incidencia de casos nuevos a menos del 3%. El efecto se redujo cuando estas restricciones se aplicaron más de seis semanas después de la notificación de epidemias o cuando el nivel de transmisibilidad era alto. El efecto de las restricciones a los viajes sería mínimo en los centros urbanos con poblaciones de alta densidad y redes de viaje. No se encontraron pruebas de que las restricciones a los viajes podrían contener la gripe en un área geográfica definida.

Conclusión

Las restricciones amplias a los viajes pueden retrasar la difusión de la gripe, si bien no pueden prevenirla. Las pruebas no apoyan las restricciones a los viajes como una intervención aislada para la contención rápida de la gripe. Las restricciones a los viajes podrían contribuir de forma muy limitada a una política de contención rápida de la gripe en origen durante la primera aparición de un virus pandémico.

ملخص

الغرض

تقييم فعالية القيود على السفر الداخلي والدولي في الاحتواء السريع للأنفلونزا.

الطريقة

قمنا بإجراء استعراض منهجي وفقاً لمتطلبات البنود المتعلقة بتقديم التقارير المفضلة لبيان الاستعراضات المنهجية والتحليلات الوصفية. وتم البحث في قواعد بيانات الرعاية الصحية والمؤلفات غير الرسمية وفحصها لمعرفة السجلات التي تم نشرها قبل أيار/مايو 2014. وأجرى باحثان استخلاص البيانات وتقييمات خطورة التحيز بشكل مستقل. وتم تجميع النتائج بشكل سردي.

النتائج

تراوحت خطورة التحيز بشكل عام في الدراسات المدرجة البالغ عددها 23 دراسة من منخفضة إلى متوسطة. وأدت القيود المفروضة على السفر الداخلي والقيود المفروضة على الحدود الدولية إلى تأخير انتشار أوبئة الأنفلونزا بأسبوع واحد وشهرين، على التوالي. وأدت القيود المفروضة على السفر الدولي إلى تأخير انتشار الأوبئة وذروتها بفترات تتراوح بين بضعة أيام وأربعة أشهر. وأدت القيود على السفر إلى تقليل الإصابة بالحالات الجديدة بأقل من 3 %. وانخفض الأثر عند تنفيذ القيود بعد الإبلاغ عن الأوبئة بأكثر من ستة أسابيع وعند ارتفاع مستوى قابلية السريان. وكان أقل أثر للقيود على السفر في المراكز الحضرية ذات الكثافة السكانية وشبكات السفر. ولم نعثر على بيّنات تفيد بأن القيود المفروضة على السفر يمكنها احتواء الأنفلونزا داخل منطقة جغرافية معينة.

الاستنتاج

يحتمل أن تؤدي القيود الموسعة على السفر إلى تأخير انتشار الأنفلونزا غير أنه لا يمكنها توقيه. ولا تدعم البيّنات القيود على السفر كتدخل فردي بهدف الاحتواء السريع للأنفلونزا. ومن الممكن أن تسهم القيود المفروضة على السفر بشكل محدود للغاية في أي سياسة تهدف إلى الاحتواء السريع للأنفلونزا عند مصدرها خلال الظهور الأول لفيروس الجائحة.

摘要

目的

评估国内和国际出行限制对快速控制流感的有效性。

方法

我们根据系统回顾和荟萃分析首选报告项目的需求进行了一项系统回顾。搜索医疗数据库和灰色文献并筛选在2014年5月前发表的记录。由两位研究者独立执行数据提取和误差风险评估。以叙事形式综合结果。

结果

在纳入的23项研究中,整体误差风险为中低等级。国内出行限制和国境线限制分别将流感流行传播推迟一个星期和两个月。国际出行限制将流行病传播和高峰期延迟几天到四个月不等。出行限制减少的新病例发病率不到3%。流行病通知发布超过六周后或在传播等级较高时,实施限制措施的影响效果趋于减少。出行限制对具有密集人口和出行网络的城市中心影响最小。我们没有发现旅游限制将流感控制在某一特定地理区域的证据。

结论

广泛的出行限制可能会推迟流感的传播,但没有阻止作用。证据不支持出行限制是一个快速控制流感的独立干预。对于任何要在大流行性流感病毒刚刚出现时就从源头快速控制流感的政策来说,出行限制的作用非常有限。

Резюме

Цель

Оценить эффективность ограничений на внутренние и международные поездки в целях предотвращения быстрого распространения гриппа.

Методы

Был проведен систематический обзор в соответствии с рекомендациями о наиболее предпочтительных параметрах отчетности для систематических обзоров и мета-анализа. Поиск и отбор соответствующей информации был осуществлен в медицинских базах данных и неиндексированной литературе, опубликованной до мая 2014 г. Отбор данных и оценка риска систематической ошибки проводились двумя исследователями независимо друг от друга. Результаты были обобщены в форме отчета.

Результаты

Общий риск систематической ошибки в 23 включенных исследованиях был низким или умеренным. Ограничения на внутренние поездки и на пересечение международных границ задерживали распространение эпидемий гриппа на одну неделю и два месяца соответственно. Ограничения на международные поездки задерживали распространение и пик эпидемий на период от нескольких дней до четырех месяцев. Ограничения на поездки сокращали число новых случаев менее чем на 3%. Эффект снижался, если меры по ограничению поездок принимались по истечении шести месяцев после уведомления об эпидемиях или когда уровень переносимости заболевания был уже высоким. Ограничения на поездки оказывали минимальное влияние в городских центрах с высокой плотностью населения и разветленной сетью пассажирских перевозок. Доказательства того, что ограничения на поездки препятствуют распространению гриппа за пределы определенного географического региона не найдены.

Вывод

Масштабные меры по ограничению поездок могут замедлить распространение гриппа, но не могут предотвратить его. Факты, подтверждающие, что ограничения на поездки, как отдельная мера, предотвращают быстрое распространение гриппа, не найдены. Ограничения на поездки в чрезвычайно малой степени способствуют быстрой локализации гриппа в месте его возникновения при первом появлении пандемического вируса.

Introduction

Travel restrictions were included in the WHO interim protocol: rapid operations to contain the initial emergence of pandemic influenza that was published in 2007 by the World Health Organization (WHO).1WHO interim protocol: rapid operations to contain the initial emergence of pandemic influenza. Geneva: World Health Organization; 2007. However, as they would hamper global travel and trade, such restrictions are not recommended by WHO once the global spread of pandemic influenza is established.2Pandemic influenza preparedness and response – a WHO guidance document. Geneva: World Health Organization; 2009.,3International Health Regulations (2005). Geneva: World Health Organization; 2008. In 2009, some countries applied travel restrictions as one of several strategies to prevent the introduction of the influenza virus A(H1N1)pdm09 into their territories but the effectiveness of this approach has subsequently been questioned.4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
Research on influenza has focused on the evaluation of the effectiveness and impact of pharmaceutical interventions.5Nicoll A, Ammon A, Amato Gauci A, Ciancio B, Zucs P, Devaux I, et al. Experience and lessons from surveillance and studies of the 2009 pandemic in Europe. Public Health. 2010;124(1):14–23. doi: http://dx.doi.org/10.1016/j.puhe.2009.12.001 PMID: 20141821
https://doi.org/10.1016/j.puhe.2009.12.0...
As quantitative assessment of the effectiveness of travel restrictions in pandemic situations tends to be more challenging, there are scarce data on this topic. In any meta-analysis of surveillance data from multiple studies, it is difficult to quantify and compare the effectiveness of travel restrictions because such interventions are frequently implemented with other countermeasures and without following standardized protocols.6Pérez Velasco R, Praditsitthikorn N, Wichmann K, Mohara A, Kotirum S, Tantivess S, et al. Systematic review of economic evaluations of preparedness strategies and interventions against influenza pandemics. PLoS One. 2012;7(2):e30333. doi: http://dx.doi.org/10.1371/journal.pone.0030333 PMID: 22393352
https://doi.org/10.1371/journal.pone.003...
However, mathematical models can be used to predict the effectiveness of each type of intervention and inform policy-makers at national and international levels. In 2009, a systematic review of studies based on such models revealed limited evidence of the effectiveness of restrictions in air travel – within and between countries – in the containment of pandemic influenza.7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
There has been no more recent systematic assessment of the effectiveness of restrictions in land, sea or air travel as isolated interventions. We therefore decided to assess the effectiveness of travel restrictions in the rapid containment of influenza strains with pandemic potential, in a systematic review that incorporated data collected during the 2009 pandemic.

Methods

Before commencement, our protocol was registered with PROSPERO – the international prospective register of scientific reviews maintained by the United Kingdom of Great Britain and Northern Ireland’s National Institute for Health Research.8Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
http://www.crd.york.ac.uk/PROSPERO/displ...
We conducted a systematic review according to the requirements of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.9Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. doi: http://dx.doi.org/10.1371/journal.pmed.1000097 PMID: 19621072
https://doi.org/10.1371/journal.pmed.100...
We assessed the evidence for restrictions in internal travel – travel within the same country – or international travel – travel between two or more countries – affecting the spread of influenza. We considered the air, terrestrial or maritime transportation of humans to or within countries affected by seasonal or pandemic influenza. The outcome measures of interest were epidemiological characteristics and some viral transmission parameters of influenza such as the basic reproductive number (R0). Studies eligible for inclusion were reports, reviews, meta-analyses, mathematical modelling studies and observational and experimental studies published before May 2014. Studies that only evaluated the spread of influenza in animals or animal products were excluded.

Search strategy

We searched numerous health-care databases and sources of grey literature (Box 1). Critical keywords and thesaurus heading terms were initially tailored to MEDLINE searches and then adapted for other sources as necessary. The full search construct was included in the registered protocol.1010 Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review [Protocol]. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPEROFILES/3943_PROTOCOL_20130706.pdf [cited 2014 Sep 29].
http://www.crd.york.ac.uk/PROSPEROFILES/...
We contacted field experts and undertook reference and citation tracking to identify further relevant literature.

Box 1  Sources of literature included in this systematic reviewHealth-care databases
  • CINAHL (Cumulative Index to Nursing and Allied Health Literature)

  • Cochrane Library – Central Register of Controlled Trials

  • EMBASE

  • PubMed – including MEDLINE

  • World Health Organization Global Index Medicus

Evidence-based reviews
  • Bandolier

  • Cochrane Library – Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment Database, NHS Economic Evaluation Database

Guidelines
  • United Kingdom Department of Health

  • United Kingdom National Institute for Health Care and Excellence – Evidence Search

  • United States Centers for Disease Control and Prevention – Guidance

Grey literature
  • Consultation with domain experts – Martin Cetron (Centers for Disease Control and Prevention, Atlanta), John Edmunds (London School of Hygiene & Tropical Medicine, London), Peter Grove (Department of Health, London), Richard J Pitman (Oxford Outcomes, Oxford)

  • OpenSIGLE system for information on grey literature in Europe

  • United Kingdom National Institute for Health Care and Excellence – Evidence Search

  • Web of Science

Manual searching of relevant journals
  • Eurosurveillance

  • Emerging Infectious Diseases

Reference tracking
  • Reference lists of all studies selected for inclusion were searched to identify further relevant studies

Citation tracking
  • Web of Science – Science Citation Index

  • Google Scholar

Internet searching

Study selection

All records identified were imported into the EndNote X6 software package (Thomson Reuters, San Francisco, United States of America). Following the removal of duplicates, all remaining records were screened for inclusion against the protocol’s eligibility criteria by two researchers.8Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
http://www.crd.york.ac.uk/PROSPERO/displ...
We used a three-stage sifting approach to review titles, abstracts and full texts. Where disagreements arose, a third reviewer provided arbitration.8Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
http://www.crd.york.ac.uk/PROSPERO/displ...

Data extraction

All records that met the eligibility criteria were subject to data extraction. Two reviewers independently extracted study data using a piloted form; any disagreements were resolved with a third reviewer. The full list of data items extracted is available on PROSPERO.8Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
http://www.crd.york.ac.uk/PROSPERO/displ...

Assessing risk of bias

Risk of bias was assessed at both study and outcome level. We used an evaluation tool developed by the United States Agency for Healthcare Research and Quality1111 Systems to rate the strength of scientific evidence. Rockville: Agency for Healthcare Research and Quality; 2002. for assessing such risk in reviews. Since we are not aware of a previously validated instrument to assess risk of bias in mathematical modelling studies, we developed a tool based on the principles for the construction of mathematical models recommended by the London School of Hygiene & Tropical Medicine,1212 Introduction to infectious disease modelling and its applications. London: London School of Hygiene Tropical Medicine; 2011. in consultation with an experienced modeller8Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
http://www.crd.york.ac.uk/PROSPERO/displ...
(see Appendix A; available at: http://www.nottingham.ac.uk/research/groups/healthprotection/documents/supplementary-data-sr-travel-restrictions-influenza-mateus-et-al-220914.pdf).

Summary measures and data synthesis

Descriptive statistics were calculated using Excel 2010 (Microsoft, Richmond, USA). We used a recognized framework to synthesize the extracted data and assessments of risk of bias in a narrative style.1313 Systematic reviews - CRD’s guidance for undertaking reviews in health care. York: University of York Centre for Reviews and Dissemination; 2009.

Results

Study selection and characteristics

Before removal of duplicates, we identified 8836 potentially relevant records. However, only 23 studies – 19 mathematical modelling studies, one time-series analysis, two literature reviews and one systematic review – met our eligibility criteria (Fig. 1).4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
,7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
,1414 Lam EH, Cowling BJ, Cook AR, Wong JY, Lau MS, Nishiura H. The feasibility of age-specific travel restrictions during influenza pandemics. Theor Biol Med Model. 2011;8(1):44. doi: http://dx.doi.org/10.1186/1742-4682-8-44 PMID: 22078655
https://doi.org/10.1186/1742-4682-8-44...
3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...

Fig. 1

Flowchart for the selection of studies on the effectiveness of travel restriction in the containment of human influenza

Of the modelling studies included, 14 used stochastic models,4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
,1515 Colizza V, Barrat A, Barthelemy M, Valleron AJ, Vespignani A. Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions. PLoS Med. 2007;4(1):e13. doi: http://dx.doi.org/10.1371/journal.pmed.0040013 PMID: 17253899
https://doi.org/10.1371/journal.pmed.004...
,1616 Cooper BS, Pitman RJ, Edmunds WJ, Gay NJ. Delaying the international spread of pandemic influenza. PLoS Med. 2006;3(6):e212. doi: http://dx.doi.org/10.1371/journal.pmed.0030212 PMID: 16640458
https://doi.org/10.1371/journal.pmed.003...
,2222 Hsieh YH, van den Driessche P, Wang L. Impact of travel between patches for spatial spread of disease. Bull Math Biol. 2007;69(4):1355–75. doi: http://dx.doi.org/10.1007/s11538-006-9169-6 PMID: 17318677
https://doi.org/10.1007/s11538-006-9169-...
,2323 Lee JM, Choi D, Cho G, Kim Y. The effect of public health interventions on the spread of influenza among cities. J Theor Biol. 2012;293:131–42. doi: http://dx.doi.org/10.1016/j.jtbi.2011.10.008 PMID: 22033506
https://doi.org/10.1016/j.jtbi.2011.10.0...
,2525 Eichner M, Schwehm M, Wilson N, Baker MG. Small islands and pandemic influenza: potential benefits and limitations of travel volume reduction as a border control measure. BMC Infect Dis. 2009;9(1):160. doi: http://dx.doi.org/10.1186/1471-2334-9-160 PMID: 19788751
https://doi.org/10.1186/1471-2334-9-160...
2929 Wood JG, Zamani N, MacIntyre CR, Beckert NG. Effects of internal border control on spread of pandemic influenza. Emerg Infect Dis. 2007;13(7):1038–45. doi: http://dx.doi.org/10.3201/eid1307.060740 PMID: 18214176
https://doi.org/10.3201/eid1307.060740...
,3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
two used deterministic models,1818 Flahault A, Vergu E, Coudeville L, Grais RF. Strategies for containing a global influenza pandemic. Vaccine. 2006;24(44-46):6751–5. doi: http://dx.doi.org/10.1016/j.vaccine.2006.05.079 PMID: 16843574
https://doi.org/10.1016/j.vaccine.2006.0...
,1919 Kernéis S, Grais RF, Boëlle PY, Flahault A, Vergu E. Does the effectiveness of control measures depend on the influenza pandemic profile? PLoS One. 2008;3(1):e1478. doi: http://dx.doi.org/10.1371/journal.pone.0001478 PMID: 18213386
https://doi.org/10.1371/journal.pone.000...
two used a combination of both stochastic and deterministic methods1414 Lam EH, Cowling BJ, Cook AR, Wong JY, Lau MS, Nishiura H. The feasibility of age-specific travel restrictions during influenza pandemics. Theor Biol Med Model. 2011;8(1):44. doi: http://dx.doi.org/10.1186/1742-4682-8-44 PMID: 22078655
https://doi.org/10.1186/1742-4682-8-44...
,1717 Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS One. 2008;3(3):e1790. doi: http://dx.doi.org/10.1371/journal.pone.0001790 PMID: 18335060
https://doi.org/10.1371/journal.pone.000...
and one used a Poisson regression model.2424 Scalia Tomba G, Wallinga J. A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. Math Biosci. 2008;214(1-2):70–2. doi: http://dx.doi.org/10.1016/j.mbs.2008.02.009 PMID: 18387639
https://doi.org/10.1016/j.mbs.2008.02.00...
Six studies1515 Colizza V, Barrat A, Barthelemy M, Valleron AJ, Vespignani A. Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions. PLoS Med. 2007;4(1):e13. doi: http://dx.doi.org/10.1371/journal.pmed.0040013 PMID: 17253899
https://doi.org/10.1371/journal.pmed.004...
1919 Kernéis S, Grais RF, Boëlle PY, Flahault A, Vergu E. Does the effectiveness of control measures depend on the influenza pandemic profile? PLoS One. 2008;3(1):e1478. doi: http://dx.doi.org/10.1371/journal.pone.0001478 PMID: 18213386
https://doi.org/10.1371/journal.pone.000...
,3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
were based on meta-population models of influenza spread3535 Rvachev LA, Longini IM Jr. A mathematical model for the global spread of influenza. Math Biosci. 1985;75(1):3–22. doi: http://dx.doi.org/10.1016/0025-5564(85)90064-1
https://doi.org/10.1016/0025-5564(85)900...
and one4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
on an alternative model.3636 Balcan D, Colizza V, Gonçalves B, Hu H, Ramasco JJ, Vespignani A. Multiscale mobility networks and the spatial spreading of infectious diseases. Proc Natl Acad Sci U S A. 2009;106(51):21484–9. doi: http://dx.doi.org/10.1073/pnas.0906910106 PMID: 20018697
https://doi.org/10.1073/pnas.0906910106...
The focus of the included studies was the effectiveness of internal2222 Hsieh YH, van den Driessche P, Wang L. Impact of travel between patches for spatial spread of disease. Bull Math Biol. 2007;69(4):1355–75. doi: http://dx.doi.org/10.1007/s11538-006-9169-6 PMID: 17318677
https://doi.org/10.1007/s11538-006-9169-...
,2323 Lee JM, Choi D, Cho G, Kim Y. The effect of public health interventions on the spread of influenza among cities. J Theor Biol. 2012;293:131–42. doi: http://dx.doi.org/10.1016/j.jtbi.2011.10.008 PMID: 22033506
https://doi.org/10.1016/j.jtbi.2011.10.0...
,2626 Bolton KJ, McCaw JM, Moss R, Morris RS, Wang S, Burma A, et al. Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia. Bull World Health Organ. 2012;90(4):264–71. doi: http://dx.doi.org/10.2471/BLT.11.093419 PMID: 22511822
https://doi.org/10.2471/BLT.11.093419...
,2727 Germann TC, Kadau K, Longini IM Jr, Macken CA. Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci U S A. 2006;103(15):5935–40. doi: http://dx.doi.org/10.1073/pnas.0601266103 PMID: 16585506
https://doi.org/10.1073/pnas.0601266103...
,2929 Wood JG, Zamani N, MacIntyre CR, Beckert NG. Effects of internal border control on spread of pandemic influenza. Emerg Infect Dis. 2007;13(7):1038–45. doi: http://dx.doi.org/10.3201/eid1307.060740 PMID: 18214176
https://doi.org/10.3201/eid1307.060740...
or international4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
,1414 Lam EH, Cowling BJ, Cook AR, Wong JY, Lau MS, Nishiura H. The feasibility of age-specific travel restrictions during influenza pandemics. Theor Biol Med Model. 2011;8(1):44. doi: http://dx.doi.org/10.1186/1742-4682-8-44 PMID: 22078655
https://doi.org/10.1186/1742-4682-8-44...
1919 Kernéis S, Grais RF, Boëlle PY, Flahault A, Vergu E. Does the effectiveness of control measures depend on the influenza pandemic profile? PLoS One. 2008;3(1):e1478. doi: http://dx.doi.org/10.1371/journal.pone.0001478 PMID: 18213386
https://doi.org/10.1371/journal.pone.000...
,2424 Scalia Tomba G, Wallinga J. A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. Math Biosci. 2008;214(1-2):70–2. doi: http://dx.doi.org/10.1016/j.mbs.2008.02.009 PMID: 18387639
https://doi.org/10.1016/j.mbs.2008.02.00...
,2525 Eichner M, Schwehm M, Wilson N, Baker MG. Small islands and pandemic influenza: potential benefits and limitations of travel volume reduction as a border control measure. BMC Infect Dis. 2009;9(1):160. doi: http://dx.doi.org/10.1186/1471-2334-9-160 PMID: 19788751
https://doi.org/10.1186/1471-2334-9-160...
,3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
travel restrictions or combined internal and international travel restrictions.2828 Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
https://doi.org/10.1038/nature04795...
,3030 Brownstein JS, Wolfe CJ, Mandl KD. Empirical evidence for the effect of airline travel on inter-regional influenza spread in the United States. PLoS Med. 2006;3(10):e401. doi: http://dx.doi.org/10.1371/journal.pmed.0030401 PMID: 16968115
https://doi.org/10.1371/journal.pmed.003...
All but three of our included studies involved assessments of the impact of restrictions on air travel.2222 Hsieh YH, van den Driessche P, Wang L. Impact of travel between patches for spatial spread of disease. Bull Math Biol. 2007;69(4):1355–75. doi: http://dx.doi.org/10.1007/s11538-006-9169-6 PMID: 17318677
https://doi.org/10.1007/s11538-006-9169-...
,2525 Eichner M, Schwehm M, Wilson N, Baker MG. Small islands and pandemic influenza: potential benefits and limitations of travel volume reduction as a border control measure. BMC Infect Dis. 2009;9(1):160. doi: http://dx.doi.org/10.1186/1471-2334-9-160 PMID: 19788751
https://doi.org/10.1186/1471-2334-9-160...
,2626 Bolton KJ, McCaw JM, Moss R, Morris RS, Wang S, Burma A, et al. Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia. Bull World Health Organ. 2012;90(4):264–71. doi: http://dx.doi.org/10.2471/BLT.11.093419 PMID: 22511822
https://doi.org/10.2471/BLT.11.093419...
Only one assessed the impact of restrictions on aerial, maritime and terrestrial transportation.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
The characteristics of the included modelling studies and time-series analysis are presented in Appendix A.

The systematic review that we included synthesized evidence from modelling studies published between 1990 and September 2009.7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
The literature reviews that we included evaluated evidence from mathematical modelling studies on the containment of pandemic influenza and evidence used for preparedness planning in the United Kingdom.2020 Scientific summary of pandemic influenza and its mitigation. Scientific evidence-based review. London: Department of Health; 2011.,2121 Modelling summary. London: Department of Health; 2012.

Risk of bias within studies

Of the 20 studies based on mathematical modelling or time-series analysis, 17 were found to be at low risk of bias (Table 1). The other three were found to be at moderate risk of bias –because of limitations in the study design2222 Hsieh YH, van den Driessche P, Wang L. Impact of travel between patches for spatial spread of disease. Bull Math Biol. 2007;69(4):1355–75. doi: http://dx.doi.org/10.1007/s11538-006-9169-6 PMID: 17318677
https://doi.org/10.1007/s11538-006-9169-...
,2424 Scalia Tomba G, Wallinga J. A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. Math Biosci. 2008;214(1-2):70–2. doi: http://dx.doi.org/10.1016/j.mbs.2008.02.009 PMID: 18387639
https://doi.org/10.1016/j.mbs.2008.02.00...
or the low quality of travel data.2525 Eichner M, Schwehm M, Wilson N, Baker MG. Small islands and pandemic influenza: potential benefits and limitations of travel volume reduction as a border control measure. BMC Infect Dis. 2009;9(1):160. doi: http://dx.doi.org/10.1186/1471-2334-9-160 PMID: 19788751
https://doi.org/10.1186/1471-2334-9-160...
Methodological issues that may have led to bias included a lack of transmission variation during the progression of epidemics, seasonality, heterogeneous mixing and varying susceptibility of populations.1414 Lam EH, Cowling BJ, Cook AR, Wong JY, Lau MS, Nishiura H. The feasibility of age-specific travel restrictions during influenza pandemics. Theor Biol Med Model. 2011;8(1):44. doi: http://dx.doi.org/10.1186/1742-4682-8-44 PMID: 22078655
https://doi.org/10.1186/1742-4682-8-44...
,2626 Bolton KJ, McCaw JM, Moss R, Morris RS, Wang S, Burma A, et al. Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia. Bull World Health Organ. 2012;90(4):264–71. doi: http://dx.doi.org/10.2471/BLT.11.093419 PMID: 22511822
https://doi.org/10.2471/BLT.11.093419...
,2727 Germann TC, Kadau K, Longini IM Jr, Macken CA. Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci U S A. 2006;103(15):5935–40. doi: http://dx.doi.org/10.1073/pnas.0601266103 PMID: 16585506
https://doi.org/10.1073/pnas.0601266103...
,2929 Wood JG, Zamani N, MacIntyre CR, Beckert NG. Effects of internal border control on spread of pandemic influenza. Emerg Infect Dis. 2007;13(7):1038–45. doi: http://dx.doi.org/10.3201/eid1307.060740 PMID: 18214176
https://doi.org/10.3201/eid1307.060740...
,3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...

Table 1
Risk of bias assessments of mathematical modelling studies or time-series analysis on the effectiveness of travel restrictions to reduce influenza transmission

The systematic and literature reviews were at moderate risk of bias (Table 2). The systematic review7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
was based on literature from only one health-care database and on a snow-balling strategy that could have introduced selection bias. Neither of the literature reviews included any assessment of the design and quality of the studies that were included or detailed descriptions of the eligibility criteria applied.2020 Scientific summary of pandemic influenza and its mitigation. Scientific evidence-based review. London: Department of Health; 2011.,2121 Modelling summary. London: Department of Health; 2012.

Table 2
Risk of bias assessments of systematic or literature reviews on the effectiveness of travel restrictions to reduce influenza transmission

Synthesis of results

Internal travel restrictions

Travel restrictions appeared to have limited effectiveness in the containment of influenza at local level (Table 3 and Table 4; Table 3 is available at: http://www.who.int/bulletin/volumes/92/12/14-135590).

Table 3
Simulated effects of the implementation of internal travel restrictions on the spread and duration of pandemic or epidemic influenza
Table 4
Simulated impact of internal travel restrictions on influenza and influenza-like illness in influenza pandemics or epidemics

With pandemic influenza A(H1N1)pdm09 in Mongolia, the estimated delay of the pandemic peak varied between 1.0 and 1.5 weeks when 50% road and rail travel restrictions over 2–4 weeks were simulated.2626 Bolton KJ, McCaw JM, Moss R, Morris RS, Wang S, Burma A, et al. Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia. Bull World Health Organ. 2012;90(4):264–71. doi: http://dx.doi.org/10.2471/BLT.11.093419 PMID: 22511822
https://doi.org/10.2471/BLT.11.093419...
The corresponding impact on the attack rate was minimal – e.g. 95% travel restrictions led to a reduction of just 0.1%.2626 Bolton KJ, McCaw JM, Moss R, Morris RS, Wang S, Burma A, et al. Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia. Bull World Health Organ. 2012;90(4):264–71. doi: http://dx.doi.org/10.2471/BLT.11.093419 PMID: 22511822
https://doi.org/10.2471/BLT.11.093419...
A study set in the USA revealed similar findings – e.g. a delay in spread of 2–3 weeks if travel restrictions were 99% effective and implemented in conjunction with border restrictions that prevented the entry of infected travellers.2828 Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
https://doi.org/10.1038/nature04795...
Travel restrictions alone could delay spread by 1 week but only if implemented within 2 weeks of the first case.2828 Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
https://doi.org/10.1038/nature04795...
In one simulation, border controls preventing 99.9% of cases entering any given country delayed epidemic spread by up to 35 days.2424 Scalia Tomba G, Wallinga J. A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. Math Biosci. 2008;214(1-2):70–2. doi: http://dx.doi.org/10.1016/j.mbs.2008.02.009 PMID: 18387639
https://doi.org/10.1016/j.mbs.2008.02.00...
Another study in the USA presented analogous results – e.g. a 90% restriction on long-distance flights led to delays in the epidemic peak that ranged between a few days and a few weeks.2727 Germann TC, Kadau K, Longini IM Jr, Macken CA. Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci U S A. 2006;103(15):5935–40. doi: http://dx.doi.org/10.1073/pnas.0601266103 PMID: 16585506
https://doi.org/10.1073/pnas.0601266103...
Effectiveness of travel restrictions decreased as the transmissibility of the strain increased; travel restrictions reduced the incidence of new cases by less than 3%.2727 Germann TC, Kadau K, Longini IM Jr, Macken CA. Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci U S A. 2006;103(15):5935–40. doi: http://dx.doi.org/10.1073/pnas.0601266103 PMID: 16585506
https://doi.org/10.1073/pnas.0601266103...
According to a time-series analysis in the USA, a 50% restriction in air travel during the 2001–2002 influenza season would have delayed the peak mortality associated with novel strains of seasonal influenza by 16 days – i.e. compared with the timing of the peak in previous years.3030 Brownstein JS, Wolfe CJ, Mandl KD. Empirical evidence for the effect of airline travel on inter-regional influenza spread in the United States. PLoS Med. 2006;3(10):e401. doi: http://dx.doi.org/10.1371/journal.pmed.0030401 PMID: 16968115
https://doi.org/10.1371/journal.pmed.003...

Internal travel restrictions in England, Scotland and Wales in the United Kingdom were predicted to have minimal impact on the magnitude of the peak and in delaying the spread of the epidemic – possibly because there are some densely populated urban areas and relatively high levels of population movement.2828 Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
https://doi.org/10.1038/nature04795...
However, in a recent review, it was estimated that a combination of internal and international travel restrictions could help to stagger the impact of a pandemic within a country such as the United Kingdom, by desynchronizing localized outbreaks.2121 Modelling summary. London: Department of Health; 2012. In Australia, it was reported that the impact of 80–99% restriction of air travel between major city hubs was less when varying transmissibility rather than constant transmissibility was simulated. 2929 Wood JG, Zamani N, MacIntyre CR, Beckert NG. Effects of internal border control on spread of pandemic influenza. Emerg Infect Dis. 2007;13(7):1038–45. doi: http://dx.doi.org/10.3201/eid1307.060740 PMID: 18214176
https://doi.org/10.3201/eid1307.060740...
In the same investigation, effectiveness fell when strain transmissibility was increased.2929 Wood JG, Zamani N, MacIntyre CR, Beckert NG. Effects of internal border control on spread of pandemic influenza. Emerg Infect Dis. 2007;13(7):1038–45. doi: http://dx.doi.org/10.3201/eid1307.060740 PMID: 18214176
https://doi.org/10.3201/eid1307.060740...
In the Republic of Korea, restriction of travel between cities by more than 50% reduced the epidemic peak by less than 0.01% when constant transmissibility was modelled.2323 Lee JM, Choi D, Cho G, Kim Y. The effect of public health interventions on the spread of influenza among cities. J Theor Biol. 2012;293:131–42. doi: http://dx.doi.org/10.1016/j.jtbi.2011.10.008 PMID: 22033506
https://doi.org/10.1016/j.jtbi.2011.10.0...
When variations in transmissibility were simulated, such travel had to be restricted by more than 90% for the epidemic peak to be delayed significantly.2323 Lee JM, Choi D, Cho G, Kim Y. The effect of public health interventions on the spread of influenza among cities. J Theor Biol. 2012;293:131–42. doi: http://dx.doi.org/10.1016/j.jtbi.2011.10.008 PMID: 22033506
https://doi.org/10.1016/j.jtbi.2011.10.0...
Travel restrictions would reduce the spread to new cities but could also increase the risk of large localized outbreaks.2323 Lee JM, Choi D, Cho G, Kim Y. The effect of public health interventions on the spread of influenza among cities. J Theor Biol. 2012;293:131–42. doi: http://dx.doi.org/10.1016/j.jtbi.2011.10.008 PMID: 22033506
https://doi.org/10.1016/j.jtbi.2011.10.0...
In China, it was observed that overall R0 would increase if symptomatic travellers were banned from moving from areas with high prevalence of seasonal influenza to areas with low prevalence. When symptomatic travellers were banned from leaving low-prevalence areas, a decrease in overall R0 to less than one was predicted.2222 Hsieh YH, van den Driessche P, Wang L. Impact of travel between patches for spatial spread of disease. Bull Math Biol. 2007;69(4):1355–75. doi: http://dx.doi.org/10.1007/s11538-006-9169-6 PMID: 17318677
https://doi.org/10.1007/s11538-006-9169-...

International travel restrictions

International travel restrictions also appeared to have limited effectiveness (Table 5 and Table 6; Table 6 is available at: http://www.who.int/bulletin/volumes/92/12/14-135590). Low-level restrictions – i.e. restrictions of less than 70% – were the least effective in containing the spread of epidemics between countries. It was found that a 40% restriction of air travel would only delay the spread of influenza A(H1N1)pdm09 from Mexico to other countries by less than 3 days.4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
In a high transmissibility scenario, a 20% or even a 50% reduction in the volume of travellers would not have any significant impact on the global spread of influenza A(H5N1).1515 Colizza V, Barrat A, Barthelemy M, Valleron AJ, Vespignani A. Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions. PLoS Med. 2007;4(1):e13. doi: http://dx.doi.org/10.1371/journal.pmed.0040013 PMID: 17253899
https://doi.org/10.1371/journal.pmed.004...
In a meta-population model of pandemic influenza, based on the 1968–1969 influenza A(H3N2) pandemic virus it was predicted delays in the epidemic peak of 9 and 14 days with 50% and 90% restriction of air travel, respectively.1818 Flahault A, Vergu E, Coudeville L, Grais RF. Strategies for containing a global influenza pandemic. Vaccine. 2006;24(44-46):6751–5. doi: http://dx.doi.org/10.1016/j.vaccine.2006.05.079 PMID: 16843574
https://doi.org/10.1016/j.vaccine.2006.0...

Table 5
Simulated effects of the implementation of international travel restrictions on the spread and duration of pandemic or epidemic influenza
Table 6
Measurement of impact of international travel restrictions on attack rate, cumulative incidence, influenza-like illness peak (i.e. number of cases) and on the number of cases of influenza epidemics

In Italy, relatively large delays were reported in reaching an influenza A(H5N1) peak – i.e. 7–37 days, depending on the level of influenza transmissibility and the extent of the restrictions simulated.1717 Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS One. 2008;3(3):e1790. doi: http://dx.doi.org/10.1371/journal.pone.0001790 PMID: 18335060
https://doi.org/10.1371/journal.pone.000...
Travel restrictions had no beneficial effect on attack rate if the level of strain transmissibility was moderate or high.1717 Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS One. 2008;3(3):e1790. doi: http://dx.doi.org/10.1371/journal.pone.0001790 PMID: 18335060
https://doi.org/10.1371/journal.pone.000...
In a more recent review, it was estimated that introduction of pandemic influenza into the United Kingdom could be delayed by up to 2 months if there was an almost complete – e.g. 99.9% – ban on air travel.2020 Scientific summary of pandemic influenza and its mitigation. Scientific evidence-based review. London: Department of Health; 2011. However, the size of the effect was considerably reduced, to just 1–2 weeks, if the level of restriction was lowered to 90%.2020 Scientific summary of pandemic influenza and its mitigation. Scientific evidence-based review. London: Department of Health; 2011. Similar observations were made in an assessment of the impact of restrictions of air, land and sea travel on the introduction of H1N1 pdm09 into Hong Kong Special Administrative Region (SAR), China.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
In this study, it was estimated that restrictions of 90% and 99% on all modes of transportation would delay the epidemic peak by up to 6 and 12 weeks, respectively, when R0 was set to 1.4.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
When R0 was set to 1.7, a restriction of 99% on all modes of transportation would delay the epidemic peak by up to 8 weeks and halve the cumulative attack rate. Air travel restrictions appeared to be the most effective isolated intervention, even though most infected cases would probably enter Hong Kong SAR by land travel from mainland China.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
Although one review of the evidence from mathematical modelling concluded that air travel bans would probably have a similar effect irrespective of the pandemic’s country of origin,2121 Modelling summary. London: Department of Health; 2012. another report believed that the effectiveness of such restrictions would vary according to the geographical source of the pandemic.3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
If air travel bans delayed the epidemic so that it coincided with the usual influenza season, the apparent number of cases and the size of the peak in the epidemic could both increase.3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
However, the opposite trends might be observed if the travel restrictions coincided with a period of low strain transmissibility.3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
By restricting air travel by 95%, it should be possible to delay pandemic spread across the USA – of an infection originating in Sydney or Hong Kong SAR – by 2–3 weeks.3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
However, there was no corresponding impact if the geographical origin of the pandemic was London because of London’s high flight densities and interconnectivity.3131 Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
https://doi.org/10.1371/journal.pone.000...
The selective cancellation of a quarter of all connection flights between 500 major cities worldwide could be more effective than the closure of all of the cities’ airports – reducing the number of infected travellers by an additional 19%.3232 Marcelino J, Kaiser M. Critical paths in a metapopulation model of H1N1: efficiently delaying influenza spreading through flight cancellation. PLoS Curr. 2012;4:e4f8c9a2e1fca8. doi: http://dx.doi.org/10.1038/nm0506-497 PMID: 16675989
https://doi.org/10.1038/nm0506-497...
A review of air travel restrictions between Asia and the United Kingdom indicated that such restrictions would stop no more than 90% of infected travellers from the pandemic’s country of origin.2121 Modelling summary. London: Department of Health; 2012. If air travel from all affected countries was restricted by 90.0% and 99.9%, the pandemic wave would be delayed by 3–4 weeks and up to 4 months, respectively,2121 Modelling summary. London: Department of Health; 2012.,2828 Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
https://doi.org/10.1038/nature04795...
but such intensive restrictions would clearly have negative social and economic impacts. A systematic review found that extensive air travel restrictions – e.g. restrictions of more than 90% – could delay the spread of pandemics by up to 4 months if the strains involved had low to moderate transmissibility.7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
However, such restrictions appeared ineffective if the strains involved had high transmissibility – i.e. if R0 was 2.4.7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
In general, a combination of interventions appeared to be more effective than the implementation of travel restrictions in isolation.7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...

Discussion

The results of our systematic review indicate that overall travel restrictions have only limited effectiveness in the prevention of influenza spread, particularly in those high transmissibility scenarios in which R0 is at least 1.9 (Box 2). The effect size varied according to the extent and timeliness of the restrictions, the size of the epidemic, strain transmissibility, the heterogeneity of the travel patterns, the geographical source and the urban density of international travel hubs. Only extensive travel restrictions – i.e. over 90% – had any meaningful effect on reducing the magnitude of epidemics. In isolation, travel restrictions might delay the spread and peak of pandemics by a few weeks or months but we found no evidence that they would contain influenza within a defined geographical area.

Box 2  Summary of findings of the 23 studies assessedInternal travel restrictions: general observations
  • Have limited effectiveness

  • Delay pandemic spread by about 1 week

  • Delay pandemic peak by about 1.5 weeks

  • Have little impact on magnitude of pandemics – e.g. they may reduce attack rates by < 2%

  • Simulated impact is particularly weak in scenarios that involve strains with high transmissibility

Internal travel restrictions: risk of bias assessment
  • Relevant studies have low to moderate risk of bias

  • Paucity of data on terrestrial travel may have led to an overestimation of the impact of travel restrictions

  • Many simulations take no account of the characteristics of human populations – e.g. the mixing and variation of susceptibility across age groups – or of seasonality. Such limitations could well have affected the simulated spread of pandemic waves and impacts of interventions

International travel restrictions: general observations
  • Have limited effectiveness – e.g. 90% air travel restriction in all affected countries may delay spread of pandemics by 3–4 weeks

  • Have minimal impact on the magnitude of pandemics, typically reducing attack rates by less than 0.02%

  • May prolong the seasonal influenza season

  • May result in higher epidemic peak if resultant delay causes pandemic wave to coincide with seasonal influenza wave

  • Simulated impact particularly weak in scenarios that involve strains with high transmissibility

  • Extensive restriction of international air travel might delay introduction of a pandemic into a country by up to 2 months and delay pandemic spread by 3–4 months

  • Would not prevent introduction of a pandemic into any given country

  • May give time for other interventions – e.g. the production and distribution of effective vaccines and antiviral drugs

  • Social and economic impacts need to be evaluated

International travel restrictions: specific measures
  • May have benefits compared with more widespread restrictions – e.g. in one simulation, compared with the closure of all of the cities’ airports, the targeted reduction of a quarter of flight connections between 500 major cities gave a greater reduction in the number of infected travellers

  • Compared with banning air travel by adults, the banning of air travel by children may be more effective at delaying the spread of a pandemic but is socially impractical

International travel restrictions: risk of bias assessment
  • Relevant studies have low to moderate risk of bias

  • A paucity of data on travel by sea and land may have led to an overestimation of the impact of air travel restrictions on the containment of influenza pandemics

  • Much of the information available on air travel has a lack of detail on flight destinations and numbers of travellers and this may have led to inaccurate assumptions being made about the spread of influenza

  • Again, many simulations take no account of the characteristics of human populations – e.g. the mixing and variation of susceptibility across age groups – or of seasonality and such limitations could well have affected the simulated spread of pandemic waves and impacts of interventions

  • When simulating novel pandemic strains, validation of models was an issue; mathematical models need to be validated against surveillance data to improve their value as predictive tools for policy-makers

Several limitations associated with our review warrant discussion. We included mathematical modelling studies that simulated very diverse scenarios with varying levels of R0, geographical locations, means of transportation, strains and population characteristics. A paucity of surveillance data concerning the impact and effectiveness of nonpharmaceutical interventions meant that our observations had to be mainly based on simulations.6Pérez Velasco R, Praditsitthikorn N, Wichmann K, Mohara A, Kotirum S, Tantivess S, et al. Systematic review of economic evaluations of preparedness strategies and interventions against influenza pandemics. PLoS One. 2012;7(2):e30333. doi: http://dx.doi.org/10.1371/journal.pone.0030333 PMID: 22393352
https://doi.org/10.1371/journal.pone.003...
While mathematical models are important tools that can be used to inform policy-makers, they cannot account fully for all aspects of real-life situations.

The lack of available data from observational or experimental studies precluded the conduct of the meta-analysis and sensitivity analysis that formed part of the protocol that we registered.8Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
http://www.crd.york.ac.uk/PROSPERO/displ...
Most of the studies that we included in our review used probabilistic models that appeared to have adequate levels of complexity to simulate disease spread and the impact of interventions. In comparison, deterministic models are less complex and do not take uncertainty into account but are still useful when limited data are available and a rapid simulation is needed.7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
Most of the studies we reviewed were limited by a lack of consideration of heterogeneous mixing, socioeconomic status and the relationship between age and immunity.3737 McMenamin J, Van-Tam J. Epidemiology of pandemic influenza A(H1N1)pdm09. In: Van-Tam J, Sellwood C, editors. Pandemic Influenza. 2nd ed. Wallingford: CABI; 2013. pp. 49–59. Many also simulated constant strain transmissibility during epidemics – even though transmissibility can vary over time because of seasonal climactic conditions, changes in host susceptibility and the effects of interventions such as social distancing, quarantine and the use of antiviral drugs.3838 Mikolajczyk R, Krumkamp R, Bornemann R, Ahmad A, Schwehm M, Duerr HP. Influenza – insights from mathematical modelling. Dtsch Arztebl Int. 2009;106(47):777–82. PMID: 20019862 The authors of some of the articles noted concerns that may have affected model accuracy, such as issues with the quality of air travel data – e.g. a lack of flight itineraries2828 Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
https://doi.org/10.1038/nature04795...
– and the need to use crude estimates of the volume of travellers within and between countries. There was a general paucity of data on land and sea travel,2525 Eichner M, Schwehm M, Wilson N, Baker MG. Small islands and pandemic influenza: potential benefits and limitations of travel volume reduction as a border control measure. BMC Infect Dis. 2009;9(1):160. doi: http://dx.doi.org/10.1186/1471-2334-9-160 PMID: 19788751
https://doi.org/10.1186/1471-2334-9-160...
although one of the studies provided comprehensive data on such travel.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
The tool we developed to assess the risk of bias in the mathematical modelling studies has not been validated and could have produced imprecise estimates.

The results of several studies indicate that, in reducing the global spread of influenza and the overall number of infected individuals, a combination of several different interventions is more effective than any single isolated measure.1616 Cooper BS, Pitman RJ, Edmunds WJ, Gay NJ. Delaying the international spread of pandemic influenza. PLoS Med. 2006;3(6):e212. doi: http://dx.doi.org/10.1371/journal.pmed.0030212 PMID: 16640458
https://doi.org/10.1371/journal.pmed.003...
,1717 Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS One. 2008;3(3):e1790. doi: http://dx.doi.org/10.1371/journal.pone.0001790 PMID: 18335060
https://doi.org/10.1371/journal.pone.000...
,3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
One study estimated that, when the strains involved have moderate transmissibility, a combination of antiviral prophylaxis, extensive travel restrictions and infant vaccination could reduce the cumulative attack rate by 77–87%.1717 Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS One. 2008;3(3):e1790. doi: http://dx.doi.org/10.1371/journal.pone.0001790 PMID: 18335060
https://doi.org/10.1371/journal.pone.000...
However, effective vaccines are not generally available at the point of emergence of a novel pandemic virus. The effectiveness of combined or single interventions can be affected by the timeliness of the implementation4Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
https://doi.org/10.1371/journal.pone.001...
,3939 Longini IM Jr, Nizam A, Xu S, Ungchusak K, Hanshaoworakul W, Cummings DA, et al. Containing pandemic influenza at the source. Science. 2005;309(5737):1083–7. doi: http://dx.doi.org/10.1126/science.1115717 PMID: 16079251
https://doi.org/10.1126/science.1115717...
and this appears to be particularly relevant with strains of higher transmissibility.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...

Often, in the context of pandemic preparedness and response, travel restrictions – especially at points of entry – have intuitive appeal to policy-makers because they demonstrate that a tangible attempt is being made to prevent the ingress of a novel virus or prevent onward spread. However, such an attempt is not always effective. WHO interim protocol: rapid operations to contain the initial emergence of pandemic influenza is implicitly focused on the creation of geographical cordons within a country and places more emphasis on the restriction of travel by land than on restrictions of air or sea travel.1WHO interim protocol: rapid operations to contain the initial emergence of pandemic influenza. Geneva: World Health Organization; 2007. However, the relevant data that are available seem to indicate that restrictions on land travel would have a limited impact on containment or even on the slowing of transmission.3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...

It seems likely that, for delaying the spread and reducing the magnitude of an epidemic in a given geographical area,7Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
https://doi.org/10.1186/1741-7015-7-76...
a combination of interventions would be more effective than isolated interventions.1616 Cooper BS, Pitman RJ, Edmunds WJ, Gay NJ. Delaying the international spread of pandemic influenza. PLoS Med. 2006;3(6):e212. doi: http://dx.doi.org/10.1371/journal.pmed.0030212 PMID: 16640458
https://doi.org/10.1371/journal.pmed.003...
,3434 Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
https://doi.org/10.1186/1471-2334-12-309...
Travel restrictions per se would not be sufficient to achieve containment in a given geographical area, and their contribution to any policy of rapid containment is likely to be limited.

Competing interests

  • The University of Nottingham Health Protection and Influenza Research Group is currently in receipt of research funds from GlaxoSmithKline (GSK) and unrestricted educational grants for influenza research from F Hoffmann-La Roche and Astra Zeneca. However, this funding did not support any aspect of the present study. Prior to October 2010, JSNV-T received funding to attend influenza-related meetings and give lectures, and also consultancy fees and research funding from several manufacturers of antiviral drugs and influenza vaccines. JSNV-T was an employee of SmithKline Beecham, Roche Products and Aventis-Pasteur MSD prior to 2005 but now has no outstanding pecuniary interests by way of shareholdings, share options or accrued pension rights.

References

  • 1
    WHO interim protocol: rapid operations to contain the initial emergence of pandemic influenza. Geneva: World Health Organization; 2007.
  • 2
    Pandemic influenza preparedness and response – a WHO guidance document. Geneva: World Health Organization; 2009.
  • 3
    International Health Regulations (2005). Geneva: World Health Organization; 2008.
  • 4
    Bajardi P, Poletto C, Ramasco JJ, Tizzoni M, Colizza V, Vespignani A. Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic. PLoS One. 2011;6(1):e16591. doi: http://dx.doi.org/10.1371/journal.pone.0016591 PMID: 21304943
    » https://doi.org/10.1371/journal.pone.0016591
  • 5
    Nicoll A, Ammon A, Amato Gauci A, Ciancio B, Zucs P, Devaux I, et al. Experience and lessons from surveillance and studies of the 2009 pandemic in Europe. Public Health. 2010;124(1):14–23. doi: http://dx.doi.org/10.1016/j.puhe.2009.12.001 PMID: 20141821
    » https://doi.org/10.1016/j.puhe.2009.12.001
  • 6
    Pérez Velasco R, Praditsitthikorn N, Wichmann K, Mohara A, Kotirum S, Tantivess S, et al. Systematic review of economic evaluations of preparedness strategies and interventions against influenza pandemics. PLoS One. 2012;7(2):e30333. doi: http://dx.doi.org/10.1371/journal.pone.0030333 PMID: 22393352
    » https://doi.org/10.1371/journal.pone.0030333
  • 7
    Lee VJ, Lye DC, Wilder-Smith A. Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies. BMC Med. 2009;7(1):76. doi: http://dx.doi.org/10.1186/1741-7015-7-76 PMID: 20003249
    » https://doi.org/10.1186/1741-7015-7-76
  • 8
    Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw [cited 2014 Sep 11].
    » http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD4201303943#.VBG2AxYjxSw
  • 9
    Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. doi: http://dx.doi.org/10.1371/journal.pmed.1000097 PMID: 19621072
    » https://doi.org/10.1371/journal.pmed.1000097
  • 10
    Mateus ALP, Beck CR, Otete HE, Dolan G, Nguyen-Van-Tam JS. Effectiveness of travel restrictions in the rapid containment of human influenza: a systematic review [Protocol]. York: University of York Centre for Reviews and Dissemination; 2013. Available from: http://www.crd.york.ac.uk/PROSPEROFILES/3943_PROTOCOL_20130706.pdf [cited 2014 Sep 29].
    » http://www.crd.york.ac.uk/PROSPEROFILES/3943_PROTOCOL_20130706.pdf
  • 11
    Systems to rate the strength of scientific evidence. Rockville: Agency for Healthcare Research and Quality; 2002.
  • 12
    Introduction to infectious disease modelling and its applications. London: London School of Hygiene Tropical Medicine; 2011.
  • 13
    Systematic reviews - CRD’s guidance for undertaking reviews in health care. York: University of York Centre for Reviews and Dissemination; 2009.
  • 14
    Lam EH, Cowling BJ, Cook AR, Wong JY, Lau MS, Nishiura H. The feasibility of age-specific travel restrictions during influenza pandemics. Theor Biol Med Model. 2011;8(1):44. doi: http://dx.doi.org/10.1186/1742-4682-8-44 PMID: 22078655
    » https://doi.org/10.1186/1742-4682-8-44
  • 15
    Colizza V, Barrat A, Barthelemy M, Valleron AJ, Vespignani A. Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions. PLoS Med. 2007;4(1):e13. doi: http://dx.doi.org/10.1371/journal.pmed.0040013 PMID: 17253899
    » https://doi.org/10.1371/journal.pmed.0040013
  • 16
    Cooper BS, Pitman RJ, Edmunds WJ, Gay NJ. Delaying the international spread of pandemic influenza. PLoS Med. 2006;3(6):e212. doi: http://dx.doi.org/10.1371/journal.pmed.0030212 PMID: 16640458
    » https://doi.org/10.1371/journal.pmed.0030212
  • 17
    Ciofi degli Atti ML, Merler S, Rizzo C, Ajelli M, Massari M, Manfredi P, et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS One. 2008;3(3):e1790. doi: http://dx.doi.org/10.1371/journal.pone.0001790 PMID: 18335060
    » https://doi.org/10.1371/journal.pone.0001790
  • 18
    Flahault A, Vergu E, Coudeville L, Grais RF. Strategies for containing a global influenza pandemic. Vaccine. 2006;24(44-46):6751–5. doi: http://dx.doi.org/10.1016/j.vaccine.2006.05.079 PMID: 16843574
    » https://doi.org/10.1016/j.vaccine.2006.05.079
  • 19
    Kernéis S, Grais RF, Boëlle PY, Flahault A, Vergu E. Does the effectiveness of control measures depend on the influenza pandemic profile? PLoS One. 2008;3(1):e1478. doi: http://dx.doi.org/10.1371/journal.pone.0001478 PMID: 18213386
    » https://doi.org/10.1371/journal.pone.0001478
  • 20
    Scientific summary of pandemic influenza and its mitigation. Scientific evidence-based review. London: Department of Health; 2011.
  • 21
    Modelling summary. London: Department of Health; 2012.
  • 22
    Hsieh YH, van den Driessche P, Wang L. Impact of travel between patches for spatial spread of disease. Bull Math Biol. 2007;69(4):1355–75. doi: http://dx.doi.org/10.1007/s11538-006-9169-6 PMID: 17318677
    » https://doi.org/10.1007/s11538-006-9169-6
  • 23
    Lee JM, Choi D, Cho G, Kim Y. The effect of public health interventions on the spread of influenza among cities. J Theor Biol. 2012;293:131–42. doi: http://dx.doi.org/10.1016/j.jtbi.2011.10.008 PMID: 22033506
    » https://doi.org/10.1016/j.jtbi.2011.10.008
  • 24
    Scalia Tomba G, Wallinga J. A simple explanation for the low impact of border control as a countermeasure to the spread of an infectious disease. Math Biosci. 2008;214(1-2):70–2. doi: http://dx.doi.org/10.1016/j.mbs.2008.02.009 PMID: 18387639
    » https://doi.org/10.1016/j.mbs.2008.02.009
  • 25
    Eichner M, Schwehm M, Wilson N, Baker MG. Small islands and pandemic influenza: potential benefits and limitations of travel volume reduction as a border control measure. BMC Infect Dis. 2009;9(1):160. doi: http://dx.doi.org/10.1186/1471-2334-9-160 PMID: 19788751
    » https://doi.org/10.1186/1471-2334-9-160
  • 26
    Bolton KJ, McCaw JM, Moss R, Morris RS, Wang S, Burma A, et al. Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia. Bull World Health Organ. 2012;90(4):264–71. doi: http://dx.doi.org/10.2471/BLT.11.093419 PMID: 22511822
    » https://doi.org/10.2471/BLT.11.093419
  • 27
    Germann TC, Kadau K, Longini IM Jr, Macken CA. Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci U S A. 2006;103(15):5935–40. doi: http://dx.doi.org/10.1073/pnas.0601266103 PMID: 16585506
    » https://doi.org/10.1073/pnas.0601266103
  • 28
    Ferguson NM, Cummings DAT, Fraser C, Cajka JC, Cooley PC, Burke DS. Strategies for mitigating an influenza pandemic. Nature. 2006;442(7101):448–52. doi: http://dx.doi.org/10.1038/nature04795 PMID: 16642006
    » https://doi.org/10.1038/nature04795
  • 29
    Wood JG, Zamani N, MacIntyre CR, Beckert NG. Effects of internal border control on spread of pandemic influenza. Emerg Infect Dis. 2007;13(7):1038–45. doi: http://dx.doi.org/10.3201/eid1307.060740 PMID: 18214176
    » https://doi.org/10.3201/eid1307.060740
  • 30
    Brownstein JS, Wolfe CJ, Mandl KD. Empirical evidence for the effect of airline travel on inter-regional influenza spread in the United States. PLoS Med. 2006;3(10):e401. doi: http://dx.doi.org/10.1371/journal.pmed.0030401 PMID: 16968115
    » https://doi.org/10.1371/journal.pmed.0030401
  • 31
    Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. Controlling pandemic flu: the value of international air travel restrictions. PLoS One. 2007;2(5):e401. doi: http://dx.doi.org/10.1371/journal.pone.0000401 PMID: 17476323
    » https://doi.org/10.1371/journal.pone.0000401
  • 32
    Marcelino J, Kaiser M. Critical paths in a metapopulation model of H1N1: efficiently delaying influenza spreading through flight cancellation. PLoS Curr. 2012;4:e4f8c9a2e1fca8. doi: http://dx.doi.org/10.1038/nm0506-497 PMID: 16675989
    » https://doi.org/10.1038/nm0506-497
  • 33
    Hollingsworth TD, Ferguson NM, Anderson RM. Will travel restrictions control the international spread of pandemic influenza? Nat Med. 2006;12(5):497–9. doi: http://dx.doi.org/10.1038/nm0506-497 PMID: 16675989
    » https://doi.org/10.1038/nm0506-497
  • 34
    Chong KC, Ying Zee BC. Modeling the impact of air, sea, and land travel restrictions supplemented by other interventions on the emergence of a new influenza pandemic virus. BMC Infect Dis. 2012;12(1):309. doi: http://dx.doi.org/10.1186/1471-2334-12-309 PMID: 23157818
    » https://doi.org/10.1186/1471-2334-12-309
  • 35
    Rvachev LA, Longini IM Jr. A mathematical model for the global spread of influenza. Math Biosci. 1985;75(1):3–22. doi: http://dx.doi.org/10.1016/0025-5564(85)90064-1
    » https://doi.org/10.1016/0025-5564(85)90064-1
  • 36
    Balcan D, Colizza V, Gonçalves B, Hu H, Ramasco JJ, Vespignani A. Multiscale mobility networks and the spatial spreading of infectious diseases. Proc Natl Acad Sci U S A. 2009;106(51):21484–9. doi: http://dx.doi.org/10.1073/pnas.0906910106 PMID: 20018697
    » https://doi.org/10.1073/pnas.0906910106
  • 37
    McMenamin J, Van-Tam J. Epidemiology of pandemic influenza A(H1N1)pdm09. In: Van-Tam J, Sellwood C, editors. Pandemic Influenza. 2nd ed. Wallingford: CABI; 2013. pp. 49–59.
  • 38
    Mikolajczyk R, Krumkamp R, Bornemann R, Ahmad A, Schwehm M, Duerr HP. Influenza – insights from mathematical modelling. Dtsch Arztebl Int. 2009;106(47):777–82. PMID: 20019862
  • 39
    Longini IM Jr, Nizam A, Xu S, Ungchusak K, Hanshaoworakul W, Cummings DA, et al. Containing pandemic influenza at the source. Science. 2005;309(5737):1083–7. doi: http://dx.doi.org/10.1126/science.1115717 PMID: 16079251
    » https://doi.org/10.1126/science.1115717

Publication Dates

  • Publication in this collection
    29 Sept 2014

History

  • Received
    11 Jan 2014
  • Reviewed
    02 Sept 2014
  • Accepted
    03 Sept 2014
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