<!DOCTYPE article
PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.3 20210610//EN" "JATS-archivearticle1-3-mathml3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" xml:lang="en" article-type="brief-report"><?properties open_access?><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-ta">Emerg Infect Dis</journal-id><journal-id journal-id-type="iso-abbrev">Emerg Infect Dis</journal-id><journal-id journal-id-type="publisher-id">EID</journal-id><journal-title-group><journal-title>Emerging Infectious Diseases</journal-title></journal-title-group><issn pub-type="ppub">1080-6040</issn><issn pub-type="epub">1080-6059</issn><publisher><publisher-name>Centers for Disease Control and Prevention</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">34647863</article-id><article-id pub-id-type="pmc">8714230</article-id><article-id pub-id-type="publisher-id">21-1944</article-id><article-id pub-id-type="doi">10.3201/eid2801.211944</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Letter</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Letter</subject></subj-group><subj-group subj-group-type="TOC-title"><subject>Effectiveness of International Travel Controls for Delaying Local Outbreaks of COVID-19</subject></subj-group></article-categories><title-group><article-title>Effectiveness of International Travel Controls for Delaying Local Outbreaks of COVID-19 </article-title><alt-title alt-title-type="running-head">Effectiveness of International Travel Controls for Delaying Local Outbreaks of COVID-19</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Yang</surname><given-names>Bingyi</given-names></name></contrib><contrib contrib-type="author"><name><surname>Sullivan</surname><given-names>Sheena G.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Du</surname><given-names>Zhanwei</given-names></name></contrib><contrib contrib-type="author"><name><surname>Tsang</surname><given-names>Tim K.</given-names></name></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Cowling</surname><given-names>Benjamin J.</given-names></name></contrib><aff id="aff1">The University of Hong Kong, Hong Kong, China (B. Yang, Zhanwei Du, T.K. Tsang, B.J. Cowling); </aff><aff id="aff2">University of Melbourne Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia (S.G. Sullivan); </aff><aff id="aff3">Laboratory of Data Discovery for Health Limited, Hong Kong (Z. Du, B.J. Cowling)</aff></contrib-group><author-notes><corresp id="cor1">Address for correspondence: Benjamin J. Cowling, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 7 Sassoon Rd, Pokfulam, Hong Kong, China; email: <email xlink:href="bcowling@hku.hk">bcowling@hku.hk</email></corresp></author-notes><pub-date pub-type="ppub"><month>1</month><year>2022</year></pub-date><volume>28</volume><issue>1</issue><fpage>251</fpage><lpage>253</lpage><permissions><copyright-year>2022</copyright-year><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/" specific-use="textmining" content-type="ccbylicense">https://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>Emerging Infectious Diseases is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.</license-p></license></permissions><abstract><p>During the coronavirus disease pandemic, international travel controls have been widely adopted. To determine the effectiveness of these measures, we analyzed data from 165 countries and found that early implementation of international travel controls led to a mean delay of 5 weeks in the first epidemic peak of cases.</p></abstract><kwd-group kwd-group-type="author"><title>Keywords: </title><kwd>coronavirus disease</kwd><kwd>2019 novel coronavirus disease</kwd><kwd>COVID-19</kwd><kwd>severe acute respiratory syndrome coronavirus 2</kwd><kwd>SARS-CoV-2</kwd><kwd>viruses</kwd><kwd>respiratory infections</kwd><kwd>zoonoses</kwd><kwd>border control</kwd><kwd>epidemiology</kwd></kwd-group></article-meta></front><body><p>International travel control (e.g., screening of inbound travelers, requiring quarantines, and even closing borders) has been a key strategy implemented by many countries to limit importations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, early in the coronavirus disease (COVID-19) pandemic, the World Health Organization (WHO) did not recommend restricting travel (<xref rid="R1" ref-type="bibr"><italic>1</italic></xref>), and travel controls have not been widely used in previous pandemics (e.g., the 2009&#x02013;10 influenza pandemic) (<xref rid="R2" ref-type="bibr"><italic>2</italic></xref>,<xref rid="R3" ref-type="bibr"><italic>3</italic></xref>). Limiting international movement has enormous social and economic costs, and the benefits of this strategy (i.e., delaying or averting an epidemic) lack real-world evidence. Previous studies, most of which were simulation studies, suggest that travel restrictions can delay but not prevent local epidemics (<xref rid="R2" ref-type="bibr"><italic>2</italic></xref>&#x02013;<xref rid="R4" ref-type="bibr"><italic>4</italic></xref>).</p><p>To examine the association between implementation of international travel controls and local outbreak progress of COVID-19, we used publicly available data (<xref rid="R5" ref-type="bibr"><italic>5</italic></xref>&#x02013;<xref rid="R7" ref-type="bibr"><italic>7</italic></xref>; T. Wu et al., unpub. data, <ext-link xlink:href="https://www.medrxiv.org/content/10.1101/2020.02.25.20027433v1" ext-link-type="uri">https://www.medrxiv.org/content/10.1101/2020.02.25.20027433v1</ext-link>) for January 1&#x02013;July 31, 2020. Only 14 (8.5%) of the 165 countries studied enacted international travel controls coincident with the lockdown in Wuhan, China (January 23); all controls involved screening inbound travelers (<xref rid="F1" ref-type="fig">Figure</xref>). Enactment of international travel controls peaked &#x02248;3 weeks after WHO declared the pandemic (March 11, 2020), by which time 112 (67.8%) countries completely closed their borders, 44 (26.6%) banned travelers from high-risk regions, and 4 (2.4%) required quarantine for travelers from high-risk regions (<xref rid="F1" ref-type="fig">Figure</xref>; <xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Figure 1). Of the 165 countries, 90 (54.5%) had imposed at least some restriction before reporting their first COVID-19 case, and 20 (12%) had imposed their strictest restrictions before reporting their first case (<xref rid="F1" ref-type="fig">Figure</xref>; <xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Figures 1&#x02013;3). </p><fig position="float" id="F1" fig-type="figure"><label>Figure</label><caption><p>Association between international travel controls and local coronavirus disease (COVID-19) outbreaks in 165 countries, January 1&#x02013;July 31, 2020. A) Temporal distribution of the international travel controls enacted by the studied countries. Data from (<xref rid="R7" ref-type="bibr"><italic>7</italic></xref>). B) Distribution of the time between a country&#x02019;s first COVID-19 case and its enactment of any or of the strongest international travel controls. C, D) Probability of reaching first local peak of COVID-19 cases by the time of implementing any (C) or the strongest (D) international travel controls, estimated by using the Kaplan-Meier survival function. Vertical dashed lines in panels B, C, and D indicate the date that Wuhan, China, underwent lockdown; vertical dotted lines indicate the date that the pandemic was declared.</p></caption><graphic xlink:href="21-1944-F" position="float"/></fig><p>We determined the progress of outbreaks in each country to be the time from January 1, 2020, to the first epidemic peak, which was identified from the modal daily case counts within any 53-day sliding window (i.e., a quarter of the length of the study period) and needed to comprise <underline>&#x0003e;</underline>10% of the cumulative incidence during the study period (<xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Figure 2). By July 31, 2020, the first epidemic peak had been reached in 122 (74%) of the studied countries (<xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Figure 4). In countries that had enacted any international travel controls before their first COVID-19 case, the first peak was reached an average of 36 days (95% CI 10&#x02013;61 days) later than it was in countries that did not enact controls until after their first case was reported (p&#x0003c;0.01 by log-rank test; Figure). Countries that implemented their strictest international travel controls before detecting any COVID-19 cases reported their first case a median of 57 days (95% CI 14&#x02013;70 days) later than countries that imposed their strongest controls after the first case was reported (p = 0.04 by log-rank test; <xref rid="F1" ref-type="fig">Figure</xref>).</p><p>After adjusting for population density and implementing nonpharmaceutical interventions by using the accelerated failure time model (<xref rid="SD1" ref-type="supplementary-material">Appendix</xref>), we estimated that the average time to detection of the first case occurred 1.22 (95% CI 1.06&#x02013;1.41) times later in countries that implemented any restrictions than in countries that implemented no travel restrictions. This time ratio was extended to 1.31 (95% CI 1.02&#x02013;1.68) if countries implemented their strongest travel restrictions (<xref rid="T1" ref-type="table">Table</xref>). Such associations still held when adjusting for time-varying nonpharmaceutical interventions by using the Cox model.</p><table-wrap position="float" id="T1"><label>Table</label><caption><title>Estimated time ratios and hazard ratios for comparing selected outcomes in countries that did and did not implement international controls before identifying their first cases of COVID-19, January&#x02013;July 2020*</title></caption><table frame="hsides" rules="groups"><col width="108" span="1"/><col width="99" span="1"/><col width="85" span="1"/><col width="9" span="1"/><col width="97" span="1"/><col width="83" span="1"/><thead><tr><th rowspan="2" valign="bottom" align="left" scope="col" colspan="1">Endpoint</th><th valign="bottom" colspan="2" align="center" scope="colgroup" rowspan="1">Adjusted time ratio (95% CI)&#x02020; <hr/></th><th rowspan="2" valign="bottom" align="left" scope="col" colspan="1"/><th valign="bottom" colspan="2" align="center" scope="colgroup" rowspan="1">Adjusted hazard ratio (95% CI)&#x02021;<hr/></th></tr><tr><th valign="bottom" colspan="1" align="center" scope="colgroup" rowspan="1">Any international controls</th><th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">The strongest international controls</th><th valign="bottom" colspan="1" align="center" scope="colgroup" rowspan="1">Any international controls</th><th valign="bottom" align="center" scope="col" rowspan="1" colspan="1">The strongest international controls</th></tr></thead><tbody><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Case peak</td><td valign="top" align="center" rowspan="1" colspan="1">1.22 (1.06&#x02013;1.41)</td><td valign="top" align="center" rowspan="1" colspan="1">1.31 (1.02&#x02013;1.68)</td><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="center" rowspan="1" colspan="1">0.66 (0.46&#x02013;0.93)</td><td valign="top" align="center" rowspan="1" colspan="1">0.65 (0.39&#x02013;1.08)</td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Death peak<hr/></td><td valign="top" align="center" rowspan="1" colspan="1">1.23 (1.01&#x02013;1.51)<hr/></td><td valign="top" align="center" rowspan="1" colspan="1">0.98 (0.71&#x02013;1.37)<hr/></td><td valign="top" align="left" rowspan="1" colspan="1">
<hr/>
</td><td valign="top" align="center" rowspan="1" colspan="1">0.74 (0.53&#x02013;1.04)<hr/></td><td valign="top" align="center" rowspan="1" colspan="1">0.90 (0.53&#x02013;1.55)<hr/></td></tr><tr><td colspan="2" valign="top" align="left" scope="col" rowspan="1">Cumulative incidence, no. cases/10,000 population</td><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="left" rowspan="1" colspan="1"/></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 0.2 </td><td valign="top" align="center" rowspan="1" colspan="1">1.20 (1.10&#x02013;1.31)</td><td valign="top" align="center" rowspan="1" colspan="1">1.23 (1.05&#x02013;1.44)</td><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="center" rowspan="1" colspan="1">0.55 (0.38&#x02013;0.78)</td><td valign="top" align="center" rowspan="1" colspan="1">0.61 (0.35&#x02013;1.04)</td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 1.0 </td><td valign="top" align="center" rowspan="1" colspan="1">1.26 (1.13&#x02013;1.42)</td><td valign="top" align="center" rowspan="1" colspan="1">1.27 (1.04&#x02013;1.55)</td><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="center" rowspan="1" colspan="1">0.49 (0.35&#x02013;0.71)</td><td valign="top" align="center" rowspan="1" colspan="1">0.90 (0.53&#x02013;1.51)</td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 5.0 </td><td valign="top" align="center" rowspan="1" colspan="1">1.25 (1.05&#x02013;1.49)</td><td valign="top" align="center" rowspan="1" colspan="1">1.34 (0.99&#x02013;1.82)</td><td valign="top" align="left" rowspan="1" colspan="1"/><td valign="top" align="center" rowspan="1" colspan="1">0.59 (0.41&#x02013;0.85)</td><td valign="top" align="center" rowspan="1" colspan="1">0.90 (0.54&#x02013;1.51)</td></tr></tbody></table><table-wrap-foot><p>*AFT, accelerated failure time; COVID-19, coronavirus disease.
&#x02020;Estimates were obtained from accelerated failure time models with log-logistic distribution, adjusted for population density and the strictest level of each nonpharmaceutical intervention used during the study period for each country. The 2 columns show time ratio of implementing international controls before the country&#x02019;s first COVID-19 case to that after the country&#x02019;s first case.
&#x02021;Estimates were obtained from Cox proportional hazard models, which adjusted for population density and time-varying nonpharmaceutical interventions during the study period for each country. The 2 columns show hazard ratio of implementing international controls before the country&#x02019;s first COVID-19 case to that after the country&#x02019;s first case.</p></table-wrap-foot></table-wrap><p>To confirm that these observations were maintained according to alternative measures of epidemic activity, we used the following as outcomes in the models: the time by which COVID-19 deaths first peaked, and attainment of a cumulative incidence of 0.2, 1.0, or 5.0 cases/10,000 persons (by which time peaks had been reached in &#x02248;10%, 30%, and 60% of the countries; <xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Figure 5). These outcomes may better indicate community spread in countries in which most cases were imported and identified during quarantine (e.g., Fiji), information that was not available from public data. Moreover, outcomes may be better when the epidemic was multimodal (e.g., Guyana) or the country did not experience its main epidemic until later in the study period (e.g., Argentina) (<xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Figure 2). Both accelerated failure time and Cox models supported earlier observations that enactment of any international travel controls delayed the time in which cumulative incidence rates or deaths peaked. However, enactment of the strongest control was not associated with a reduced time to peak death or cumulative incidence of 5 cases/100,000 persons (<xref rid="T1" ref-type="table">Table</xref>).</p><p>Our work may be influenced by other unmeasured confounders, such as the stringency of international travel controls. We repeated our analyses by removing countries in Asia, in which implementation tended to be more strict, and found that our earlier observations largely held (<xref rid="SD1" ref-type="supplementary-material">Appendix</xref> Table). In addition, we examined the broader association between international travel controls and local epidemic progression, but we did not examine the roles of specific measures (e.g., quarantine and risk-dependent triage management).</p><p>Our findings suggest that implementing international travel controls earlier delayed the initial epidemic peak by &#x02248;5 weeks. Although travel restrictions did not prevent the virus from entering most countries, delaying its introduction bought valuable time for local health systems and governments to prepare to respond to local transmission.</p><supplementary-material id="SD1" position="float" content-type="local-data"><caption><title>Appendix</title><p>Supplemental methods and results from study of effectiveness of international travel controls for delaying local outbreaks of coronavirus disease.</p></caption><media xlink:href="21-1944-Techapp-s1.pdf" id="d64e299" position="anchor"/></supplementary-material></body><back><ack><title>Acknowledgments</title><p>We thank the Department of Health of the Food and Health Bureau of the Government of Hong Kong for conducting the outbreak investigation and providing data for analysis. </p><p>This project was supported by the Health and Medical Research Fund, Food and Health Bureau and Government of the Hong Kong Special Administrative Region (grant no. COVID190118). The WHO Collaborating Centre for Reference and Research on Influenza is supported by the Australian Government Department of Health.</p><p>B.J.C. consults for Roche, GSK, Moderna, AstraZeneca, and Sanofi Pasteur and is supported by the AIR@innoHK program of the Innovation and Technology Commission of the Hong Kong Special Administrative Region Government. S.G.S. reports performing unpaid consulting for Sanofi Pasteur and Sequiris. The authors report no other potential conflicts of interest.</p><p>All authors are affiliated with WHO collaborating centers. The objective technical analysis and results reported here were not part of official WHO work, and opinions contained herein do not necessarily represent the views of WHO.</p></ack><fn-group><fn fn-type="other"><p><italic>Suggested citation for this article</italic>: Yang B, Sullivan SG, Du Z, Tsang TK, Cowling BJ. Effectiveness of international travel controls for delaying local outbreaks of COVID-19. Emerg Infect Dis. 2022 Jan [<italic>date cited</italic>]. <ext-link xlink:href="https://doi.org/10.3201/eid2801.211944" ext-link-type="uri">https://doi.org/10.3201/eid2801.211944</ext-link></p></fn></fn-group><bio id="d64e316"><p>Dr. Yang is a postdoctoral fellow at the School of Public Health, University of Hong Kong. Her research interests are quantifying transmission dynamics and control of infectious diseases.</p></bio><ref-list><title>References</title><ref id="R1"><label>1. </label><mixed-citation publication-type="webpage"><collab>World Health Organization</collab>. Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (<year>2019</year>-nCoV) [<comment>cited 2021 Aug 2</comment>]. <ext-link xlink:href="https://www.who.int/news/item/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov)" ext-link-type="uri">https://www.who.int/news/item/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov)</ext-link></mixed-citation></ref><ref id="R2"><label>2. </label><mixed-citation publication-type="journal"><string-name><surname>Cowling</surname>
<given-names>BJ</given-names></string-name>, <string-name><surname>Lau</surname>
<given-names>LLH</given-names></string-name>, <string-name><surname>Wu</surname>
<given-names>P</given-names></string-name>, <string-name><surname>Wong</surname>
<given-names>HWC</given-names></string-name>, <string-name><surname>Fang</surname>
<given-names>VJ</given-names></string-name>, <string-name><surname>Riley</surname>
<given-names>S</given-names></string-name>, <etal>et al.</etal>
<article-title>Entry screening to delay local transmission of 2009 pandemic influenza A (H1N1).</article-title>
<source>BMC Infect Dis</source>. <year>2010</year>;<volume>10</volume>:<fpage>82</fpage>. <pub-id pub-id-type="doi">10.1186/1471-2334-10-82</pub-id><pub-id pub-id-type="pmid">20353566</pub-id></mixed-citation></ref><ref id="R3"><label>3. </label><mixed-citation publication-type="journal"><string-name><surname>Ryu</surname>
<given-names>S</given-names></string-name>, <string-name><surname>Gao</surname>
<given-names>H</given-names></string-name>, <string-name><surname>Wong</surname>
<given-names>JY</given-names></string-name>, <string-name><surname>Shiu</surname>
<given-names>EYC</given-names></string-name>, <string-name><surname>Xiao</surname>
<given-names>J</given-names></string-name>, <string-name><surname>Fong</surname>
<given-names>MW</given-names></string-name>, <etal>et al.</etal>
<article-title>Nonpharmaceutical measures for pandemic influenza in nonhealthcare settings&#x02013;international travel-related measures.</article-title>
<source>Emerg Infect Dis</source>. <year>2020</year>;<volume>26</volume>:<fpage>961</fpage>&#x02013;<lpage>6</lpage>. <pub-id pub-id-type="doi">10.3201/eid2605.190993</pub-id><pub-id pub-id-type="pmid">32027587</pub-id></mixed-citation></ref><ref id="R4"><label>4. </label><mixed-citation publication-type="journal"><string-name><surname>Burns</surname>
<given-names>J</given-names></string-name>, <string-name><surname>Movsisyan</surname>
<given-names>A</given-names></string-name>, <string-name><surname>Stratil</surname>
<given-names>JM</given-names></string-name>, <string-name><surname>Coenen</surname>
<given-names>M</given-names></string-name>, <string-name><surname>Emmert-Fees</surname>
<given-names>KM</given-names></string-name>, <string-name><surname>Geffert</surname>
<given-names>K</given-names></string-name>, <etal>et al.</etal>
<article-title>Travel-related control measures to contain the COVID-19 pandemic: a rapid review.</article-title>
<source>Cochrane Database Syst Rev</source>. <year>2020</year>;<volume>10</volume>:<elocation-id>CD013717</elocation-id>.<ext-link xlink:href="http://" ext-link-type="uri">
</ext-link><pub-id pub-id-type="pmid">33502002</pub-id></mixed-citation></ref><ref id="R5"><label>5. </label><mixed-citation publication-type="journal"><string-name><surname>Dong</surname>
<given-names>E</given-names></string-name>, <string-name><surname>Du</surname>
<given-names>H</given-names></string-name>, <string-name><surname>Gardner</surname>
<given-names>L</given-names></string-name>. <article-title>An interactive web-based dashboard to track COVID-19 in real time.</article-title>
<source>Lancet Infect Dis</source>. <year>2020</year>;<volume>20</volume>:<fpage>533</fpage>&#x02013;<lpage>4</lpage>. <pub-id pub-id-type="doi">10.1016/S1473-3099(20)30120-1</pub-id><pub-id pub-id-type="pmid">32087114</pub-id></mixed-citation></ref><ref id="R6"><label>6. </label><mixed-citation publication-type="webpage"><string-name><surname>Hale</surname>
<given-names>T</given-names></string-name>, <string-name><surname>Angrist</surname>
<given-names>N</given-names></string-name>, <string-name><surname>Goldszmidt</surname>
<given-names>R</given-names></string-name>, <string-name><surname>Kira</surname>
<given-names>B</given-names></string-name>, <string-name><surname>Petherick</surname>
<given-names>A</given-names></string-name>, <string-name><surname>Phillips</surname>
<given-names>T</given-names></string-name>, <etal>et al.</etal> A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker) [<comment>cited 2021 Aug 2</comment>]. <ext-link xlink:href="https://www.nature.com/articles/s41562-021-01079-8" ext-link-type="uri">https://www.nature.com/articles/s41562-021-01079-8</ext-link></mixed-citation></ref><ref id="R7"><label>7. </label><mixed-citation publication-type="webpage"><collab>Our World in Data</collab>. Policy responses to the coronavirus pandemic [<comment>cited 2021 Aug 2</comment>]. <ext-link xlink:href="https://ourworldindata.org/policy-responses-covid" ext-link-type="uri">https://ourworldindata.org/policy-responses-covid</ext-link></mixed-citation></ref></ref-list></back></article>