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Author Notes:

Correspondence: Mary A. Shiraef, mshiraef@nd.edu

Author contributions: M.A.S. conceived the codebook for the COBAP database, managed data collection and verification processes, and wrote the manuscript; P.F. implemented the matching technique, wrote the code for the analysis, and wrote the methods section of the manuscript;

L.F. ran exploratory data analysis, generated the figures, improved code legibility, and managed data on European Union countries. M.A.W. ran exploratory data analysis, improved code legibility, and managed data on information-scarce countries.

E.B. managed data for island countries. M.A.S., Erin S. and E.B. assisted with RA recruitment, and C.H., Erin S. and E.B. assisted with RA training. D.T., Erin S., Elizabeth S. L.F. H.A.J., E.T. and C.H. contributed language expertise to the data collection and verification processes.

M.A.S., L.F., M.A.W., E.B., C.H., Erin S., J.F., D.T., Elizabeth S., N.M., H.A.J., E. T. contributed at least 20 h to the data collection process and conducted the internal review process. All authors reviewed the final manuscript.

Acknowledgements: The COBAP Team thanks Wayde ZC Marsh for the idea to use matching for this study, Stanford University’s Immigration Policy Lab (IPL) for their roles in the early stages of this study, and Matthew Amme as well as Yashwini Selvaraj for logistical support.

We thank Jeff Harden and Alejandro Campos for sharing a draft of their paper which uses matching on a different topic, which aided our work process greatly. COBAP is grateful to the volunteer RAs who piloted the original data collection process in 2020.

We are grateful also to experts who donated their time to review portions of the 2020 data: Drs. Mary Mitsdarffer, Maggie Shum, Susanna E. Brantley, Luis L. Schenoni, Johanna Sweere, and Colin Lewis-Beck. The database would not be possible without the data collectors who continued to update and verify the database, the listed consortia coauthors of this publication.

We credit the internship program at the University of Notre Dame’s Department of Political Science, led by Dr. Carolina Arroyo, for its efforts in recruitment according to language expertise gaps on our team.

We especially thank Hawraa Al Janabi for her use of both Arabic and Turkish in reading and interpreting policies for the database, Cora Hirst for her use of French, Erin Tutaj for her use of Spanish, and Erin Straight for her use of both Spanish and Portuguese.

We thank several workshops in which we had the chance to discuss the model, including the Kellogg Institute for International Studies’ Comparative Politics Workshop, the University of Waterloo’s Department of Political Science, and the COVID-19 Public Health and Social Measures (PHSMs) Research Outcome Conference, convened by the Coronanet Project.

Disclosures: The authors declare no competing interests.

Subjects:

Research Funding:

Open Access funding enabled and organized by Projekt DEAL.

Keywords:

  • Disease prevention
  • Immunology
  • SARS-CoV-2
  • Health economics

Did border closures slow SARS-CoV-2?

Tools:

Journal Title:

Scientific Reports

Volume:

Volume 12

Publisher:

Type of Work:

Article | Final Publisher PDF

Abstract:

Despite the economic, social, and humanitarian costs of border closures, more than 1000 new international border closures were introduced in response to the 2020–2021 pandemic by nearly every country in the world. The objective of this study was to examine whether these border closures reduced the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Prior to 2020, the impacts of border closures on disease spread were largely unknown, and their use as a pandemic policy was advised against by international organizations. We tested whether they were helpful in reducing spread by using matching techniques on our hand-coded COVID Border Accountability Project (COBAP) Team database of international closures, converted to a time-series cross-sectional data format. We controlled for national-level internal movement restrictions (domestic lockdowns) using the Oxford COVID-19 Government Response Tracker (OxCGRT) time-series data. We found no evidence in favor of international border closures, whereas we found a strong association between national-level lockdowns and a reduced spread of SARS-CoV-2 cases. More research must be done to evaluate the byproduct effects of closures versus lockdowns as well as the efficacy of other preventative measures introduced at international borders.

Copyright information:

© The Author(s) 2022.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/rdf).
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