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Nikolas Lazar, Email: nikolas_lazar@brown.edu

M.A.S. wrote and developed the decision-set structure of the survey and codebook and wrote the manuscript. All authors contributed to the data collection and review process. C.H. and J.S. contributed to the biomedical design of the data collection process. M.A.S., L.S., C.L.B and M.A.W. contributed to the social sciences design of the data collection process. M.A.S. and M.A. developed the data verification process. M.A. wrote the code for our project website, interactive map visualizations and data automation process. M.A.S., L.S., J.S., C.H., B.W., T.N., C.L.B, and M.A. wrote the first draft of the manuscript. T.N. and M.A. implemented the data visualizations of the manuscript. C.H. wrote and compiled the supplementary materials. S.E.B. generated the figures of the manuscript. All research assistant (RA) members of the COBAP Team contributed at least 20 volunteer hours of data collection and/or data verification to the project. All RA coauthors of the project contributed at least 40 hours of data collection to the project. M.A.S. recruited and managed the volunteers. N.L., M.A.W. C.H. and E.S. trained new volunteers. All faculty coauthors conducted reviews of the data. M.A.S., S.E.B., N.L., M.A.W., Y.S., C.L.B., L.S. and C.H. finalized the manuscript. All authors reviewed and approved the final manuscript.

The idea for the COBAP Team was born in March 2020 in the Immigration Policy Lab (IPL) at Stanford University. The Principal Investigator (PI) of COBAP, Mary A. Shiraef, was a visiting student researcher (VSR) in Stanford’s Department of Political Science when the virus first appeared in the United States (U.S.). With Jennifer Fei and Jessica Sadye Wolff, Shiraef set out to map the initial immigration-related response of each country and clean the country-level restrictions data from the ACAPS Government Measures Dataset (ACAPS) into travel history-based versus citizenship status-based bans per country (https://immigrationlab.org/2020/06/26/will-covid-19-harden-worlds-borders/). The COBAP Team is grateful for these early stage consultations with Stanford, and especially to Prof. Jeremy Weinstein, Prof. David Laitin, Prof. James Fearon, Jennifer Fei, and Jessica Sadye Wolff. We also thank the University of Notre Dame, and especially Shana Scogin, Matthew Dahl and Assoc. Prof. Victoria Hui for their early support for the project. COBAP is grateful to the volunteer RAs who piloted the original data collection process: Elizabeth Beling, Aadya Bhaskaran, Cora Hirst, Cayleigh Jackson, Camilla Kline, Nikolas Lazar, Rachel E. Musetti, Hannah Risman, Hannah Rossi, Aman Bedi, Yashwini Selvaraj, Suzanne Martin, Ellen Shiraef, Mary A. Shiraef, Michael Shiraef, Noah Rusk Taylor, Bryn Walker, Ian Wang, and Mark A. Weiss. The database would not be possible without the data collectors who continued to update and then verify the database for the complete timeline of 2020, the listed consortia coauthors of this publication. We thank our language consultants, Dr. Gemma Dipoppa, Dr. Nihan Tuncer, Soyoung Lee, Tirapat Pattanavhaew, and Dallas Hayden for their availability to confirm the content of a policy text. We are grateful for review of the EU context by Dr. Foteini Kalantzi at Oxford University; and for all the experts and public officials around the world who took some time to review our data and suggest missing sources. For perspective on the epidemiological implications of the dataset, we thank Dr. Nathan Lo from the University of California, San Francisco (UCSF). We thank the Kellogg Institute at the University of Notre Dame and especially to Paul Friesen, Ilana Rothkopf, Jacob Turner, and Bryce Kleinsteuber for their comments on the project’s developments in the Comparative Politics Workshop. We acknowledge the Nanovic Institute at the University of Notre Dame for generously allowing the PI to adapt her COVID-postponed data collection project to an online data collection effort. Finally, we thank especially the many members of the public who have virtually supported our data collection effort: Laxman Iyer, Mary Trachian-Bradley, Renu Kuppuswami, Charlie Spradley, Carolyn Zhou, Natasha Patel, Paul Muren, Joseph Shiraef, Catherine Williams, Sarah Barbour, Kelsey Bohlke, and Laura Sanman, among others.We thank especially the many members of the public who have virtually supported our data collection effort: Laxman Iyer, Renu Kuppuswami, Charlie Spradley, Carolyn Zhou, Natasha Patel, Paul Muren, Joseph Shiraef, Catherine Williams, Sarah Barbour, Kelsey Bohlke, and Laura Sanman, among others.

The authors declare no competing interests.

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Keywords:

  • Politics
  • Viral infection

COVID Border Accountability Project, a hand-coded global database of border closures introduced during 2020

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Journal Title:

Scientific Data

Volume:

Volume 8

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Type of Work:

Article | Final Publisher PDF

Abstract:

Quantifying the timing and content of policy changes affecting international travel and immigration is key to ongoing research on the spread of SARS-CoV-2 and the socioeconomic impacts of border closures. The COVID Border Accountability Project (COBAP) provides a hand-coded dataset of >1000 policies systematized to reflect a complete timeline of country-level restrictions on movement across international borders during 2020. Trained research assistants used pre-set definitions to source, categorize and verify for each new border policy: start and end dates, whether the closure is “complete” or “partial”, which exceptions are made, which countries are banned, and which air/land/sea borders were closed. COBAP verified the database through internal and external audits from public health experts. For purposes of further verification and future data mining efforts of pandemic research, the full text of each policy was archived. The structure of the COBAP dataset is designed for use by social and biomedical scientists. For broad accessibility to policymakers and the public, our website depicts the data in an interactive, user-friendly, time-based map.

Copyright information:

© The Author(s) 2021

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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