Non-pharmaceutical interventions to combat COVID-19 in the Americas described through daily sub-national data

Author:

Touchton MichaelORCID,Knaul Felicia Marie,Arreola-Ornelas Héctor,Porteny Thalia,Carniado Óscar Méndez,Faganello Marco,Hummel Calla,Otero Silvia,Insua Jorge,Patino Fausto,Undurraga EduardoORCID,Pérez-Cruz Pedro,Sanchez-Talanquer MarianoORCID,Velasco Guachalla V. Ximena,Nelson-Nuñez Jami,Boulding Carew,Calderon-Anyosa Renzo,Garcia Patricia J,Vargas Enciso ValentinaORCID

Abstract

AbstractThis dataset covers national and subnational non-pharmaceutical interventions (NPI) to combat the COVID-19 pandemic in the Americas. Prior to the development of a vaccine, NPI were governments’ primary tools to mitigate the spread of COVID-19. Variation in subnational responses to COVID-19 is high and is salient for health outcomes. This dataset captures governments’ dynamic, varied NPI to combat COVID-19 for 80% of Latin America’s population from each country’s first case through December 2021. These daily data encompass all national and subnational units in Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, and Peru. The dataset includes individual and aggregate indices of nine NPI: school closures, work suspensions, public event cancellations, public transport suspensions, information campaigns, local travel restrictions, international travel controls, stay-at-home orders, and restrictions on the size of gatherings. We also collected data on mask mandates as a separate indicator. Local country-teams drew from multiple data sources, resulting in high-quality, reliable data. The dataset thus allows for consistent, meaningful comparisons of NPI within and across countries during the pandemic.

Funder

University of Miami Institute for Advanced Study of the Americas

Inter-American Development Bank

Institute for Advanced Study of the Americas at the University of Miami

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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