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

Michael M. Touchton, Felicia Marie Knaul, Thalia Porteny, Héctor Arreola-Ornelas, Silvia Otero-Bahamon, Jorge Insua

Research output: Contribution to journalResearch Articlepeer-review


This 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.
Translated title of the contributionIntervenciones no farmacéuticas para combatir el COVID-19 en las Américas descritas a través de datos subnacionales diarios
Original languageEnglish
JournalScientific data
Issue number1
StatePublished - Oct 2023

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health


Dive into the research topics of 'Non-pharmaceutical interventions to combat COVID-19 in the Americas described through daily sub-national data'. Together they form a unique fingerprint.

Cite this