COVID-19 non-pharmaceutical interventions: data annotation for rapidly changing local policy information-Reference-Cited by-同舟云学术

COVID-19 non-pharmaceutical interventions: data annotation for rapidly changing local policy information

Published:2023-03-09 Issue:1 Volume:10 Page:
ISSN:2052-4463
Container-title:Scientific Data
language:en
Short-container-title:Sci Data

Author:

Hurt Benjamin^ORCID,Hoque Oishee Bintey^ORCID,Mokrzycki Finn^ORCID,Mathew Anjali,Xue Maryann,Gabitsinashvili Luka^ORCID,Mokrzycki Haile,Fischer Ranya,Telesca Nicholas,Xue Lauren Aurelia,Ritchie Jacob^ORCID,Zamfirescu-Pereira J. D.,Bernstein Michael^ORCID,Whiting Mark^ORCID,Marathe Madhav

Abstract

AbstractUnderstanding the scope, prevalence, and impact of the COVID-19 pandemic response will be a rich ground for research for many years. Key to the response to COVID-19 was the non-pharmaceutical intervention (NPI) measures, such as mask mandates or stay-in-place orders. For future pandemic preparedness, it is critical to understand the impact and scope of these interventions. Given the ongoing nature of the pandemic, existing NPI studies covering only the initial portion provide only a narrow view of the impact of NPI measures. This paper describes a dataset of NPI measures taken by counties in the U.S. state of Virginia that include measures taken over the first two years of the pandemic beginning in March 2020. This data enables analyses of NPI measures over a long time period that can produce impact analyses on both the individual NPI effectiveness in slowing the pandemic spread, and the impact of various NPI measures on the behavior and conditions of the different counties and state.

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

Link

https://www.nature.com/articles/s41597-023-01979-6.pdf

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