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Nature: AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19

Mary Wilson

New member
Published: 25 March 2021
DOI: https://doi.org/10.1038/s41597-021-00878-y

ParthasarathySuryanarayanan 1?,Ching-Hueitsou1,ananyaPoddar1,DiwakarMahajan 1, Bharath Dandala 1, Piyush Madan2, anshul agrawal1, Charles Wachira3,
Osebe Mogaka Samuel3, Osnat Bar-Shira4, Clifton Kipchirchir3, Sharon Okwako3,
William Ogallo3, Fred Otieno3, timothy Nyota3, Fiona Matu3, Vesna Resende Barros4,
Daniel Shats4, Oren Kagan4, Sekou Remy3, Oliver Bent3, Pooja Guhan3, Shilpa Mahatma1, aisha Walcott-Bryant3, Divya Pathak1 & Michal Rosen-Zvi 4


Abstract

The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease, governments worldwide have implemented non-pharmaceutical interventions (NPIs) to slow the spread of the virus. Examples of such interventions include community actions, such as school closures or restrictions on mass gatherings, individual actions including mask wearing and self-quarantine, and environmental actions such as cleaning public facilities. We present the Worldwide Non-pharmaceutical Interventions Tracker for COVID-19 (WNTRAC), a comprehensive dataset consisting of over 6,000 NPIs implemented worldwide since the start of the pandemic. WNTRAC covers NPIs implemented across 261 countries and territories, and classifies NPIs into a taxonomy of 16 NPI types. NPIs are automatically extracted daily from Wikipedia articles using natural language processing techniques and then manually validated to ensure accuracy and veracity. We hope that the dataset will prove valuable for policymakers, public health leaders, and researchers in modeling and analysis efforts to control the spread of COVID-19.
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PDF Format:
https://www.nature.com/articles/s41597-021-00878-y.pdf
 
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