Journal Article

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

Otieno, Fred, Wachira, Charles, Poddar, Ananya, Madan, Piyush, Bar-Shira, Osnat, Matu, Fiona, Guhan, Pooja, Mahatma, Shilpa, Pathak, Divya, Nyota, Timothy, Shats, Daniel, Tsou, Ching-Huei, Ogallo, William, Barros, Vesna Resende, Dandala, Bharath, Kagan, Oren, Walcott-Bryant, Aisha, Suryanarayanan, Parthasarathy, Mahajan, Diwakar, Okwako, Sharon, Samuel, Osebe Mogaka, Bent, Oliver, Kipchirchir, Clifton, Remy, Sekou, Rosen-Zvi, Michal, Agrawal, Anshul

2021

Overview

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. Measurement(s) Preventive Intervention • Public Health Technology Type(s) natural language processing objective • Artificial Intelligence Sample Characteristic - Environment anthropogenic environment Sample Characteristic - Location Global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13999484

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 692/700/1538 / 692/700/3934 / 706/648/697/129 / Artificial Intelligence / Communicable Disease Control - trends / Coronaviruses / COVID-19 / COVID-19 - prevention & control / COVID-19 - therapy / Data Descriptor / Global Health / Humanities and Social Sciences / Humans / Language / multidisciplinary / Natural language processing / Pandemics / Pharmaceuticals / Public health / Science / Science (multidisciplinary)