Catalogue Search | MBRL
Search Results Heading
Explore the vast range of titles available.
MBRLSearchResults
-
DisciplineDiscipline
-
Is Peer ReviewedIs Peer Reviewed
-
Item TypeItem Type
-
SubjectSubject
-
YearFrom:-To:
-
More FiltersMore FiltersSourceLanguage
Done
Filters
Reset
2
result(s) for
"Samuel, Osebe Mogaka"
Sort by:
AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19
by
Otieno, Fred
,
Wachira, Charles
,
Poddar, Ananya
in
692/700/1538
,
692/700/3934
,
706/648/697/129
2021
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
Journal Article
WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
by
Otieno, Fred
,
Osebe Mogaka Samuel
,
Parthasarathy Suryanarayanan
in
Artificial intelligence
,
Closures
,
Coronaviruses
2021
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 with no definitive treatment or vaccine, governments worldwide have implemented non-pharmaceutical intervention (NPI) to slow the spread of the virus. Examples of such interventions include community actions (e.g. school closures, restrictions on mass gatherings), individual actions (e.g. mask wearing, self-quarantine), and environmental actions (e.g. public facility cleaning). 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 NPI measures into a taxonomy of sixteen NPI types. NPI measures are automatically extracted daily from Wikipedia articles using natural language processing techniques and manually validated to ensure accuracy and veracity. We hope that the dataset is valuable for policymakers, public health leaders, and researchers in modeling and analysis efforts for controlling the spread of COVID-19.