论文标题
WNTRAC：AI辅助跟踪全球为Covid-19实施的非药物干预措施
WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
论文作者
论文摘要
2019年冠状病毒病（Covid-19）全球大流行改变了世界各地人类社会的几乎所有方面。全世界政府针对新兴的，高度可传播的疾病，没有明确的治疗或疫苗，已经实施了非药物干预（NPI），以减缓病毒的传播。此类干预措施的例子包括社区行动（例如，关闭学校，对大众聚会的限制），个人行动（例如，戴面具，戴，自我争夺）和环境行动（例如，公共设施清洁）。我们介绍了Covid-19（WNTRAC）的全球非药物干预跟踪器，这是一个综合数据集，该数据集由自大流行开始以来全球实施的6,000多个NPI组成。 WNTRAC涵盖了在261个国家和地区实施的NPI，并将NPI措施分类为16种NPI类型的分类法。 NPI措施每天使用自然语言处理技术从Wikipedia文章中自动提取，并手动验证以确保准确性和真实性。我们希望该数据集在控制Covid-19的传播的建模和分析工作中对决策者，公共卫生领导者和研究人员来说都是有价值的。
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.
