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.

全球冠状病毒病2019（COVID-19）流行已经改变了全世界人类社会的几乎所有方面。针对一种新兴的，高度传播的疾病，世界各国政府已实施非药物干预措施（NPI），以减慢病毒的传播速度。此类干预措施的例子包括社区行动，例如学校停课或限制群众聚会；个人行动，包括戴口罩和自我隔离；以及环境行动，例如清洁公共设施。我们展示了针对COVID-19的全球非药物干预追踪器（WNTRAC），这是自大流行开始以来在全球范围内实施的6,000多种NPI的综合数据集。WNTRAC涵盖了在261个国家和地区实施的NPI，并将NPI分为16种NPI类型的分类法。每天使用自然语言处理技术自动从Wikipedia文章中提取NPI，然后手动进行验证以确保准确性和准确性。我们希望该数据集将对决策者，公共卫生领导者和研究人员进行建模和分析工作以控制COVID-19传播时证明有价值。