Keshteli Ammar Hassanzadeh, Allen Dana, Anjum Afia, Patel Yashvi, Sivakumaran Aadhavya, Tian Siyang, Wang Fei, Wang Hao, Lewis Mark A, Greiner Russell, Wishart David S
Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada.
Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada.
Data Brief. 2021 Oct;38:107381. doi: 10.1016/j.dib.2021.107381. Epub 2021 Sep 20.
One year after identifying the first case of the 2019 coronavirus disease (COVID-19) in Canada, federal and provincial governments are still struggling to manage the pandemic. Provincial governments across Canada have experimented with widely varying policies in order to limit the burden of COVID-19. However, to date, the effectiveness of these policies has been difficult to ascertain. This is partly due to the lack of a publicly available, high-quality dataset on COVID-19 interventions and outcomes for Canada. The present paper provides a dataset containing important, Canadian-specific data that is known to affect COVID-19 outcomes, including sociodemographic, climatic, mobility and health system related information for all 10 Canadian provinces and their health regions. This dataset also includes longitudinal data on the daily number of COVID-19 cases, deaths, and the constantly changing intervention policies that have been implemented by each province in an attempt to control the pandemic.
在加拿大确诊首例2019冠状病毒病(COVID-19)一年后,联邦和省政府仍在努力应对这场疫情。加拿大各省的政府尝试了广泛不同的政策,以减轻COVID-19的负担。然而,迄今为止,这些政策的有效性难以确定。部分原因是缺乏一个关于加拿大COVID-19干预措施和结果的公开可用的高质量数据集。本文提供了一个数据集,其中包含已知会影响COVID-19结果的重要的、加拿大特有的数据,包括加拿大所有10个省及其卫生区域的社会人口、气候、流动性和卫生系统相关信息。该数据集还包括COVID-19病例数、死亡数的每日纵向数据,以及每个省为控制疫情而实施的不断变化的干预政策。