Counts of COVID-19 reported in URUGUAY: 2020-2021
收藏DataCite Commons2024-07-09 更新2025-04-16 收录
下载链接:
https://zenodo.org/records/11452602
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资源简介:
Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
Project Tycho 数据集收录了全球各国上报的疾病病例数统计数据。Project Tycho 数据编目团队从各类权威来源提取上述病例数数据,来源通常为国家或国际卫生主管机构,例如美国疾病控制中心(US Centers for Disease Control)与世界卫生组织(World Health Organization)。上述原始数据源涵盖开放获取与受限访问两类资源。针对受限访问资源,Project Tycho 团队已获得数据提供方的再分发许可。所有数据集均保留与原始发布源完全一致的病例数统计结果,Project Tycho 团队未对任何病例数进行修改,仅在针对某一疾病与地区的最优可用数据为逐日汇总数据时,将单条病例数数据聚合为日度统计值。Project Tycho 团队已通过新增标准化疾病与地区标识符等变量完成数据集预处理,提升了数据的可解释性,同时将数据统一调整为标准数据格式。所有国家级与行政一级(admin1)的地理区域,只要可识别出ISO代码,均保留与原始数据源一致的地理层级;若数据源明确标注该地区的地理层级存在误差,则除外。如需了解编目团队的决策依据、推荐数据处理流程及所用数据源的详细信息,请参阅数据集下载压缩包中附带的 README 文件。
提供机构:
University of Pittsburgh
创建时间:
2022-08-12



