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Counts of Dengue hemorrhagic fever reported in AMERICAN SAMOA: 2004-2009

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NIAID Data Ecosystem2026-04-18 收录
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https://www.tycho.pitt.edu/dataset/AS.20927009
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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. 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. Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datasets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of acquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc. Depending on the intended use of a dataset, we recommend a few data processing steps before analysis: - Analyze missing data: Project Tycho datasets do not include time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported. - Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

Project Tycho数据集收录了全球各国报告的传染病病例数。Project Tycho数据整理团队从各类权威数据源提取上述病例数,此类数据源通常为国家或国际卫生主管部门,例如美国疾病控制与预防中心(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。针对受限访问数据源,Project Tycho团队已获得数据贡献方的再分发许可。所有数据集均保留与原始发布源完全一致的病例数数据,Project Tycho团队未对任何病例数进行任何形式的修改。Project Tycho团队已完成数据集预处理工作,新增了标准化疾病与位置标识符等变量,以提升数据可解释性,同时将数据统一格式化为标准数据格式。 每份Project Tycho数据集仅收录特定传染病(如麻疹)与特定国家(如美国)的病例数,病例数按时间间隔进行统计上报。除病例数外,数据集还包含该类数据的相关属性信息,例如统计地点、年龄分组、亚人群、诊断确定性、感染来源以及病例数提取来源等。单份数据集可包含多组病例数时间序列,例如"美国疾病控制与预防中心上报的美国麻疹病例数"、"世界卫生组织上报的美国麻疹病例数"以及"境外输入性美国麻疹病例数"等。 根据数据集的具体使用场景,我们建议在开展分析前完成以下数据处理步骤: 1. 缺失数据处理:Project Tycho数据集未收录无病例数上报的时间间隔(由于源文档不完整,多数数据集的病例数时间序列存在缺失,用户需自行补充无对应计数的时间间隔);但数据集已包含病例数为0的时间间隔记录。 2. 区分累积型与非累积型时间序列:Project Tycho数据集的病例数时间序列可分为"累积型"与"固定间隔型"两类。累积型病例数时间序列由重叠的时间区间构成,此类区间起始日期一致,但终止日期各不相同。例如,某累积计数时间序列中的每个区间均可起始于1月1日,终止日期分别为1月7日、14日、21日等。公共卫生机构通常会按累积时间区间上报病例数。固定间隔型病例数时间序列由互斥的时间区间构成,所有区间的起始与终止日期均不相同,但区间长度完全一致(如日、周、月、年)。鉴于这两类病例数数据的特性存在差异,我们为每个计数值新增了名为"PartOfCumulativeCountSeries"的属性,用以标记其所属类型。
创建时间:
2018-04-01
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