Counts of Dengue reported in PITCAIRN: 2000-2003

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数据集包含全球各国报告的疾病病例数统计数据。Project Tycho数据整理团队从各类权威来源提取此类病例数数据，来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）、世界卫生组织（World Health Organization）。这些原始数据源涵盖开放获取与受限访问两类。对于受限访问数据源，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版本完全一致的病例数，未经过任何修改。Project Tycho团队已对数据集进行预处理，新增标准化疾病与位置标识符等变量以提升数据可解释性，同时将数据格式统一为标准格式。

每份Project Tycho数据集对应特定疾病（如麻疹）与特定国家（如美利坚合众国）的病例数统计，按时间间隔报告病例数。除病例数外，数据集还包含此类统计的相关属性信息，例如发病地点、年龄组、亚人群、诊断确定性、感染来源，以及病例数提取来源。一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报告的美国麻疹病例数”“世界卫生组织报告的美国麻疹病例数”，或“境外输入的美国麻疹病例数”等。

根据数据集的使用场景，我们建议在分析前完成以下数据处理步骤：
- 处理缺失数据：Project Tycho数据集未包含未报告病例数的时间区间（多数数据集的病例数时间序列因源文档不完整而存在缺失，用户需补充未记录病例数的时间区间）。需注意，数据集已包含报告病例数为0的时间区间。
- 区分累计型与非累计型时间序列：Project Tycho数据集中的病例数时间序列可分为“累计型”与“固定区间型”。累计型病例数时间序列由起始日期相同但结束日期不同的重叠区间构成，例如某累计计数序列的所有区间均始于1月1日，结束日期分别为1月7日、14日、21日等。公共卫生机构通常采用累计时间区间报告病例数。固定区间型病例数序列则由互斥的时间区间构成，所有区间的起始、结束日期均不相同，但时长一致（如日、周、月、年）。鉴于这两类病例数数据的性质差异，我们通过为每个计数值新增名为PartOfCumulativeCountSeries的属性进行标注区分。