Counts of Dengue reported in MEXICO: 1971-2012

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".

第谷计划（Project Tycho）数据集收录了全球各国上报的各类疾病的病例计数数据。第谷计划数据整理团队从各类权威来源提取上述病例计数数据，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）与世界卫生组织。上述原始数据来源涵盖开放获取与受限获取两类渠道，对于受限获取来源，第谷计划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计数数据，第谷计划团队未对任何计数内容进行修改。团队已对数据集完成预处理，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，并将数据统一格式化为标准数据结构。

每个第谷计划数据集仅对应特定疾病（如麻疹）与特定国家（如美国）的病例计数数据，病例计数按时间区间进行统计上报。除病例计数外，数据集还包含与计数相关的各类属性信息，例如数据所属地点、年龄分组、亚人群、诊断确定性、感染来源以及数据提取来源等。单个数据集可包含多组病例计数时间序列，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。

根据数据集的预期使用场景，我们建议在开展分析前完成以下数据处理步骤：
- 处理缺失数据：第谷计划数据集不会收录未上报病例数的时间区间（由于源文档存在缺失，多数数据集的病例计数时间序列并不完整），用户需自行补充无计数的时间区间。需注意，数据集已收录病例数为0的时间区间。
- 分离累积型与非累积型时间区间序列：第谷计划数据集内的病例计数时间序列可分为“累积型”与“固定区间型”两类。累积型病例计数时间序列由重叠的计数区间构成，这类区间均起始于同一日期，但终止日期各不相同。例如，某累积计数序列的所有区间均起始于1月1日，终止日期则分别为1月7日、14日、21日等。公共卫生机构通常会采用累积时间区间的方式上报病例数。固定区间型病例计数序列则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）。鉴于这两类病例计数数据的性质存在差异，我们为每个计数值新增了名为“PartOfCumulativeCountSeries”的属性，用于标记其所属类型。