Counts of Dengue reported in GUYANA: 1978-2012

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".

Project Tycho 数据集收录全球各国上报的传染病病例数。Project Tycho 项目的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机构，例如美国疾病控制与预防中心（Centers for Disease Control and Prevention，简称 CDC）与世界卫生组织（World Health Organization，简称 WHO）。上述原始数据来源涵盖开放获取与受限访问两类渠道。针对受限访问数据源，Project Tycho 团队已获得数据提供方的再分发许可。所有数据集的病例数均与原始来源发布的统计值完全一致，Project Tycho 团队未对任何统计值进行修改。Project Tycho 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，以提升数据的可解释性，同时将数据统一格式化为标准数据结构。

每份 Project Tycho 数据集仅对应特定国家的特定传染病（例如麻疹）的病例数，病例数按时间周期进行统计上报。除病例数本身外，数据集还包含此类统计值的相关属性信息，例如地理位置、年龄分组、亚人群、诊断确定性、感染来源以及病例数的提取来源等。单个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：Project Tycho 数据集未包含未上报病例数的时间周期（由于源文档的不完整性，多数数据集的病例数时间序列存在缺失），使用者需自行补充无统计值的时间周期。但数据集已包含病例数为 0 的时间周期记录。
- 区分累计型与非累计型时间序列：Project Tycho 数据集内的病例数时间序列可分为「累计型」与「固定周期型」两类。累计型病例数时间序列由重叠的统计周期构成：所有周期起始日期相同，但结束日期各不相同。例如，某累计型统计序列的所有周期均始于 1 月 1 日，结束日期则分别为 1 月 7 日、14 日、21 日等。公共卫生机构通常采用累计时间周期的方式上报病例数。固定周期型病例数序列则由互斥的统计周期构成：所有周期的起始与结束日期均不相同，但周期长度完全一致（如日、周、月、年）。鉴于两类病例数数据的本质差异，我们为每个统计值新增了名为"PartOfCumulativeCountSeries"的属性，用以标识该值所属的序列类型。