Lyme disease public use aggregated data with geography, 1992-2007

Overview: Public health surveillance data are collected and reported voluntarily to CDC by U.S. states and territories through the National Notifiable Diseases Surveillance System (NNDSS) (https://www.cdc.gov/nndss/index.html). Data include demographic, clinical, and geographic information; data do not include direct identifiers. Two types of datasets of human Lyme disease case data collected through public health surveillance are available: one includes annual case count aggregated by county of residence according to specific demographic variables and one is line-listed with patient demographic factors, month of illness onset, and clinical presentation information but without corresponding geographic information. These privacy-protected datasets were implemented in accordance with methodology described in Lee et al. Protecting Privacy and Transforming COVID-19 Case Surveillance Datasets for Public Use. Public Health Rep. 2021 Sep-Oct;136(5):554-561. doi: 10.1177/00333549211026817. Lyme disease became nationally notifiable in 1991. Different surveillance case definitions have been in effect over time; details are available here: https://ndc.services.cdc.gov/conditions/lyme-disease/. In 2008, a probable case definition was included in public health surveillance for the first time. In 2022, states with a high incidence of Lyme disease started reporting cases based on laboratory evidence alone without requirement for a clinical investigation, precluding comparison with historical data (for more information: https://www.cdc.gov/mmwr/volumes/73/wr/mm7306a1.htm?s_cid=mm7306a1_w). As such, Lyme disease surveillance data are grouped into separate datasets based on when these major changes occurred; data are provided for download separately for 1992–2007, 2008–2021, and 2022 to current. Data will be updated annually upon final verification of Lyme disease surveillance data by health departments. Data Limitations: Surveillance data have significant limitations that must be considered in the analysis, interpretation, and reporting of results. 1. Under-reporting and misclassification are features common to all surveillance systems. Not every case of Lyme disease is reported to CDC, and some cases that are reported may be reflect illness due to another cause. 2. Please note that before the 2022 surveillance case definition went into effect, several states with high Lyme disease incidence had initiated alternative methods of surveillance and those data were not reportable to CDC. 3. Final case data are subject to each state’s abilities to capture and classify cases, which is dependent upon budget and personnel. This can vary not only between states, but also from year to year within a given state. Consequently, a sudden or marked change in reported cases does not necessarily represent a true change in disease incidence. Every effort should be made to construct analyses to limit overinterpretation of this variation (see the following reference for more context: Kugeler KJ, Eisen RJ. Challenges in Predicting Lyme Disease Risk. JAMA Netw Open. 2020 Mar 2;3(3):e200328. doi: 10.1001/jamanetworkopen.2020.0328.)概述： 本数据集的公共卫生监测数据由美国各州及领地通过国家法定传染病监测系统（National Notifiable Diseases Surveillance System, NNDSS）自愿上报至美国疾病控制与预防中心（Centers for Disease Control and Prevention, CDC），相关查询网址为：https://www.cdc.gov/nndss/index.html。数据涵盖人口统计学、临床及地理信息，且不包含直接识别信息。目前可获取两类通过公共卫生监测收集的人类莱姆病病例数据集：一类为按患者居住县聚合的年度病例计数数据，基于特定人口统计学变量进行汇总；另一类为逐病例列表式数据集，包含患者人口统计学特征、发病月份及临床表现信息，但未附带对应地理信息。本批受隐私保护的数据集构建遵循Lee等人于《公共卫生报告》（Public Health Rep. 2021年9-10月刊，第136卷第5期，554-561页，DOI: 10.1177/00333549211026817）发表的《保护隐私并优化面向公众使用的新冠病例监测数据集》一文所述方法。 莱姆病于1991年被纳入全国法定传染病报告范畴。随着时间推移，不同的监测病例定义先后生效，详细信息可通过以下链接查阅：https://ndc.services.cdc.gov/conditions/lyme-disease/。2008年，公共卫生监测体系首次纳入疑似病例定义。2022年，莱姆病高发病率州开始仅基于实验室检测证据上报病例，不再要求开展临床调查，该调整导致当前数据无法与历史数据进行横向比较（更多相关信息可参阅：https://www.cdc.gov/mmwr/volumes/73/wr/mm7306a1.htm?s_cid=mm7306a1_w）。据此，莱姆病监测数据根据上述重大变更节点划分为独立数据集，分别提供1992–2007年、2008–2021年及2022年至今三个时段的数据供下载。各卫生部门完成莱姆病监测数据最终核验后，数据集将按年度更新。 数据局限性： 监测数据存在显著局限性，在数据分析、结果解读及报告撰写过程中必须予以充分考量： 1. 漏报与错分类是所有传染病监测系统共有的固有特征。并非所有莱姆病病例都会上报至CDC，部分上报病例可能实际由其他病因引发。 2. 请注意，在2022版监测病例定义正式生效前，多个莱姆病高发病率州已采用替代监测方案，此类数据并未上报至CDC。 3. 最终病例数据的质量取决于各州对病例的捕获与分类能力，而该能力受预算与人员配置水平影响。这种差异不仅存在于各州之间，同一州内也会随年份变化出现波动。因此，上报病例数的突发或显著变化未必代表疾病发病率的真实改变。应尽可能通过合理的分析设计，避免对这类数据波动做出过度解读（更多背景信息请参阅文献：Kugeler KJ, Eisen RJ. 莱姆病风险预测面临的挑战. JAMA网络公开. 2020年3月2日;3(3):e200328. DOI: 10.1001/jamanetworkopen.2020.0328.）