COVID-19 case rate per 100,000 population and percent test positivity in the last 14 days by town - ARCHIVE

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. This dataset includes a count and rate per 100,000 population for COVID-19 cases, a count of COVID-19 molecular diagnostic tests, and a percent positivity rate for tests among people living in community settings for the previous two-week period. Dates are based on date of specimen collection (cases and positivity). A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case. Percent positivity is calculated as the number of positive tests among community residents conducted during the 14 days divided by the total number of positive and negative tests among community residents during the same period. If someone was tested more than once during that 14 day period, then those multiple test results (regardless of whether they were positive or negative) are included in the calculation. These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities. These data are updated weekly and reflect the previous two full Sunday-Saturday (MMWR) weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). DPH note about change from 7-day to 14-day metrics: Prior to 10/15/2020, these metrics were calculated using a 7-day average rather than a 14-day average. The 7-day metrics are no longer being updated as of 10/15/2020 but the archived dataset can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/s22x-83rd As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well. With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as the

备注：康涅狄格州公共卫生部（Connecticut Department of Public Health，DPH）正在更新并精简新冠病例、死亡及检测数据。自2022年6月27日起，相关数据将以4张数据表而非12张的形式发布。
《每日新冠病例、死亡与检测数据》数据集包含按样本提交日期统计的病例及检测数据，其中死亡数据按死亡日期统计。该数据集每日更新，收录了新冠疫情暴发以来的全部相关信息，数据可通过以下链接获取：https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj。
《新冠疫情州级指标》数据集包含超过93列数据，每日更新，当前收录2022年6月21日至今的相关信息，数据链接为：https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6。
《新冠疫情县级指标》数据集包含25列数据，每日更新，当前收录2022年6月16日至今的相关信息，数据链接为：https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22。
《新冠疫情镇级指标》数据集包含16列数据，每日更新，当前收录2022年6月16日至今的相关信息，数据链接为：https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada。
为保护个人隐私，若某镇过去7天内的新冠病例数或核酸扩增检测（Nucleic Acid Amplification Test，NAAT）阳性结果数少于5例，则相关数据将予以隐藏。
该数据集包含新冠病例数及每10万人口病例率、新冠分子诊断检测数，以及过去两周内社区居民的检测阳性率。数据日期以标本采集日期为准（适用于病例及阳性检测结果）。
仅当个人首次获得新冠检测阳性结果时，才会被计为新增病例——因为病例被定义为一次感染病程。若后续再次检测仍为阳性，该结果会计入检测阳性率统计，但不会被计为新增病例。
检测阳性率的计算方式为：过去14天内社区居民的阳性检测数除以同期社区居民的总检测数（含阳性与阴性）。若个人在该14天内多次接受检测，则所有检测结果（无论阳性或阴性）均会被纳入统计。
上述病例与检测统计不包含养老机构、辅助生活设施及矫正机构等聚集性场所内人员的相关病例或检测数据。
该类数据每周更新，涵盖过去两个完整的周日至周六周期（即美国疾病控制与预防中心（Centers for Disease Control and Prevention，CDC）的发病与死亡周报（Morbidity and Mortality Weekly Report，MMWR）周期，详见https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf）。
康涅狄格州公共卫生部关于指标计算周期从7天调整为14天的说明：2020年10月15日之前，此类指标以7天均值进行计算，而非14天均值。自2020年10月15日起，7天周期指标不再更新，但存档数据集可通过以下链接获取：https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/s22x-83rd。
众所周知，我们对新冠疫情的认知始终在深化，包括监测社区新冠传播活动的最优方法。康涅狄格州公共卫生部决定改用14天指标率，因其相较7天指标率更为稳定，在镇级数据层面尤为明显。
此外，自去年夏季康涅狄格州公共卫生部首次发布校园疫情指标以来，美国疾控中心已建议采用14天指标率，其他州（如马萨诸塞州）也已开始采用14天周期指标来监测新冠传播情况。
就地理维度而言，我们注意到尽管官方增补文件中重点强调县级指标，但仍有许多民众通过镇级数据辅助决策，这一情况不难理解，因为