{"title":"德克萨斯州四个县COVID-19病例与死亡之间的相关性","authors":"A. Chin, K. Chin, T. Chin","doi":"10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3092","DOIUrl":null,"url":null,"abstract":"Rationale: Predicting deaths from COVID-19 in the near-term has important public health implications. National models may not be applicable at the county level, where limited test availability and/or delays in test results may alter the relationship between COVID-19 diagnoses and deaths. Methods: Publicly available data for daily new COVID-19 cases and deaths from March 4th, 2020 to December 1st, 2020 in Dallas County was obtained from the Texas Department of State Health Services website on December 17th, 2020. COVID-19 cases were reported by local health departments based on the date of test results, while deaths were reported based on death certificates. Due to the lag in case and death reporting, the last two weeks prior to the date of download were excluded. A linear regression was performed using the 7-day rolling average of newly reported cases vs the 7-day rolling average of new deaths utilizing different lag periods. The lag period resulting in the highest R2 value was identified. A similar analysis was subsequently performed in three other Texas counties. Results: Dallas County, which has a population of 2.636 million, had 114,981 confirmed COVID-19 cases and 1708 COVID-19 related deaths over the study period. As shown in Figure 1A, The maximum R2 value was observed at a lag period of 10 days (R2 = 0.8158, p < 0.001). Spikes in cases were seen in July and late November, with deaths following shortly after (Figure 1B). Similar results were seen in Tarrant and Bexar counties, with a maximum R2 value occurring at a lag period of 12 and 7 days (R2 = 0.7323, R2 = 0.7800), respectively. However, Harris County had a maximum R2 value at a lag of only 2 days (R2 = 0.7324). Discussion: Potential contributors to the lag between diagnosis and death include the disease process itself as well as county specific delays in testing and/or testing reporting. In particular, in locations with large surges, cases may overwhelm testing capabilities such that mean case count is under reported, and more cases are identified late in the disease process. Conclusions: In all four counties, peaks in deaths from COVID-19 closely followed peaks in reported cases. In three of four counties, the lag was 7-12 days, consistent with the expected lag between diagnosis and death. In Harris county however, the lag was only 2 days, supporting the idea that national models may not be applicable at a county level.","PeriodicalId":375809,"journal":{"name":"TP63. TP063 COVID-19 IN ENVIRONMENTAL, OCCUPATIONAL, AND POPULATION HEALTH","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Correlation Between COVID-19 Cases and Deaths in Four Texas Counties\",\"authors\":\"A. Chin, K. Chin, T. Chin\",\"doi\":\"10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rationale: Predicting deaths from COVID-19 in the near-term has important public health implications. National models may not be applicable at the county level, where limited test availability and/or delays in test results may alter the relationship between COVID-19 diagnoses and deaths. Methods: Publicly available data for daily new COVID-19 cases and deaths from March 4th, 2020 to December 1st, 2020 in Dallas County was obtained from the Texas Department of State Health Services website on December 17th, 2020. COVID-19 cases were reported by local health departments based on the date of test results, while deaths were reported based on death certificates. Due to the lag in case and death reporting, the last two weeks prior to the date of download were excluded. A linear regression was performed using the 7-day rolling average of newly reported cases vs the 7-day rolling average of new deaths utilizing different lag periods. The lag period resulting in the highest R2 value was identified. A similar analysis was subsequently performed in three other Texas counties. Results: Dallas County, which has a population of 2.636 million, had 114,981 confirmed COVID-19 cases and 1708 COVID-19 related deaths over the study period. As shown in Figure 1A, The maximum R2 value was observed at a lag period of 10 days (R2 = 0.8158, p < 0.001). Spikes in cases were seen in July and late November, with deaths following shortly after (Figure 1B). Similar results were seen in Tarrant and Bexar counties, with a maximum R2 value occurring at a lag period of 12 and 7 days (R2 = 0.7323, R2 = 0.7800), respectively. However, Harris County had a maximum R2 value at a lag of only 2 days (R2 = 0.7324). Discussion: Potential contributors to the lag between diagnosis and death include the disease process itself as well as county specific delays in testing and/or testing reporting. In particular, in locations with large surges, cases may overwhelm testing capabilities such that mean case count is under reported, and more cases are identified late in the disease process. Conclusions: In all four counties, peaks in deaths from COVID-19 closely followed peaks in reported cases. In three of four counties, the lag was 7-12 days, consistent with the expected lag between diagnosis and death. In Harris county however, the lag was only 2 days, supporting the idea that national models may not be applicable at a county level.\",\"PeriodicalId\":375809,\"journal\":{\"name\":\"TP63. TP063 COVID-19 IN ENVIRONMENTAL, OCCUPATIONAL, AND POPULATION HEALTH\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TP63. TP063 COVID-19 IN ENVIRONMENTAL, OCCUPATIONAL, AND POPULATION HEALTH\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3092\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TP63. TP063 COVID-19 IN ENVIRONMENTAL, OCCUPATIONAL, AND POPULATION HEALTH","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
理由:预测近期COVID-19的死亡人数具有重要的公共卫生意义。国家模式可能不适用于县一级,在县一级,有限的检测可用性和/或检测结果的延迟可能会改变COVID-19诊断与死亡之间的关系。方法:从2020年12月17日德克萨斯州卫生服务部网站获取2020年3月4日至2020年12月1日达拉斯县每日新增COVID-19病例和死亡的公开数据。当地卫生部门根据检测结果日期报告新冠肺炎病例,根据死亡证明报告死亡人数。由于病例和死亡报告滞后,因此不包括下载日期前最后两周的病例。使用新报告病例的7天滚动平均值与使用不同滞后期的新死亡的7天滚动平均值进行线性回归。确定了导致最高R2值的滞后时间。随后在德克萨斯州的其他三个县进行了类似的分析。结果:达拉斯县有263.6万人口,在研究期间确诊了114981例COVID-19病例,1708例COVID-19相关死亡。如图1A所示,滞后期为10 d时,R2值达到最大值(R2 = 0.8158, p <0.001)。7月和11月下旬出现病例高峰,随后不久出现死亡(图1B)。塔兰特县和贝尔县也出现了类似的结果,R2最大值分别出现在滞后12天和7天(R2 = 0.7323, R2 = 0.780)。而哈里斯县的R2最大值仅滞后2 d (R2 = 0.7324)。讨论:造成诊断和死亡之间滞后的潜在因素包括疾病过程本身以及国家在检测和/或检测报告方面的特定延迟。特别是,在大量激增的地区,病例可能超过检测能力,导致报告的平均病例数不足,并且在疾病过程的后期发现了更多病例。结论:在所有四个县,COVID-19死亡高峰与报告病例高峰密切相关。在4个县中,有3个县的滞后期为7-12天,与诊断和死亡之间的预期滞后期一致。然而,在哈里斯县,滞后时间仅为2天,这支持了国家模式可能不适用于县一级的观点。
Correlation Between COVID-19 Cases and Deaths in Four Texas Counties
Rationale: Predicting deaths from COVID-19 in the near-term has important public health implications. National models may not be applicable at the county level, where limited test availability and/or delays in test results may alter the relationship between COVID-19 diagnoses and deaths. Methods: Publicly available data for daily new COVID-19 cases and deaths from March 4th, 2020 to December 1st, 2020 in Dallas County was obtained from the Texas Department of State Health Services website on December 17th, 2020. COVID-19 cases were reported by local health departments based on the date of test results, while deaths were reported based on death certificates. Due to the lag in case and death reporting, the last two weeks prior to the date of download were excluded. A linear regression was performed using the 7-day rolling average of newly reported cases vs the 7-day rolling average of new deaths utilizing different lag periods. The lag period resulting in the highest R2 value was identified. A similar analysis was subsequently performed in three other Texas counties. Results: Dallas County, which has a population of 2.636 million, had 114,981 confirmed COVID-19 cases and 1708 COVID-19 related deaths over the study period. As shown in Figure 1A, The maximum R2 value was observed at a lag period of 10 days (R2 = 0.8158, p < 0.001). Spikes in cases were seen in July and late November, with deaths following shortly after (Figure 1B). Similar results were seen in Tarrant and Bexar counties, with a maximum R2 value occurring at a lag period of 12 and 7 days (R2 = 0.7323, R2 = 0.7800), respectively. However, Harris County had a maximum R2 value at a lag of only 2 days (R2 = 0.7324). Discussion: Potential contributors to the lag between diagnosis and death include the disease process itself as well as county specific delays in testing and/or testing reporting. In particular, in locations with large surges, cases may overwhelm testing capabilities such that mean case count is under reported, and more cases are identified late in the disease process. Conclusions: In all four counties, peaks in deaths from COVID-19 closely followed peaks in reported cases. In three of four counties, the lag was 7-12 days, consistent with the expected lag between diagnosis and death. In Harris county however, the lag was only 2 days, supporting the idea that national models may not be applicable at a county level.