背景:许多针对COVID-19快速抗原测试的大规模分布的干预措施已经在网上使用,直接面向消费者(DTC)订购系统;然而,对家庭测试用户的社会人口统计学特征知之甚少。我们旨在表征快速抗原测试的在线订单模式,并分别确定与COVID-19的邻里特征和社区发生率的地理空间和时间关联。
方法:这项观察性研究在线分析,DTC从2021年3月至11月在五个社区从SayYes!Covid测试计划的受益者那里订购快速抗原测试试剂盒:路易斯维尔,肯塔基州;印第安纳波利斯,印第安纳州;富尔顿县,格鲁吉亚;奥阿胡,夏威夷;安阿伯/伊普西兰蒂,密歇根。使用空间自回归模型,我们评估了测试套件分布与人口普查区块水平教育的地理空间关联,收入,年龄,人口密度,种族分布和人口普查道一级社会脆弱性指数。滞后关联分析用于测量在线快速抗原试剂盒订单与社区水平COVID-19发病率之间的关联。
结果:总计,在干预期间订购了164,402个DTC测试套件。所有站点的测试分布在块组水平上显著地在地理空间上聚集(Moran'sI:p<0.001);然而,教育,收入,年龄,人口密度,种族,和社会脆弱性指数与跨站点的测试订单不一致。在密歇根,格鲁吉亚,还有肯塔基,当天COVID-19的发病率与检测试剂盒的订购量之间有很强的相关性(密歇根州:r=0.89,乔治亚州:r=0.85,肯塔基州:r=0.75).当天和前6天COVID-19的发病率使当前DTC订单增加9.0(95%CI=1.7,16.3),3.0(95%CI=1.3,4.6),密歇根州为6.8(95%CI=3.4,10.2),格鲁吉亚,还有肯塔基,分别。印第安纳州检测试剂盒订单与COVID-19发病率之间没有同一天或6天的滞后相关性。
结论:我们的研究结果表明,在线订购与基于社会人口统计学特征的地理空间聚类无关。观察到的DTC订购的时间首选项可以指导DTC测试计划周围的公共卫生消息。
Many interventions for widescale distribution of rapid antigen tests for COVID-19 have utilized online, direct-to-consumer (DTC) ordering systems; however, little is known about the sociodemographic characteristics of home-test users. We aimed to characterize the patterns of online orders for rapid antigen tests and determine geospatial and temporal associations with neighborhood characteristics and community incidence of COVID-19, respectively.
This observational study analyzed online, DTC orders for rapid antigen test kits from beneficiaries of the Say Yes! Covid Test program from March to November 2021 in five communities: Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O\'ahu, Hawaii; and Ann Arbor/Ypsilanti, Michigan. Using spatial autoregressive models, we assessed the geospatial associations of test kit distribution with Census block-level education, income, age, population density, and racial distribution and Census tract-level Social Vulnerability Index. Lag association analyses were used to measure the association between online rapid antigen kit orders and community-level COVID-19 incidence.
In total, 164,402 DTC test kits were ordered during the intervention. Distribution of tests at all sites were significantly geospatially clustered at the block-group level (Moran\'s I: p < 0.001); however, education, income, age, population density, race, and social vulnerability index were inconsistently associated with test orders across sites. In Michigan, Georgia, and Kentucky, there were strong associations between same-day COVID-19 incidence and test kit orders (Michigan: r = 0.89, Georgia: r = 0.85, Kentucky: r = 0.75). The incidence of COVID-19 during the current day and the previous 6-days increased current DTC orders by 9.0 (95% CI = 1.7, 16.3), 3.0 (95% CI = 1.3, 4.6), and 6.8 (95% CI = 3.4, 10.2) in Michigan, Georgia, and Kentucky, respectively. There was no same-day or 6-day lagged correlation between test kit orders and COVID-19 incidence in Indiana.
Our findings suggest that online ordering is not associated with geospatial clustering based on sociodemographic characteristics. Observed temporal preferences for DTC ordering can guide public health messaging around DTC testing programs.