US Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia, USA.
Clin Infect Dis. 2021 Nov 16;73(10):1831-1839. doi: 10.1093/cid/ciab185.
Monitoring of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence can complement case reporting to inform more accurate estimates of SARS-CoV-2 infection burden, but few studies have undertaken repeated sampling over time on a broad geographic scale.
We performed serologic testing on a convenience sample of residual serum obtained from persons of all ages, at 10 sites in the United States from 23 March through 14 August 2020, from routine clinical testing at commercial laboratories. We standardized our seroprevalence rates by age and sex, using census population projections and adjusted for laboratory assay performance. Confidence intervals were generated with a 2-stage bootstrap. We used bayesian modeling to test whether seroprevalence changes over time were statistically significant.
Seroprevalence remained below 10% at all sites except New York and Florida, where it reached 23.2% and 13.3%, respectively. Statistically significant increases in seroprevalence followed peaks in reported cases in New York, South Florida, Utah, Missouri, and Louisiana. In the absence of such peaks, some significant decreases were observed over time in New York, Missouri, Utah, and Western Washington. The estimated cumulative number of infections with detectable antibody response continued to exceed reported cases in all sites.
Estimated seroprevalence was low in most sites, indicating that most people in the United States had not been infected with SARS-CoV-2 as of July 2020. The majority of infections are likely not reported. Decreases in seroprevalence may be related to changes in healthcare-seeking behavior, or evidence of waning of detectable anti-SARS-CoV-2 antibody levels at the population level. Thus, seroprevalence estimates may underestimate the cumulative incidence of infection.
监测严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）抗体的流行情况可以补充病例报告，从而更准确地估计 SARS-CoV-2 感染负担，但很少有研究在广泛的地理范围内随着时间的推移进行重复采样。
我们在美国 10 个地点的商业实验室常规临床检测中，对 2020 年 3 月 23 日至 8 月 14 日期间从所有年龄段的人群中获得的剩余血清进行了血清学检测。我们使用人口普查人口预测数据对年龄和性别进行了标准化，并对实验室检测性能进行了调整。置信区间通过两阶段自举法生成。我们使用贝叶斯模型来检验血清流行率随时间变化是否具有统计学意义。
除纽约和佛罗里达州外，所有地点的血清流行率均低于 10%，纽约和佛罗里达州分别达到 23.2%和 13.3%。在纽约、南佛罗里达州、犹他州、密苏里州和路易斯安那州报告病例达到峰值后，血清流行率呈显著上升趋势。在没有这种峰值的情况下，纽约、密苏里州、犹他州和华盛顿西部的血清流行率随时间呈显著下降趋势。在所有地点，估计具有可检测抗体反应的累积感染人数继续超过报告病例数。
截至 2020 年 7 月，大多数地点的估计血清流行率较低，表明美国大多数人尚未感染 SARS-CoV-2。大多数感染病例可能未被报告。血清流行率下降可能与医疗寻求行为的变化有关，或者是人群中可检测到的抗 SARS-CoV-2 抗体水平下降的证据。因此，血清流行率估计可能低估了感染的累积发生率。
