Department of Surgery, School of Medicine, University of California Irvine, Irvine, CA, USA.
Institute for Clinical and Translational Sciences, University of California Irvine, Irvine, CA, USA.
BMC Infect Dis. 2023 May 16;23(1):330. doi: 10.1186/s12879-023-08284-y.
While others have reported severe acute respiratory syndrome-related coronavirus 2(SARS-CoV-2) seroprevalence studies in health care workers (HCWs), we leverage the use of a highly sensitive coronavirus antigen microarray to identify a group of seropositive health care workers who were missed by daily symptom screening that was instituted prior to any epidemiologically significant local outbreak. Given that most health care facilities rely on daily symptom screening as the primary method to identify SARS-CoV-2 among health care workers, here, we aim to determine how demographic, occupational, and clinical variables influence SARS-CoV-2 seropositivity among health care workers.
We designed a cross-sectional survey of HCWs for SARS-CoV-2 seropositivity conducted from May 15th to June 30th 2020 at a 418-bed academic hospital in Orange County, California. From an eligible population of 5,349 HCWs, study participants were recruited in two ways: an open cohort, and a targeted cohort. The open cohort was open to anyone, whereas the targeted cohort that recruited HCWs previously screened for COVID-19 or work in high-risk units. A total of 1,557 HCWs completed the survey and provided specimens, including 1,044 in the open cohort and 513 in the targeted cohort. Demographic, occupational, and clinical variables were surveyed electronically. SARS-CoV-2 seropositivity was assessed using a coronavirus antigen microarray (CoVAM), which measures antibodies against eleven viral antigens to identify prior infection with 98% specificity and 93% sensitivity.
Among tested HCWs (n = 1,557), SARS-CoV-2 seropositivity was 10.8%, and risk factors included male gender (OR 1.48, 95% CI 1.05-2.06), exposure to COVID-19 outside of work (2.29, 1.14-4.29), working in food or environmental services (4.85, 1.51-14.85), and working in COVID-19 units (ICU: 2.28, 1.29-3.96; ward: 1.59, 1.01-2.48). Amongst 1,103 HCWs not previously screened, seropositivity was 8.0%, and additional risk factors included younger age (1.57, 1.00-2.45) and working in administration (2.69, 1.10-7.10).
SARS-CoV-2 seropositivity is significantly higher than reported case counts even among HCWs who are meticulously screened. Seropositive HCWs missed by screening were more likely to be younger, work outside direct patient care, or have exposure outside of work.
虽然其他人已经报告了针对医疗保健工作者(HCW)的严重急性呼吸系统综合症相关冠状病毒 2(SARS-CoV-2)血清流行率研究,但我们利用高度敏感的冠状病毒抗原微阵列来识别一组被日常症状筛查遗漏的血清阳性的医疗保健工作者,而这种筛查是在任何具有流行病学意义的本地疫情之前建立的。鉴于大多数医疗机构依赖日常症状筛查作为识别 SARS-CoV-2 感染 HCW 的主要方法,在这里,我们旨在确定人口统计学、职业和临床变量如何影响 HCW 的 SARS-CoV-2 血清阳性率。
我们设计了一项针对 SARS-CoV-2 血清阳性率的横断面调查,于 2020 年 5 月 15 日至 6 月 30 日在加利福尼亚州奥兰治县的一家 418 张床位的学术医院进行。在符合条件的 5349 名 HCW 中,研究参与者通过两种方式招募:开放队列和目标队列。开放队列对任何人开放,而目标队列则招募之前筛查过 COVID-19 或在高风险单位工作的 HCW。共有 1557 名 HCW 完成了调查并提供了标本,其中 1044 名来自开放队列,513 名来自目标队列。通过电子方式调查人口统计学、职业和临床变量。使用冠状病毒抗原微阵列(CoVAM)评估 SARS-CoV-2 血清阳性率,该阵列可测量针对 11 种病毒抗原的抗体,以识别 98%特异性和 93%敏感性的既往感染。
在所测试的 HCW(n=1557)中,SARS-CoV-2 血清阳性率为 10.8%,危险因素包括男性(OR 1.48,95%CI 1.05-2.06)、工作外接触 COVID-19(2.29,1.14-4.29)、从事食品或环境卫生服务(4.85,1.51-14.85)以及从事 COVID-19 病房(ICU:2.28,1.29-3.96;病房:1.59,1.01-2.48)。在 1103 名未进行过筛查的 HCW 中,血清阳性率为 8.0%,其他危险因素包括年龄较小(1.57,1.00-2.45)和从事行政工作(2.69,1.10-7.10)。
即使在经过精心筛查的 HCW 中,SARS-CoV-2 血清阳性率也明显高于报告的病例数。筛查遗漏的血清阳性 HCW 更有可能年龄较小,从事直接患者护理以外的工作,或在工作以外接触过 COVID-19。