亚利桑那州马里科帕县基于病例的 SARS-CoV-2 抗体血清阳性率准确性。
Accuracy of Case-Based Seroprevalence of SARS-CoV-2 Antibodies in Maricopa County, Arizona.
机构信息
Megan Jehn and Camila Tompkins are with the School of Human Evolution and Social Change, Arizona State University (ASU), Tempe. Urvashi Pandit, Rebecca Sunenshine, and Jessica White are with the Maricopa County Department of Public Health, Phoenix, AZ. Susanna Sabin is with the Center for Evolution and Medicine, ASU. Erin Kaleta is with the Department of Laboratory Medicine and Pathology, Mayo Clinic, Scottsdale, AZ. Ariella P. Dale is with the Centers for Disease Control and Prevention (CDC) assigned to Maricopa County Department of Public Health. Heather M. Ross, Katherine Kenny, Heidi Sanborn, and Natalie Heywood are with the Edson College of Nursing and Health Innovation, ASU. J. Mac McCullough is with the College of Health Solutions, ASU. Susan Pepin is with Knowledge Enterprise, ASU. Amy H. Schnall is with the National Center for Environmental Health, CDC, Atlanta, GA. Timothy Lant is with the Biodesign Institute, ASU.
出版信息
Am J Public Health. 2022 Jan;112(1):38-42. doi: 10.2105/AJPH.2021.306568.
We conducted a community seroprevalence survey in Arizona, from September 12 to October 1, 2020, to determine the presence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used the seroprevalence estimate to predict SARS-CoV-2 infections in the jurisdiction by applying the adjusted seroprevalence to the county's population. The estimated community seroprevalence of SARS-CoV-2 infections was 4.3 times greater (95% confidence interval = 2.2, 7.5) than the number of reported cases. Field surveys with representative sampling provide data that may help fill in gaps in traditional public health reporting. (. 2022;112(1):38-42. https://doi.org/10.2105/AJPH.2021.306568).
我们于 2020 年 9 月 12 日至 10 月 1 日在亚利桑那州进行了社区血清流行率调查，以确定是否存在针对严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）的抗体。我们使用血清流行率估计值通过将调整后的血清流行率应用于该县的人口来预测该管辖区的 SARS-CoV-2 感染。估计的 SARS-CoV-2 感染社区血清流行率比报告的病例数高 4.3 倍（95%置信区间= 2.2，7.5）。具有代表性抽样的实地调查提供的数据可能有助于填补传统公共卫生报告中的空白。（. 2022；112（1）：38-42。https://doi.org/10.2105/AJPH.2021.306568）。
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