Research Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand.
Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand.
Int J Environ Res Public Health. 2022 Jun 24;19(13):7783. doi: 10.3390/ijerph19137783.
The SARS-CoV-2 virus, which is driving the current COVID-19 epidemic, has been detected in wastewater and is being utilized as a surveillance tool to establish an early warning system to aid in the management and prevention of future pandemics. qPCR is the method usually used to detect SARS-CoV-2 in wastewater. There has been no study using an immunoassay that is less laboratory-intensive than qPCR with a shorter turnaround time. Therefore, we aimed to evaluate the performance of an automated chemiluminescence enzyme immunoassay (CLEIA) for SARS-CoV-2 antigen in wastewater. The CLEIA assay achieved 100% sensitivity and 66.7% specificity in a field-captured wastewater sample compared to the gold standard RT-qPCR. Our early findings suggest that the SARS-CoV-2 antigen can be identified in wastewater samples using an automated CLEIA, reducing the turnaround time and improving the performance of SARS-CoV-2 wastewater monitoring during the pandemic.
正在引发当前 COVID-19 疫情的 SARS-CoV-2 病毒已在废水中被检出,并被用作监测工具,以建立早期预警系统,帮助管理和预防未来的大流行。qPCR 通常用于检测废水中的 SARS-CoV-2。目前还没有研究使用比 qPCR 实验室工作量更小、周转时间更短的免疫测定法。因此,我们旨在评估用于废水检测的 SARS-CoV-2 抗原自动化化学发光酶免疫测定法 (CLEIA) 的性能。与金标准 RT-qPCR 相比,该 CLEIA 检测法在野外采集的废水样本中实现了 100%的灵敏度和 66.7%的特异性。我们的初步发现表明,使用自动化 CLEIA 可以在废水样本中识别 SARS-CoV-2 抗原,从而缩短周转时间,并提高大流行期间 SARS-CoV-2 废水监测的性能。