David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA.
Department of Environmental Sciences, College of Environmental Sciences and Forestry, State University of New York, Syracuse, NY 13210, USA.
Int J Environ Res Public Health. 2022 Apr 16;19(8):4851. doi: 10.3390/ijerph19084851.
A residential building's wastewater presents a potential non-invasive method of surveilling numerous infectious diseases, including SARS-CoV-2. We analyzed wastewater from 16 different residential locations at Syracuse University (Syracuse, NY, USA) during fall semester 2020, testing for SARS-CoV-2 RNA twice weekly and compared the presence of clinical COVID-19 cases to detection of the viral RNA in wastewater. The sensitivity of wastewater surveillance to correctly identify dormitories with a case of COVID-19 ranged from 95% (95% confidence interval [CI] = 76-100%) on the same day as the case was diagnosed to 73% (95% CI = 53-92%), with 7 days lead time of wastewater. The positive predictive value ranged from 20% (95% CI = 13-30%) on the same day as the case was diagnosed to 50% (95% CI = 40-60%) with 7 days lead time. The specificity of wastewater surveillance to correctly identify dormitories without a case of COVID-19 ranged from 60% (95% CI = 52-67%) on the day of the wastewater sample to 67% (95% CI = 58-74%) with 7 days lead time. The negative predictive value ranged from 99% (95% CI = 95-100%) on the day of the wastewater sample to 84% (95% CI = 77-91%) with 7 days lead time. Wastewater surveillance for SARS-CoV-2 at the building level is highly accurate in determining if residents have a COVID-19 infection. Particular benefit is derived from negative wastewater results that can confirm a building is COVID-19 free.
一栋住宅大楼的废水是一种潜在的非侵入性方法,可以监测多种传染病,包括 SARS-CoV-2。我们在 2020 年秋季分析了锡拉丘兹大学(美国纽约州锡拉丘兹)16 个不同住宅地点的废水,每周两次检测 SARS-CoV-2 RNA,并将临床 COVID-19 病例的出现与废水中病毒 RNA 的检测进行比较。废水监测正确识别有 COVID-19 病例的宿舍的灵敏度,从确诊病例当天的 95%(95%置信区间[CI] = 76-100%)到 7 天废水提前期的 73%(95%CI = 53-92%)不等。阳性预测值从确诊病例当天的 20%(95%CI = 13-30%)到 7 天废水提前期的 50%(95%CI = 40-60%)不等。废水监测正确识别无 COVID-19 病例的宿舍的特异性,从废水样本当天的 60%(95%CI = 52-67%)到 7 天废水提前期的 67%(95%CI = 58-74%)不等。阴性预测值从废水样本当天的 99%(95%CI = 95-100%)到 7 天废水提前期的 84%(95%CI = 77-91%)不等。在建筑物层面上,针对 SARS-CoV-2 的废水监测在确定居民是否感染 COVID-19 方面非常准确。废水检测结果为阴性可以确认建筑物没有 COVID-19 感染,这尤其有益。