Strike William, Rockward Alexus, Mijatovic Blazan, Noble Ann, Olsson Cullen, Torabi Soroosh, Banadaki Mohammad Dehghan, Adatorwovor Reuben, Keck James, Berry Scott
Department of Biomedical Engineering, University of Kentucky, 522 Robotics and Manufacturing Building, Lexington, KY 40506-0108, United States.
Department of Mechanical and Aerospace Engineering, University of Kentucky, 151 Ralph G. Anderson Building, Lexington, KY 40506-0503, United States.
Environ Adv. 2025 Jul;20. doi: 10.1016/j.envadv.2025.100635. Epub 2025 Apr 19.
Wastewater-based epidemiology (WBE) is a promising tool for improving health outcomes through early detection and cost-effective pathogen surveillance. Long-term care facilities (LTCFs) serve and employ vulnerable populations that may particularly benefit from the use of WBE, but financial and technical costs associated with standard sampling methods limit the feasibility of WBE in the LTCF setting. In this work, we used passive sampling to simplify the wastewater analysis process and compared its performance to the standard composite sampling method. Moore swabs and automatic composite samplers were used concurrently to sample wastewater from two LTCFs, and samples were analyzed for SARS-CoV-2 concentration. Passive sampling relies on an unknown volume of wastewater flowing through a cotton material, which complicates back calculations of pathogen concentration. We chose to calculate analyte concentrations based on the squeezed eluent from the cotton swab, which is practical for temporal analysis. Across all samples, passive and composite sampling performed similarly for SARS-CoV-2 detection and mean concentration. However, we observed a sensitivity advantage at low SARS-CoV-2 concentrations (<180 gc/mL) when using passive sampling. Furthermore, SARS-CoV-2 wastewater concentrations obtained via passive sampling correlated with the reported clinical cases, with wastewater concentration leading reported clinical cases by an average of 4 days. Passive and composite sampling were also performed at a wastewater treatment plant (WWTP) to examine the effects of facility type on sampling performance. To our knowledge, this is the first work performing a comparative analysis at both facility- and community-scale locations. Passive sampling yielded significantly higher SARS-CoV-2 and fecal load biomarkers than composite sampling at WWTPs, illustrating an important difference between LTCF samples and WWTP samples.
基于废水的流行病学（WBE）是一种很有前景的工具，可通过早期检测和具有成本效益的病原体监测来改善健康状况。长期护理机构（LTCF）服务并雇佣了弱势群体，这些群体可能特别受益于WBE的使用，但与标准采样方法相关的财务和技术成本限制了WBE在LTCF环境中的可行性。在这项工作中，我们使用被动采样来简化废水分析过程，并将其性能与标准混合采样方法进行比较。同时使用摩尔拭子和自动混合采样器对两家LTCF的废水进行采样，并对样本进行SARS-CoV-2浓度分析。被动采样依赖于流经棉质材料的未知体积的废水，这使得病原体浓度的反向计算变得复杂。我们选择根据从棉签中挤出的洗脱液来计算分析物浓度，这对于时间分析来说是可行的。在所有样本中，被动采样和混合采样在SARS-CoV-2检测和平均浓度方面表现相似。然而，我们观察到在使用被动采样时，在低SARS-CoV-2浓度（<180 gc/mL）下具有灵敏度优势。此外，通过被动采样获得的SARS-CoV-2废水浓度与报告的临床病例相关，废水浓度平均比报告的临床病例提前4天。还在污水处理厂（WWTP）进行了被动采样和混合采样，以检查设施类型对采样性能的影响。据我们所知，这是第一项在设施和社区规模地点进行比较分析的工作。在污水处理厂，被动采样产生的SARS-CoV-2和粪便负荷生物标志物明显高于混合采样，这说明了LTCF样本和污水处理厂样本之间的重要差异。
