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Wastewater threshold as an indicator of COVID-19 cases in correctional facilities for public health response: A modeling study
Water Research ( IF 11.4 ) Pub Date : 2024-06-12 , DOI: 10.1016/j.watres.2024.121934
Dan Han 1 , Pamela Linares 1 , Rochelle H Holm 2 , Kartik Chandran 3 , Ted Smith 2
Affiliation  

Although prison facilities are not fully isolated from the communities in which they are located, most of the population is confined and requires high levels of health vigilance and protection. This study aimed to examine the dynamic relationship between facility-level wastewater viral concentrations and the probability of at least one positive COVID-19 case within the facility. The study period was from January 11, 2021 to May 8, 2023. Wastewater samples were collected and analyzed for SARS-CoV-2 (N1) and pepper mild mottle virus (PMMoV) three times weekly across 14 prison facilities in Kentucky (USA). Positive clinical case reports were also provided. A hierarchical Bayesian facility-level temporal model with a latent lagged process was developed. We modeled facility-specific SARS-CoV-2 (N1) normalized by the PMMoV wastewater concentration ratio threshold associated with at least one COVID-19 clinical case at an 80 % probability. The threshold differed among facilities. Across the 14 facilities, our model demonstrates a mean capture rate of 94.95 % via the N1/PMMoV ratio threshold with . However, as the threshold was set higher, such as at ≥0.9, the mean capture rate of the model was reduced to 60 %. This robust performance underscores the effectiveness of the model for accurately detecting the presence of positive COVID-19 cases among incarcerated people. The findings of this study provide a facility-specific threshold model for public health response based on frequent wastewater surveillance.

中文翻译:


废水阈值作为惩教设施中用于公共卫生应对的 COVID-19 病例指标:一项建模研究



尽管监狱设施并未与所在社区完全隔离,但大多数人口都受到限制,需要高度的健康警惕和保护。本研究旨在研究设施级废水病毒浓度与设施内至少一例 COVID-19 阳性病例的概率之间的动态关系。研究期间为 2021 年 1 月 11 日至 2023 年 5 月 8 日。每周 3 次在美国肯塔基州 14 个监狱设施中收集废水样本并分析 SARS-CoV-2 (N1) 和胡椒轻度斑驳病毒 (PMMoV) 。还提供了积极的临床病例报告。开发了具有潜在滞后过程的分层贝叶斯设施级时间模型。我们对特定设施的 SARS-CoV-2 (N1) 进行了建模,并通过与至少一个 COVID-19 临床病例相关的 PMMoV 废水浓度比阈值进行归一化,概率为 80%。不同设施的门槛不同。在 14 个设施中,我们的模型显示,通过 N1/PMMoV 比率阈值,平均捕获率为 94.95%。然而,随着阈值设置得更高,例如≥0.9,模型的平均捕获率降低至60%。这种稳健的表现凸显了该模型在准确检测被监禁者中是否存在 COVID-19 阳性病例方面的有效性。这项研究的结果为基于频繁废水监测的公共卫生响应提供了一个特定于设施的阈值模型。
更新日期:2024-06-12
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