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Modeling infection from SARS-CoV-2 wastewater concentrations: promise, limitations, and future directions
Journal of Water & Health ( IF 2.3 ) Pub Date : 2022-08-01 , DOI: 10.2166/wh.2022.094
Jeffrey Soller 1 , Wiley Jennings 2 , Mary Schoen 1 , Alexandria Boehm 3 , Krista Wigginton 4 , Raul Gonzalez 5 , Katherine E Graham 3 , Graham McBride 6 , Amy Kirby 2 , Mia Mattioli 2
Affiliation  

Estimating total infection levels, including unreported and asymptomatic infections, is important for understanding community disease transmission. Wastewater can provide a pooled community sample to estimate total infections that is independent of case reporting biases toward individuals with moderate to severe symptoms and by test-seeking behavior and access. We derive three mechanistic models for estimating community infection levels from wastewater measurements based on a description of the processes that generate SARS-CoV-2 RNA signals in wastewater and accounting for the fecal strength of wastewater through endogenous microbial markers, daily flow, and per-capita wastewater generation estimates. The models are illustrated through two case studies of wastewater data collected during 2020–2021 in Virginia Beach, VA, and Santa Clara County, CA. Median simulated infection levels generally were higher than reported cases, but at times, were lower, suggesting a discrepancy between the reported cases and wastewater data, or inaccurate modeling results. Daily simulated infection estimates showed large ranges, in part due to dependence on highly variable clinical viral fecal shedding data. Overall, the wastewater-based mechanistic models are useful for normalization of wastewater measurements and for understanding wastewater-based surveillance data for public health decision-making but are currently limited by lack of robust SARS-CoV-2 fecal shedding data.



中文翻译:

模拟 SARS-CoV-2 废水浓度的感染:前景、局限性和未来方向

估计总感染水平,包括未报告和无症状感染,对于了解社区疾病传播很重要。废水可以提供汇集的社区样本来估计总感染,这与病例报告对中度至重度症状个体的偏见以及寻求测试的行为和访问无关。我们基于对废水中产生 SARS-CoV-2 RNA 信号的过程的描述,并通过内源性微生物标记、每日流量和每人均废水产生量估算。这些模型通过对 2020-2021 年在弗吉尼亚州弗吉尼亚海滩和加利福尼亚州圣克拉拉县收集的废水数据的两个案例研究进行了说明。中位数模拟感染水平通常高于报告病例,但有时较低,这表明报告病例与废水数据之间存在差异,或建模结果不准确。每日模拟感染估计显示范围很大,部分原因是依赖于高度可变的临床病毒粪便脱落数据。总体而言,基于废水的机械模型可用于废水测量的标准化和理解基于废水的监测数据以进行公共卫生决策,但目前由于缺乏可靠的 SARS-CoV-2 粪便脱落数据而受到限制。每日模拟感染估计显示范围很大,部分原因是依赖于高度可变的临床病毒粪便脱落数据。总体而言,基于废水的机械模型可用于废水测量的标准化和理解基于废水的监测数据以进行公共卫生决策,但目前由于缺乏可靠的 SARS-CoV-2 粪便脱落数据而受到限制。每日模拟感染估计显示范围很大,部分原因是依赖于高度可变的临床病毒粪便脱落数据。总体而言,基于废水的机械模型可用于废水测量的标准化和理解基于废水的监测数据以进行公共卫生决策,但目前由于缺乏可靠的 SARS-CoV-2 粪便脱落数据而受到限制。

更新日期:2022-08-01
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