Emerging investigator series: meta-analyses on SARS-CoV-2 viral RNA levels in wastewater and their correlations to epidemiological indicators
Emerging investigator series: meta-analyses on SARS-CoV-2 viral RNA levels in wastewater and their correlations to epidemiological indicators
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DOI：
10.1039/d2ew00084a
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发表时间：
2022-05-04
影响因子：
5
通讯作者：
Ling, Fangqiong
中科院分区：
文献类型：
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作者：
Mantilla-Calderon, David;Huang, Kaiyu (Kevin);Ling, Fangqiong
工作背景：基于废水的流行病学（WBE）的最新应用已经证明了其在社区层面跟踪COVID-19传播和动态的能力。尽管越来越多的研究，定量合成的SARS-CoV-2 RNA水平的废水产生的研究跨越空间和时间使用不同的方法还没有进行。目的：本研究的目的是通过研究方法中的关键协变量分层，检查废水中SARS-CoV-2 RNA水平与流行病学指标之间的相关性。此外，我们还研究了废水样品中阳性检测比例与方法学协变量之间的关系。研究方法：我们系统地搜索了2021年2月16日发表的Web of Science研究，进行了可重复的筛选，并采用混合效应模型来估计废水样品中SARS-CoV-2病毒RNA的数量及其与病例流行率、采样模式（抓取或复合采样）和分析的废水部分（即，固体、固体-上清液混合物或上清液/上清液）。结果：发现了101项研究; 20项研究（671份生物样本和1751份观察结果）在重复性筛选后保留。所有研究的平均阳性率为0.68（95%-CI，[0.52; 0.85]）。平均病毒RNA丰度为5244标记拷贝/mL（95%-CI，[0; 16 432]）。病毒RNA水平与病例流行率之间的Pearson相关系数为0.28（95%-CI，[0.01; 0.51]）（每日新发病例）或0.29（95%-CI，[-0.15; 0.73]）（累积病例）。分析的分数占阳性检测百分比变异的12.4%，其次是病例患病率（每日新发病例占9.3%，累积病例占5.9%）和采样模式（0.6%）。在阳性检测的观察结果中，分析的分数占病毒RNA水平变异的56.0%，其次是采样模式（6.9%）和病例流行率（每日新发病例为0.9%，累积病例为0.8%）。虽然采样模式和分析的分数都与SARS-CoV-2病毒RNA水平显著相关，但与分析的分数相关的阳性检测增加的幅度更大。混合效应模型将研究视为随机效应，将病例患病率视为固定效应，该模型解释了SARS-CoV-2阳性检测和病毒RNA水平变异性的90%以上。释义：SARS-CoV-2病毒RNA水平和病例流行指标之间Pearson相关系数的正汇总均值和置信区间提供了定量证据，加强了基于废水的COVID-19监测的价值。研究之间在阳性检测比例、病毒RNA水平和Pearson相关系数方面存在很大的异质性，这表明强烈需要生成数据的方法来解释交叉研究异质性和更详细的元数据报告。分析的馏分解释了较大的方差，表明样品预处理和分馏是方法标准化中需要优先考虑的方向。考虑研究水平差异的混合效应模型为综合多项研究的数据提供了一个新的视角。
Background: recent applications of wastewater-based epidemiology (WBE) have demonstrated its ability to track the spread and dynamics of COVID-19 at the community level. Despite the growing body of research, quantitative synthesis of SARS-CoV-2 RNA levels in wastewater generated from studies across space and time using diverse methods has not been performed. Objective: the objective of this study is to examine the correlations between SARS-CoV-2 RNA levels in wastewater and epidemiological indicators across studies, stratified by key covariates in study methodologies. In addition, we examined the association of proportions of positive detections in wastewater samples and methodological covariates. Methods: we systematically searched the Web of Science for studies published by February 16th, 2021, performed a reproducible screening, and employed mixed-effects models to estimate the levels of SARS-CoV-2 viral RNA quantities in wastewater samples and their correlations to the case prevalence, the sampling mode (grab or composite sampling), and the wastewater fraction analyzed (i.e., solids, solid-supernatant mixtures, or supernatants/filtrates). Results: a hundred and one studies were found; twenty studies (671 biosamples and 1751 observations) were retained following a reproducible screening. The mean positivity across all studies was 0.68 (95%-CI, [0.52; 0.85]). The mean viral RNA abundance was 5244 marker copies per mL (95%-CI, [0; 16 432]). The Pearson correlation coefficients between the viral RNA levels and case prevalence were 0.28 (95%-CI, [0.01; 0.51]) for daily new cases or 0.29 (95%-CI, [-0.15; 0.73]) for cumulative cases. The fraction analyzed accounted for 12.4% of the variability in the percentage of positive detections, followed by the case prevalence (9.3% by daily new cases and 5.9% by cumulative cases) and sampling mode (0.6%). Among observations with positive detections, the fraction analyzed accounted for 56.0% of the variability in viral RNA levels, followed by the sampling mode (6.9%) and case prevalence (0.9% by daily new cases and 0.8% by cumulative cases). While the sampling mode and fraction analyzed both significantly correlated with the SARS-CoV-2 viral RNA levels, the magnitude of the increase in positive detection associated with the fraction analyzed was larger. The mixed-effects model treating studies as random effects and case prevalence as fixed effects accounted for over 90% of the variability in SARS-CoV-2 positive detections and viral RNA levels. Interpretations: positive pooled means and confidence intervals in the Pearson correlation coefficients between the SARS-CoV-2 viral RNA levels and case prevalence indicators provide quantitative evidence that reinforces the value of wastewater-based monitoring of COVID-19. Large heterogeneities among studies in proportions of positive detections, viral RNA levels, and Pearson correlation coefficients suggest a strong demand for methods to generate data accounting for cross-study heterogeneities and more detailed metadata reporting. Large variance was explained by the fraction analyzed, suggesting sample pre-processing and fractionation as a direction that needs to be prioritized in method standardization. Mixed-effects models accounting for study level variations provide a new perspective to synthesize data from multiple studies.