Siri Yadpiroon, Malla Bikash, Thao Le Thanh, Hirai Soichiro, Ruti Annisa Andarini, Rahmani Aulia Fajar, Raya Sunayana, Angga Made Sandhyana, Sthapit Niva, Shrestha Sadhana, Takeda Tomoko, Kitajima Masaaki, Dinh Nguyen Quoc, Phuc Pham Duc, Ngo Huong Thi Thuy, Haramoto Eiji
Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
Sci Total Environ. 2024 Dec 20;957:177449. doi: 10.1016/j.scitotenv.2024.177449. Epub 2024 Nov 19.
Wastewater-based epidemiology (WBE) is an effective, non-invasive method for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by tracking viral prevalence in water. This study aimed to investigate the presence of SARS-CoV-2 in surface water in Vietnam over two years. One-step quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to quantify SARS-CoV-2 and its variant-specific mutation sites (G339D/E484A) and pepper mild mottle virus (PMMoV) from a total of 315 samples (105 samples per site) to compare with reported Coronavirus disease 2019 (COVID-19) cases and environmental factors. SARS-CoV-2 was detected in 38 % (40/105), 43 % (45/105), and 39 % (41/105) of water samples from Sites A, B, and C, respectively, with concentrations of 3.0-5.6 log copies/L. PMMoV concentrations were 5.1-8.9 log copies/L. SARS-CoV-2 levels were higher in winter compared with summer. There was a strong positive association between the mutant type and SARS-CoV-2 concentrations (Spearman's rho = 0.77, p < 0.01). The mean concentrations of mutant and nonmutant types were 2.3 and 1.8 log copies/L, respectively. Peaks in SARS-CoV-2 concentrations preceded reported COVID-19 cases by 2-4 weeks, with the highest association observed at a 4-week delay (Pearson's correlation coefficient: 0.46-0.53). Environmental factors, including temperature, pH, and electrical conductivity, correlated negatively with SARS-CoV-2 (Spearman's rho = -0.21, -0.28, and -0.21, respectively, p < 0.05), whereas average rainfall, humidity, and dissolved oxygen correlated positively (Spearman's rho = 0.20, 0.27, and 0.51, respectively, p < 0.05). These correlations highlight the significance of environmental variables in understanding viral prevalence in water. Our findings confirmed the utility of WBE as an early warning system for long-term monitoring. Future research should incorporate environmental factors to improve prediction accuracy for clinical cases and other waterborne diseases.
基于废水的流行病学（WBE）是一种通过追踪水中病毒流行情况来监测严重急性呼吸综合征冠状病毒2（SARS-CoV-2）传播的有效、非侵入性方法。本研究旨在调查越南地表水在两年时间里SARS-CoV-2的存在情况。采用一步法定量逆转录聚合酶链反应（qRT-PCR）检测方法，对总共315份样本（每个采样点105份样本）中的SARS-CoV-2及其变异特异性突变位点（G339D/E484A）和辣椒轻斑驳病毒（PMMoV）进行定量，以与报告的2019冠状病毒病（COVID-19）病例及环境因素进行比较。在A、B、C三个采样点的水样中，分别有38%（40/105）、43%（45/105）和39%（41/105）检测到SARS-CoV-2，浓度为3.0 - 5.6 log拷贝/升。PMMoV浓度为5.1 - 8.9 log拷贝/升。与夏季相比，冬季SARS-CoV-2水平更高。变异类型与SARS-CoV-2浓度之间存在强正相关（斯皮尔曼等级相关系数rho = 0.77，p < 0.01）。变异型和非变异型的平均浓度分别为2.3和1.8 log拷贝/升。SARS-CoV-2浓度峰值比报告的COVID-19病例提前2 - 4周出现，在延迟4周时观察到最高相关性（皮尔逊相关系数：0.46 - 0.53）。包括温度、pH值和电导率在内的环境因素与SARS-CoV-2呈负相关（斯皮尔曼等级相关系数rho分别为 - 0.21、 - 0.28和 - 0.21，p < 0.05），而平均降雨量、湿度和溶解氧呈正相关（斯皮尔曼等级相关系数rho分别为0.20、0.27和0.51，p < 0.05）。这些相关性突出了环境变量在理解水中病毒流行情况方面的重要性。我们的研究结果证实了WBE作为长期监测预警系统的实用性。未来的研究应纳入环境因素，以提高对临床病例和其他水传播疾病的预测准确性。
