PDF(Pubmed)
Abstract：
Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.
摘要：
废水流行病学（WBE）已成为一种有效的环境监测工具，用于预测具有集中式污水基础设施的高收入国家（HIC）的严重急性呼吸道综合症冠状病毒2（SARS-CoV-2）疾病暴发。然而,很少有研究将WBE与流行病模型一起应用于低资源环境中SARS-CoV-2的流行程度。本研究旨在探讨从那格浦尔地区的农村和城市集水区收集未经处理的废水样品的可行性，使用实时qPCR检测和定量SARS-CoV-2，为了比较病毒载量的地理差异，并将废水数据整合到改良的易感暴露感染确认阳性回收（SEIPR）模型中。在分析了983份SARS-CoV-2RNA的废水样本中，我们检测到明显更高的样本阳性率，43.7%(95%置信区间(CI)40.1，47.4)和30.4%(95%CI24.66，36.66)，与农村样本相比，城市的病毒载量更高，分别。基本生殖数,R0，与人口密度呈正相关，与湿度呈负相关，下水道中降雨和废物稀释的代表。SEIPR模型估计2019年未报告冠状病毒病(COVID-19)病例在浪潮开始时的比率是确诊病例的13.97[95%CI(10.17,17.0)]倍，代表案件和医疗资源负担的实质性差异。废水监测可能被证明是一种更可靠的方法，可以为当局未来浪潮中COVID-19病例的激增做好准备。
