Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona, Spain.
Enteric Virus Laboratory, School of Biology, University of Barcelona, 08028, Barcelona, Spain.
Water Res. 2023 Aug 15;242:120223. doi: 10.1016/j.watres.2023.120223. Epub 2023 Jun 14.
Here we analyze SARS-CoV-2 genome copies in Catalonia's wastewater during the Omicron peak and develop a mathematical model to estimate the number of infections and the temporal relationship between reported and unreported cases. 1-liter samples from 16 wastewater treatment plants were collected and used in a compartmental epidemiological model. The average correlation between genome copies and reported cases was 0.85, with an average delay of 8.8 days. The model estimated that 53% of the population was infected, compared to the 19% reported cases. The under-reporting was highest in November and December 2021. The maximum genome copies shed in feces by an infected individual was estimated to range from 1.4×10 gc/g to 4.4×10 gc/g. Our framework demonstrates the potential of wastewater data as a leading indicator for daily new infections, particularly in contexts with low detection rates. It also serves as a complementary tool for prevalence estimation and offers a general approach for integrating wastewater data into compartmental models.
在这里，我们分析了奥密克戎高峰期间加泰罗尼亚废水中的 SARS-CoV-2 基因组拷贝，并开发了一个数学模型来估计感染人数以及报告病例和未报告病例之间的时间关系。从 16 个污水处理厂采集了 1 升样本，并用于一个隔室流行病学模型。基因组拷贝与报告病例之间的平均相关性为 0.85，平均延迟为 8.8 天。该模型估计，有 53%的人口感染，而报告的病例为 19%。2021 年 11 月和 12 月的漏报率最高。受感染个体粪便中排出的最大基因组拷贝数估计在 1.4×10 gc/g 到 4.4×10 gc/g 之间。我们的框架证明了废水数据作为每日新感染的领先指标的潜力，特别是在检测率较低的情况下。它还可以作为流行率估计的补充工具，并提供了一种将废水数据纳入隔室模型的通用方法。
