Silva-Magaña Miguel Atl, Mazari-Hiriart Marisa, Noyola Adalberto, Espinosa-García Ana C, de Anda-Jáuregui Guillermo, Hernández-Lemus Enrique
Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico.
Laboratorio Nacional de Ciencias de la Sostenibilidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Front Public Health. 2025 Aug 14;13:1640581. doi: 10.3389/fpubh.2025.1640581. eCollection 2025.
Wastewater-based epidemiology (WBE) provides a non-invasive, community-level approach to monitor infectious diseases such as COVID-19. This study investigated the temporal relationship between SARS-CoV-2 RNA levels in wastewater and reported COVID-19 cases in adjacent populations in Mexico City. A total of 40 samples were collected from the Copilco neighborhood during two epidemiological waves (April-September 2021 and November 2021-February 2022). An optimized one-step RT-qPCR protocol targeting the N1 gene achieved 96.7% efficiency with a detection limit of 10 copies/μL. Spatial classification identified three proximity zones based on drainage system topology. Cross-correlation analysis between viral genome copies and confirmed case data revealed a significant temporal lag of 6-8 days. These results support the application of WBE as an early-warning tool to inform public health strategies and anticipate infection trends.
基于废水的流行病学(WBE)提供了一种非侵入性的、社区层面的方法来监测诸如COVID-19等传染病。本研究调查了墨西哥城废水中SARS-CoV-2 RNA水平与相邻人群中报告的COVID-19病例之间的时间关系。在两个疫情波期间(2021年4月至9月和2021年11月至2022年2月),从科皮尔科社区共采集了40个样本。针对N1基因的优化一步法RT-qPCR方案效率达到96.7%,检测限为10拷贝/微升。空间分类根据排水系统拓扑结构确定了三个邻近区域。病毒基因组拷贝数与确诊病例数据之间的互相关分析显示出6至8天的显著时间滞后。这些结果支持将WBE作为一种预警工具,为公共卫生策略提供信息并预测感染趋势。