Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.
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http://dx.doi.org/10.1021/acsestwater.1c00434 | DOI Listing |
BMC Public Health
January 2025
Department of Infectious Diseases, Nanning Center for Disease Control and Prevention, Nanning, 530023, China.
Introduction: COVID-19 has caused tremendous hardships and challenges around the globe. Due to the prevalence of asymptomatic and pre-symptomatic carriers, relying solely on disease testing to screen for infections is not entirely reliable, which may affect the accuracy of predictions about the pandemic trends. This study is dedicated to developing a predictive model aimed at estimating of the dynamics of COVID-19 at an early stage based on wastewater data, to assist in establishing an effective early warning system for disease control.
View Article and Find Full Text PDFFood Environ Virol
January 2025
Laboratorio de Ecología Viral y Virus Zoonóticos, Unidad Académica de Bacteriología y Virología, Instituto de Higiene, Facultad de Medicina, Universidad de la República, Av. Alfredo Navarro 3051, 11600, Montevideo, Uruguay.
Human respiratory and enteric viruses are responsible for substantial morbidity and mortality worldwide. Wastewater-based epidemiology utilizing next-generation sequencing serves as an effective tool for monitoring viral circulation dynamics at the community level. However, these complex environmental samples are often laden with other microorganisms and host genomic material, which can hinder the sensitivity of viral detection.
View Article and Find Full Text PDFJ Appl Microbiol
January 2025
Centre for Sustainable Disinfection and Sterilization, Technological University of the Shannon, Athlone Campus, N37 HD68, Ireland.
This is a timely and important review that focuses on the appropriateness of established cleaning, disinfection and sterilization methods to safely and effectively address infectious fungal drug-resistant pathogens that can potentially contaminate reusable medical devices used in healthcare environment in order to mitigate the risk of patient infection. The release of the World Health Organisation (WHO) fungal priority pathogen list (FPPL) in 2022 highlighted the public health crisis of antimicrobial resistance (AMR) in clinically relevant fungal species. Contamination of medical devices with drug-resistant fungal pathogens (including those on the FPPL) in healthcare are rare events that are more likely to occur due to cross-transmission arising from lapses in hand-hygiene practices.
View Article and Find Full Text PDFBMC Res Notes
January 2025
Institute of Environmental Science and Research Ltd, Christchurch, New Zealand.
Objective: The World Health Organization (WHO) has declared antimicrobial resistance (AMR) as one of the top threats to global public health. While AMR surveillance of human clinical isolates is well-established in many countries, the increasing threat of AMR has intensified efforts to detect antibiotic resistance genes (ARGs) accurately and sensitively in environmental samples, wastewater, animals, and food. Using five ARGs and the 16S rRNA gene, we compared quantitative PCR (qPCR) and metagenomic sequencing (MGS), two commonly used methods to uncover the wastewater resistome.
View Article and Find Full Text PDFJ R Soc Interface
January 2025
Department of Frontier Science for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Aoba 6-6-06, Aramaki, Aoba-ku, Sendai, Miyagi 980-8579, Japan.
The current situation of COVID-19 measures makes it difficult to accurately assess the prevalence of SARS-CoV-2 due to a decrease in reporting rates, leading to missed initial transmission events and subsequent outbreaks. There is growing recognition that wastewater virus data assist in estimating potential infections, including asymptomatic and unreported infections. Understanding the COVID-19 situation hidden behind the reported cases is critical for decision-making when choosing appropriate social intervention measures.
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