Tracking infectious diseases at the community level is challenging due to asymptomatic infections and the logistical complexities of mass surveillance. Wastewater surveillance has emerged as a valuable tool for monitoring infectious disease agents including SARS-CoV-2 and Mpox virus. However, detecting the Mpox virus in wastewater is particularly challenging due to its relatively low prevalence in the community. In this study, we aim to characterize three molecular assays for detecting and tracking the Mpox virus in wastewater from El Paso, Texas, during February and March 2023. In this study, a combined approach utilizing three real-time PCR assays targeting the C22L, F3L, and F8L genes and sequencing was employed to detect and track the Mpox virus in wastewater samples. The samples were collected from four sewersheds in the City of El Paso, Texas, during February and March 2023. Wastewater data was compared with reported clinical case data in the city. Mpox virus DNA was detected in wastewater from all the four sewersheds, whereas only one Mpox case was reported during the sampling period. Positive signals were still observed in multiple sewersheds after the Mpox case was identified. Higher viral concentrations were found in the pellet than in the supernatant of wastewater. Notably, an increasing trend in viral concentration was observed approximately 1–2 weeks before the reporting of the Mpox case. Further sequencing and epidemiological analysis provided supporting evidence for unreported Mpox infections in the city. Our analysis suggests that the Mpox cases in the community is underestimated. The findings emphasize the value of wastewater surveillance as a public health tool for monitoring infectious diseases even in low-prevalence areas, and the need for heightened vigilance to mitigate the spread of Mpox disease for safeguarding global health. Center of Infectious Diseases at 10.13039/100012615 UTHealth , the 10.13039/100007130 University of Texas System , and the Texas Epidemic Public Health Institute. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of these funding organizations.

Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study aimed to monitor the SARS-CoV-2 variant community dynamics and evolution using receptor-binding domain (RBD) amplicon sequencing of wastewater samples. We sequenced wastewater from El Paso, Texas, over 17 months, compared the sequencing data with clinical genome data, and performed biodiversity analysis to reveal SARS-CoV-2 variant dynamics and evolution. We identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Comparison with clinical genome sequencing data revealed earlier detection of variants and identification of unreported outbreaks. Our results also showed strong consistency with clinical data for dominant variants at the local, state, and national levels. Alpha diversity analyses revealed significant seasonal variations, with the highest diversity observed in winter. By segmenting the outbreak into lag, growth, stationary, and decline phases, we found higher variant diversity during the lag phase, likely due to lower inter-variant competition preceding outbreak growth. Our findings underscore the importance of low transmission periods in facilitating rapid mutation and variant evolution. Our approach, integrating RBD amplicon sequencing with wastewater surveillance, demonstrates effectiveness in tracking viral evolution and understanding variant emergence, thus enhancing public health preparedness.

Quantitative microbial risk assessment (QMRA) can be used to evaluate health risks associated with recreational beach use. This study developed a site-specific risk assessment using a novel approach that combined quantitative PCR-based measurement of microbial source tracking (MST) genetic markers (human, dog, and gull fecal bacteria) with a QMRA analysis of potential pathogen risk. Water samples (n = 24) from two recreational beaches were collected and analyzed for MST markers as part of a broader Beach Exposure And Child Health Study that examined child behavior interactions with the beach environment. We report here the measurements of fecal bacteria MST markers in the environmental DNA extracts of those samples and a QMRA analysis of potential health risks utilizing the results from the MST measurements in the water samples. Human-specific Bacteroides was enumerated by the HF183 Taqman qPCR assay, gull-specific Catellicoccus was enumerated by the Gull2 qPCR assay, and dog-specific Bacteroides was enumerated by the DogBact qPCR assay. Derived reference pathogen doses, calculated from the MST marker concentrations detected in recreational waters, were used to estimate the risk of gastrointestinal illness for both children and adults. Dose–response equations were used to estimate the probability of the risk of infection (P_inf) per a swimming exposure event. Based on the QMRA simulations presented in this study, the GI risk from swimming or playing in water containing a mixture of human and non-human fecal sources appear to be primarily driven by the human fecal source. However, the estimated median GI health risk for both beaches never exceeded the U.S. EPA risk threshold of 32 illnesses per 1,000 recreation events. Our research suggests that utilizing QMRA together with MST can further extend our understanding of potential recreational bather risk by identifying the source contributing the greatest risk in a particular location, therefore informing beach management responses and decision-making.

In the 5 years since the emergence of the COVID-19 pandemic, the field of wastewater-based epidemiology (WBE) has dramatically expanded with programs implemented across the globe to monitor for SARS-CoV-2 and other viruses of public health concern. However, the best way to use wastewater surveillance data and inform local communities of the utility of wastewater science remains limited and sporadically discussed. Specifically, there is vague guidance regarding interpreting varying levels of viral loads in wastewater for public health significance. While collaborative efforts are key to implementing these community-specific wastewater surveillance programs, effectively using the data for public health decision-making still needs significant refinement. Aligned with recent calls for advancing the science of wastewater surveillance, the experiences described in this article examine the critical need to advance other aspects of WBE programs, including communication, ethics, and decision-making.

The border city of El Paso, Texas, and its water utility, El Paso Water, initiated a SARS-CoV-2 wastewater monitoring program to assess virus trends and the appropriateness of a wastewater monitoring program for the community. Nearly weekly sample collection at four wastewater treatment facilities (WWTFs), serving distinct regions of the city, was analyzed for SARS-CoV-2 genes using the CDC 2019-Novel coronavirus Real-Time RT-PCR diagnostic panel. Virus concentrations ranged from 86.7 to 268,000 gc/L, varying across time and at each WWTF. The lag time between virus concentrations in wastewater and reported COVID-19 case rates (per 100,00 population) ranged from 4–24 days for the four WWTFs, with the strongest trend occurring from November 2021 - June 2022. This study is an assessment of the utility of a geographically refined SARS-CoV-2 wastewater monitoring program to supplement public health efforts that will manage the virus as it becomes endemic in El Paso.