A radical polymer membrane for simultaneous degradation of organic pollutants and water filtration.

Integrating reactive radicals into membranes that resemble biological membranes has always been a pursuit for simultaneous organics degradation and water filtration. In this research, we discovered that a radical polymer (RP) that can directly trigger the oxidative degradation of sulfamethozaxole (SMX). Mechanistic studies by experiment and density functional theory simulations revealed that peroxyl radicals are the reactive species, and the radicals could be regenerated in the presence of O2. Furthermore, an interpenetrating RP network membrane consisting of polyvinyl alcohol and the RP was fabricated to demonstrate the simultaneous filtration of large molecules in the model wastewater stream and the degradation of ~ 85% of SMX with a steady permeation flux. This study offers valuable insights into the mechanism of RP-triggered advanced oxidation processes and provides an energy-efficient solution for the degradation of organic compounds and water filtration in wastewater treatment.

Selective adsorption of high ionization potential value organic pollutants in wastewater.

It is imperative to devise effective removal strategies for high ionization potential (IP) organic pollutants in wastewater as their reduced electron-donating capacity challenges the efficiency of advanced oxidation systems in degradation. Against this backdrop, leveraging the metal-based carbon material structure meticulously, we employed metal-pyridine-N (M-N-C, M=Fe, Co, and Ni) as the electron transfer bridge. This distinctive design facilitated the ordered transfer of electrons from the adsorbent surface to the surface of high IP value pollutants, acting as a "supplement" to compensate for their deficient electron-donating capability, thereby culminating in the selective adsorption of these pollutants. Furthermore, this adsorbent also demonstrated effective removal of trace emerging contaminants (2 mg/L), displayed robust resistance to various salts, exhibited reusability, and maintained stability. These findings carry substantial implications for future carbon-based material design, offering a pathway toward exceptional adsorption performance in treating water pollution.

Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty.

Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

Efficient hydrogen production from wastewater remediation by piezoelectricity coupling advanced oxidation processes.

Efficient H2 harvesting from wastewater instead of pure water can minimize fresh water consumption, which is expected to solve the problem of water shortage in H2 production process and contribute to carbon neutrality in the environmental remediation, but the inevitable electron depletion caused by electron-consuming pollutants will result in an exhausted H2 evolution reaction (HER) performance. In this paper, by coupling piezocatalysis and advanced oxidation processes (AOPs) by a MoS2/Fe0/peroxymonosulfate (PMS) ternary system, extensive types of wastewater achieved considerable H2 generation, which exceeded the yield in pure water with synchronous advanced degradation of organic pollutants. In addition, profiting from the crucial bridging role of PMS, the H2 yield in nitrobenzene wastewater after the introduction of PMS-based AOPs increased 3.37-fold from 267.7 µmol·g-1·h-1 to 901.0 µmol·g-1·h-1 because the presence of PMS both thermodynamically benefited MoS2 piezocatalytic H2 evolution and eliminated the electron depletion caused by organic pollutants. By this way, the original repressed H2 evolution performance in substrate of wastewater not only was regained but even showed a significant enhancement than that in pure water (505.7 µmol·g-1·h-1). Additionally, the cyclonic piezoelectric reactor was preliminarily designed for future industrialization. This strategy provided a valuable path for the recycling of actual wastewater by fuel production and synchronous advanced treatment.

Superexchange-induced Pt-O-Ti3+ site on single photocatalyst for efficient H2 production with organics degradation in wastewater.

Efficient photocatalytic H2 production from wastewater instead of pure water is a dual solution to the environmental and energy crisis, but due to the rapid recombination of photoinduced charge in the photocatalyst and inevitable electron depletion caused by organic pollutants, a significant challenge of dual-functional photocatalysis (simultaneous oxidative and reductive reactions) in single catalyst is designing spatial separation path for photogenerated charges at atomic level. Here, we designed a Pt-doped BaTiO3 single catalyst with oxygen vacancies (BTPOv) that features Pt-O-Ti3+ short charge separation site, which enables excellent H2 production performance (1519 µmol·g-1·h-1) while oxidizing moxifloxacin (k = 0.048 min-1), almost 43 and 98 times than that of pristine BaTiO3 (35 µmol·g-1·h-1 and k = 0.00049 min-1). The efficient charge separation path is demonstrated that the oxygen vacancies extract photoinduced charge from photocatalyst to catalytic surface, and the adjacent Ti3+ defects allow rapid migration of electrons to Pt atoms through the superexchange effect for H* adsorption and reduction, while the holes will be confined in Ti3+ defects for oxidation of moxifloxacin. Impressively, the BTPOv shows an exceptional atomic economy and potential for practical applications, a best H2 production TOF (370.4 h-1) among the recent reported dual-functional photocatalysts and exhibiting excellent H2 production activity in multiple types of wastewaters.

Separating signal from noise in wastewater data: An algorithm to identify community-level COVID-19 surges in real time.

Wastewater monitoring has provided health officials with early warnings for new COVID-19 outbreaks, but to date, no approach has been validated to distinguish signal (sustained surges) from noise (background variability) in wastewater data to alert officials to the need for heightened public health response. We analyzed 62 wk of data from 19 sites participating in the North Carolina Wastewater Monitoring Network to characterize wastewater metrics around the Delta and Omicron surges. We found that wastewater data identified outbreaks 4 to 5 d before case data (reported on the earlier of the symptom start date or test collection date), on average. At most sites, correlations between wastewater and case data were similar regardless of how wastewater concentrations were normalized and whether calculated with county-level or sewershed-level cases, suggesting that officials may not need to geospatially align case data with sewershed boundaries to gain insights into disease transmission. Although wastewater trend lines captured clear differences in the Delta versus Omicron surge trajectories, no single wastewater metric (detectability, percent change, or flow-population normalized viral concentrations) reliably signaled when these surges started. After iteratively examining different combinations of these three metrics, we developed the Covid-SURGE (Signaling Unprecedented Rises in Groupwide Exposure) algorithm, which identifies unprecedented signals in the wastewater data. With a true positive rate of 82%, a false positive rate of 7%, and strong performance during both surges and in small and large sites, our algorithm provides public health officials with an automated way to flag community-level COVID-19 surges in real time.

Sulfion oxidation assisting self-powered hydrogen production system based on efficient catalysts from spent lithium-ion batteries.

Converting spent lithium-ion batteries (LIBs) and industrial wastewater into high-value-added substances by advanced electrocatalytic technology is important for sustainable energy development and environmental protection. Here, we propose a self-powered system using a home-made sulfide fuel cell (SFC) to power a two-electrode electrocatalytic sulfion oxidation reaction (SOR)-assisted hydrogen (H2) production electrolyzer (ESHPE), in which the sulfion-containing wastewater is used as the liquid fuel to produce clean water, sulfur, and hydrogen. The catalysts for the self-powered system are mainly prepared from spent LIBs to reduce the cost, such as the bifunctional Co9S8 catalyst was prepared from spent LiCoO2 for SOR and hydrogen evolution reaction (HER). The Fe-N-P codoped coral-like carbon nanotube arrays encapsulated Fe2P (C-ZIF/sLFP) catalyst was prepared from spent LiFePO4 for oxygen reduction reaction. The Co9S8 catalyst shows excellent catalytic activities in both SOR and HER, evidenced by the low cell voltage of 0.426 V at 20 mA cm-2 in ESHPE. The SFC with Co9S8 as anode and C-ZIF/sLFP as cathode exhibits an open-circuit voltage of 0.69 V and long discharge stability for 300 h at 20 mA cm-2. By integrating the SFC and ESHPE, the self-powered system delivers an impressive hydrogen production rate of 0.44 mL cm-2 min-1. This work constructs a self-powered system with high-performance catalysts prepared from spent LIBs to transform sulfion-containing wastewater into purified water and prepare hydrogen, which is promising to achieve high economic efficiency, environmental remediation, and sustainable development.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond.

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets.

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

EU surveys insights: analytical tools, future directions, and the essential requirement for reference materials in wastewater monitoring of SARS-CoV-2, antimicrobial resistance and beyond.

BACKGROUND: Wastewater surveillance (WWS) acts as a vigilant sentinel system for communities, analysing sewage to protect public health by detecting outbreaks and monitoring trends in pathogens and contaminants. To achieve a thorough comprehension of present and upcoming practices and to identify challenges and opportunities for standardisation and improvement in WWS methodologies, two EU surveys were conducted targeting over 750 WWS laboratories across Europe and other regions. The first survey explored a diverse range of activities currently undertaken or planned by laboratories. The second survey specifically targeted methods and quality controls utilised for SARS-CoV-2 surveillance. RESULTS: The findings of the two surveys provide a comprehensive insight into the procedures and methodologies applied in WWS. In Europe, WWS primarily focuses on SARS-CoV-2 with 99% of the survey participants dedicated to this virus. However, the responses highlighted a lack of standardisation in the methodologies employed for monitoring SARS-CoV-2. The surveillance of other pathogens, including antimicrobial resistance, is currently fragmented and conducted by only a limited number of laboratories. Notably, these activities are anticipated to expand in the future. Survey replies emphasise the collective recognition of the need to enhance the accuracy of results in WWS practices, reflecting a shared commitment to advancing precision and effectiveness in WWS methodologies. CONCLUSIONS: These surveys identified a lack of standardised common procedures in WWS practices and the need for quality standards and reference materials to enhance the accuracy and reliability of WWS methods in the future. In addition, it is important to broaden surveillance efforts beyond SARS-CoV-2 to include other emerging pathogens and antimicrobial resistance to ensure a comprehensive approach to protecting public health.

Simultaneous detection of influenza A, B and respiratory syncytial virus in wastewater samples by one-step multiplex RT-ddPCR assay.

BACKGROUND: After the occurrence of the COVID-19 pandemic, detection of other disseminated respiratory viruses using highly sensitive molecular methods was declared essential for monitoring the spread of health-threatening viruses in communities. The development of multiplex molecular assays are essential for the simultaneous detection of such viruses even at low concentrations. In the present study, a highly sensitive and specific multiplex one-step droplet digital PCR (RT-ddPCR) assay was developed for the simultaneous detection and absolute quantification of influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV), and beta-2-microglobulin transcript as an endogenous internal control (IC B2M). RESULTS: The assay was first evaluated for analytical sensitivity and specificity, linearity, reproducibility, and recovery rates with excellent performance characteristics and then applied to 37 wastewater samples previously evaluated with commercially available and in-house quantitative real-time reverse transcription PCR (RT-qPCR) assays. IAV was detected in 16/37 (43%), IBV in 19/37 (51%), and RSV in 10/37 (27%) of the wastewater samples. Direct comparison of the developed assay with real-time RT-qPCR assays showed statistically significant high agreement in the detection of IAV (kappa Cohen's correlation coefficient: 0.834, p = 0.001) and RSV (kappa: 0.773, p = 0.001) viruses between the two assays, while the results for the detection of IBV (kappa: 0.355, p = 0.27) showed good agreement without statistical significance. CONCLUSIONS: Overall, the developed one-step multiplex ddPCR assay is cost-effective, highly sensitive and specific, and can simultaneously detect three common respiratory viruses in the complex matrix of wastewater samples even at low concentrations. Due to its high sensitivity and resistance to PCR inhibitors, the developed assay could be further used as an early warning system for wastewater monitoring.

Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals.

BACKGROUND: Human viruses released into the environment can be detected and characterized in wastewater. The study of wastewater virome offers a consolidated perspective on the circulation of viruses within a population. Because the occurrence and severity of viral infections can vary across a person's lifetime, studying the virome in wastewater samples contributed by various demographic segments can provide valuable insights into the prevalence of viral infections within these segments. In our study, targeted enrichment sequencing was employed to characterize the human virome in wastewater at a building-level scale. This was accomplished through passive sampling of wastewater in schools, university settings, and nursing homes in two cities in Catalonia. Additionally, sewage from a large urban wastewater treatment plant was analysed to serve as a reference for examining the collective excreted human virome. RESULTS: The virome obtained from influent wastewater treatment plant samples showcased the combined viral presence from individuals of varying ages, with astroviruses and human bocaviruses being the most prevalent, followed by human adenoviruses, polyomaviruses, and papillomaviruses. Significant variations in the viral profiles were observed among the different types of buildings studied. Mamastrovirus 1 was predominant in school samples, salivirus and human polyomaviruses JC and BK in the university settings while nursing homes showed a more balanced distribution of viral families presenting papillomavirus and picornaviruses and, interestingly, some viruses linked to immunosuppression. CONCLUSIONS: This study shows the utility of building-level wastewater-based epidemiology as an effective tool for monitoring the presence of viruses circulating within specific age groups. It provides valuable insights for public health monitoring and epidemiological studies.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan.

BACKGROUND: Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing. RESULTS: During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified. CONCLUSIONS: The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

Pharmaceutical pollution of the world's rivers.

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.

Preparing for Mpox Resurgence: Surveillance Lessons From Outbreaks in Toronto, Canada.

BACKGROUND: With many global jurisdictions, Toronto, Canada, experienced an mpox outbreak in spring/summer 2022. Cases declined following implementation of a large vaccination campaign. A surge in early 2023 led to speculation that asymptomatic and/or undetected local transmission was occurring in the city. METHODS: Mpox cases and positive laboratory results are reported to Toronto Public Health. Epidemic curves and descriptive risk factor summaries for the 2022 and 2023 outbreaks were generated. First- and second-dose vaccination was monitored. Mpox virus wastewater surveillance and whole genome sequencing were conducted to generate hypotheses about the source of the 2023 resurgence. RESULTS: An overall 515 cases were reported in spring/summer 2022 and 17 in the 2022-2023 resurgence. Wastewater data correlated with the timing of cases. Whole genome sequencing showed that 2022-2023 cases were distinct from 2022 cases and closer to sequences from another country, suggesting a new importation as a source. At the start of the resurgence, approximately 16% of first-dose vaccine recipients had completed their second dose. CONCLUSIONS: This investigation demonstrates the importance of ongoing surveillance and preparedness for mpox outbreaks. Undetected local transmission was not a likely source of the 2022-2023 resurgence. Ongoing preexposure vaccine promotion remains important to mitigate disease burden.

Genomic Analysis and Surveillance of Respiratory Syncytial Virus (RSV) Using Wastewater-Based Epidemiology (WBE).

Respiratory syncytial virus (RSV) causes severe infections in infants, immunocompromised or elderly individuals resulting in annual epidemics of respiratory disease. Currently, limited clinical surveillance and the lack of predictable seasonal dynamics limits the public health response. Wastewater-based epidemiology (WBE) has recently been used globally as a key metric in determining prevalence of SARS-CoV-2 in the community but its application to other respiratory viruses is limited. In this study, we present an integrated genomic WBE approach, applying RT-qPCR and partial G-gene sequencing to track RSV levels and variants in the community. We report increasing detection of RSV in wastewater concomitant with increasing numbers of positive clinical cases. Analysis of wastewater-derived RSV sequences permitted identification of distinct circulating lineages within and between seasons. Altogether, our genomic WBE platform has the potential to complement ongoing global surveillance and aid the management of RSV by informing the timely deployment of pharmaceutical and non-pharmaceutical interventions.

Environmental Surveillance for Salmonella Typhi and its Association With Typhoid Fever Incidence in India and Malawi.

BACKGROUND: Environmental surveillance (ES) for Salmonella Typhi potentially offers a low-cost tool to identify communities with a high burden of typhoid fever. METHODS: We developed standardized protocols for typhoid ES, including sampling site selection, validation, characterization; grab or trap sample collection, concentration; and quantitative PCR targeting Salmonella genes (ttr, staG, and tviB) and a marker of human fecal contamination (HF183). ES was implemented over 12 months in a historically high typhoid fever incidence setting (Vellore, India) and a lower incidence setting (Blantyre, Malawi) during 2021-2022. RESULTS: S. Typhi prevalence in ES samples was higher in Vellore compared with Blantyre; 39/520 (7.5%; 95% confidence interval [CI], 4.4%-12.4%) vs 11/533 (2.1%; 95% CI, 1.1%-4.0%) in grab and 79/517 (15.3%; 95% CI, 9.8%-23.0%) vs 23/594 (3.9%; 95% CI, 1.9%-7.9%) in trap samples. Detection was clustered by ES site and correlated with site catchment population in Vellore but not Blantyre. Incidence of culture-confirmed typhoid in local hospitals was low during the study and zero some months in Vellore despite S. Typhi detection in ES. CONCLUSIONS: ES describes the prevalence and distribution of S. Typhi even in the absence of typhoid cases and could inform vaccine introduction. Expanded implementation and comparison with clinical and serological surveillance will further establish its public health utility.

Chronic shedding of a SARS-CoV-2 Alpha variant in wastewater.

BACKGROUND: Central Michigan University (CMU) participated in a state-wide SARS-CoV-2 wastewater monitoring program since 2021. Wastewater samples were collected from on-campus sites and nine off-campus wastewater treatment plants servicing small metropolitan and rural communities. SARS-CoV-2 genome copies were quantified using droplet digital PCR and results were reported to the health department. RESULTS: One rural, off-campus site consistently produced higher concentrations of SARS-CoV-2 genome copies. Samples from this site were sequenced and contained predominately a derivative of Alpha variant lineage B.1.1.7, detected from fall 2021 through summer 2023. Mutational analysis of reconstructed genes revealed divergence from the Alpha variant lineage sequence over time, including numerous mutations  in the Spike RBD and NTD. CONCLUSIONS: We discuss the possibility that a chronic SARS-CoV-2 infection accumulated adaptive mutations that promoted long-term infection. This study reveals that small wastewater treatment plants can enhance resolution of rare events and facilitate reconstruction of viral genomes due to the relative lack of contaminating sequences.

Correlation of SARS-CoV-2 in Wastewater and Individual Testing Results in a Jail, Atlanta, Georgia, USA.

Institution-level wastewater-based surveillance was implemented during the COVID-19 pandemic, including in carceral facilities. We examined the relationship between COVID-19 diagnostic test results of residents in a jail in Atlanta, Georgia, USA (average population ≈2,700), and quantitative reverse transcription PCR signal for SARS-CoV-2 in weekly wastewater samples collected during October 2021‒May 2022. The jail offered residents rapid antigen testing at entry and periodic mass screenings by reverse transcription PCR of self-collected nasal swab specimens. We aggregated individual test data, calculated the Spearman correlation coefficient, and performed logistic regression to examine the relationship between strength of SARS-CoV-2 PCR signal (cycle threshold value) in wastewater and percentage of jail population that tested positive for COVID-19. Of 13,745 nasal specimens collected, 3.9% were COVID-positive (range 0%-29.5% per week). We observed a strong inverse correlation between diagnostic test positivity and cycle threshold value (r = -0.67; p<0.01). Wastewater-based surveillance represents an effective strategy for jailwide surveillance of COVID-19.

Wastewater Surveillance for Identifying SARS-CoV-2 Infections in Long-Term Care Facilities, Kentucky, USA, 2021-2022.

Persons living in long-term care facilities (LTCFs) were disproportionately affected by COVID-19. We used wastewater surveillance to detect SARS-CoV-2 infection in this setting by collecting and testing 24-hour composite wastewater samples 2-4 times weekly at 6 LTCFs in Kentucky, USA, during March 2021-February 2022. The LTCFs routinely tested staff and symptomatic and exposed residents for SARS-CoV-2 using rapid antigen tests. Of 780 wastewater samples analyzed, 22% (n = 173) had detectable SARS-CoV-2 RNA. The LTCFs reported 161 positive (of 16,905) SARS-CoV-2 clinical tests. The wastewater SARS-CoV-2 signal showed variable correlation with clinical test data; we observed the strongest correlations in the LTCFs with the most positive clinical tests (n = 45 and n = 58). Wastewater surveillance was 48% sensitive and 80% specific in identifying SARS-CoV-2 infections found on clinical testing, which was limited by frequency, coverage, and rapid antigen test performance.