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• Viral stability in archived wastewater samples stored at −80 °C were investigated. • Minimal loss of viral RNA/DNA was noted in nucleic acid extracts stored for 8–24 months. • Extensive viral decay was found when raw wastewater samples were stored and reprocessed. • After processing, archived samples may be stored at −80 °C for at least 2 years. Wastewater-based monitoring has been widely implemented worldwide for the tracking of SARS-CoV-2 outbreaks and other viral diseases. In many surveillance programmes, unprocessed and processed wastewater samples are often frozen and stored for long periods of time in case the identification and tracing of an emerging health threat becomes necessary. However, extensive sample bioarchives may be difficult to maintain due to limitations in ultra-freezer capacity and associated cost. Furthermore, the stability of viruses in such samples has not been systematically investigated and hence the usefulness of bioarchives is unknown. In this study, we assessed the stability of SARS-CoV-2, influenza viruses, noroviruses and the faecal indicator virus, crAssphage, in raw wastewater and purified nucleic aacid extracts stored at -80 °C for 6–24 months. We found that the isolated viral RNA and DNA showed little signs of degradation in storage over 8–24 months, whereas extensive decay viral and loss of qPCR signal was observed during the storage of raw unprocessed wastewater. The most stable viruses were noroviruses and crAssphage, followed by SARS-CoV-2 and influenza A virus. Based on our findings, we conclude that bioarchives comprised of nucleic acid extracts derived from concentrated wastewater samples may be archived long-term, for at least two years, whereas raw wastewater samples may be discarded after one year. [ABSTRACT FROM AUTHOR]

• Respiratory pathogens are detected year-round at low abundances in urban wastewater. • Hospital wastewater shows more viral diversity in winter versus summer. • Raw influent wastewater contains significantly more viruses than treated effluent. • Genomic wastewater surveillance demonstrates value for public health preparedness. Genomic surveillance of SARS-CoV-2 has given insight into the evolution and epidemiology of the virus and its variant lineages during the COVID-19 pandemic. Expanding this approach to include a range of respiratory pathogens can better inform public health preparedness for potential outbreaks and epidemics. Here, we simultaneously sequenced 38 pathogens including influenza viruses, coronaviruses and bocaviruses, to examine the abundance and seasonality of respiratory pathogens in urban wastewater. We deployed a targeted bait capture method and short-read sequencing (Illumina Respiratory Virus Oligos Panel; RVOP) on composite wastewater samples from 8 wastewater treatment plants (WWTPs) and one associated hospital site. By combining seasonal sampling with whole genome sequencing, we were able to concurrently detect and characterise a range of common respiratory pathogens, including SARS-CoV-2, adenovirus and parainfluenza virus. We demonstrated that 38 respiratory pathogens can be detected at low abundances year-round, that hospital pathogen diversity is higher in winter vs. summer sampling events, and that significantly more viruses are detected in raw influent compared to treated effluent samples. Finally, we compared detection sensitivity of RT-qPCR vs. next generation sequencing for SARS-CoV-2, enteroviruses, influenza A/B, and respiratory syncytial viruses. We conclude that both should be used in combination; RT-qPCR allowed accurate quantification, whilst genomic sequencing detected pathogens at lower abundance. We demonstrate the valuable role of wastewater genomic surveillance and its contribution to the field of wastewater-based epidemiology, gaining rapid understanding of the seasonal presence and persistence for common respiratory pathogens. By simultaneously monitoring seasonal trends and early warning signs of many viruses circulating in communities, public health agencies can implement targeted prevention and rapid response plans. [Display omitted] [ABSTRACT FROM AUTHOR]

This manuscript showcases results from a large scale and comprehensive wastewater-based epidemiology (WBE) study focussed on multi-biomarker suite analysis of both chemical and biological determinants in 10 cities and towns across England equating to a population of ∼7 million people. Multi-biomarker suite analysis, describing city metabolism, can provide a holistic understanding to encompass all of human, and human-derived, activities of a city in a single model: from lifestyle choices (e.g. caffeine intake, nicotine) through to health status (e.g. prevalence of pathogenic organisms, usage of pharmaceuticals as proxy for non-communicable disease, NCD, conditions or infectious disease status), and exposure to harmful chemicals due to environmental and industrial sources (e.g. pesticide intake via contaminated food and industrial exposure). Population normalised daily loads (PNDLs) of many chemical markers were found, to a large extent, driven by the size of population contributing to wastewater (especially NCDs). However, there are several exceptions providing insights into chemical intake that can inform either disease status in various communities or unintentional exposure to hazardous chemicals: e.g. very high PNDLs of ibuprofen in Hull resulting from its direct disposal (confirmed by ibuprofen/2-hydroxyibuprofen ratios) and bisphenol A (BPA) in Hull, Lancaster and Portsmouth likely related to industrial discharge. An importance for tracking endogenous health markers such as 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA, an oxidative stress marker) as a generic marker of health status in communities was observed due to increased levels of HNE-MA seen at Barnoldswick wastewater treatment plant that coincided with higher-than-average paracetamol usage and SARS-CoV-2 prevalence in this community. PNDLs of virus markers were found to be highly variable. Being very prevalent in communities nationwide during sampling, SARS-CoV-2 presence in wastewater was to a large extent community driven. The same applies to the fecal marker virus, crAssphage, which is very prevalent in urban communities. In contrast, norovirus and enterovirus showed much higher variability in prevalence across all sites investigated, with clear cases of localized outbreaks in some cities while maintaining low prevalence in other locations. In conclusion, this study clearly demonstrates the potential for WBE to provide an integrated assessment of community health which can help target and validate policy interventions aimed at improving public health and wellbeing. [Display omitted] • First national WBE study encompassing both chemical and biological markers. • Community-wide chemical intake informs disease status and hazardous chemical exposure. • Direct disposal of unused pharma and industrial discharge plasticisers observed. • Endogenous health markers important as generic markers of health status in communities. • Virus markers are highly variable with clear cases of localized outbreaks observed. [ABSTRACT FROM AUTHOR]

• Biochemical markers (BCIs) tested as population markers (PE) in wastewater-based epidemiology (WBE). • Cimetidine is the best performing BCI. • Chemical markers outperform genetic markers as PE BCIs. • Ammonium/orthophosphate as well as viral PE markers are not recommended as PE markers. • PE BCI calibration/validation at the country/region level is advised to establish best PE markers. This study identifies biochemical markers (BCIs) that can be used as population markers in wastewater-based epidemiology (WBE) and compares their estimates with other established population size estimation (PE) methods, including census data (PE CEN). Several groups of BCIs (64 targets: genetic and chemical markers) were investigated in an intercity study, including 10 cities/towns within England equating to a population of ∼7 million people. Several selection criteria were applied to identify the best BCIs to provide robust estimation of population size at a catchment level: (1) excellent performance with analytical methods; (2) excellent fit of the linear regression model which indicates PE-driven BCI daily loads; (3) low temporal variability in usage; (4) human-linked origin. Only a few tested BCIs showed a strong positive linear correlation between daily BCI loads and PE indicating their low spatiotemporal variability. These are: cimetidine, clarithromycin, metformin, cotinine, bezafibrate, metronidazole and hydroxymetronidazole, diclofenac, and benzophenone 1. However, only high/long term usage pharmaceuticals: cimetidine and metformin as well as cotinine (metabolite of nicotine) performed well when tested in two independent datasets and catchments accounting for both spatial and temporal scales. Strong seasonal usage trends were observed for antihistamines, NSAIDs (anti-inflammatories), antibiotics and UV filters, invalidating them as PE markers. Key conclusions from the study are: (1) Cimetidine is the best performing BCI; (2) Chemical markers outperform genetic markers as PE BCIs; (3) Water utility PE estimates (PE WW) align well with PE CEN and PE BCI values; (4) Ammonium/orthophosphate as well as viral PE markers suffer from high temporal variability, hence, they are not recommended as PE BCI markers, and, most importantly, (5) PE BCI calibration/validation at the country/region level is advised in order to establish the best PE markers suited for local/national needs and accounting for site/region specific uncertainties. [ABSTRACT FROM AUTHOR]

• HT qPCR detected all 73 targeted ARGs, while metagenomics detected 491 ARGs. • HT qPCR was more sensitive to low abundance genes, detecting all target ARGs. • Both methods enabled the spatiotemporal separation of hospital and WWTP resistomes. • Metagenomics provided contextual data making it more suitable for risk assessment. • HT qPCR permitted more sensitive quantification of clinically relevant AMR genes. Wastewater serves as an important reservoir of antimicrobial resistance (AMR), and its surveillance can provide insights into population-level trends in AMR to inform public health policy. This study compared two common high-throughput screening approaches, namely (i) high-throughput quantitative PCR (HT qPCR), targeting 73 antimicrobial resistance genes, and (ii) metagenomic sequencing. Weekly composite samples of wastewater influent were taken from 47 wastewater treatment plants (WWTPs) across Wales, as part of a national AMR surveillance programme, alongside 4 weeks of daily wastewater effluent samples from a large municipal hospital. Metagenomic analysis provided more comprehensive resistome coverage, detecting 545 genes compared to the targeted 73 genes by HT qPCR. It further provided contextual information critical to risk assessment (i.e. potential bacterial hosts). In contrast, HT qPCR exhibited higher sensitivity, quantifying all targeted genes including those of clinical relevance present at low abundance. When limited to the HT qPCR target genes, both methods were able to reflect the spatiotemporal dynamics of the complete metagenomic resistome, distinguishing that of the hospital and the WWTPs. Both approaches revealed correlations between resistome compositional shifts and environmental variables like ammonium wastewater concentration, though differed in their interpretation of some potential influencing factors. Overall, metagenomics provides more comprehensive resistome profiling, while qPCR permits sensitive quantification of genes significant to clinical resistance. We highlight the importance of selecting appropriate methodologies aligned to surveillance aims to guide the development of effective wastewater-based AMR monitoring programmes. [Display omitted] [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic. [Display omitted] • Wastewater is a relatively unbiased medium transporting multiple markers of human health. • Biological- and chemical-based Wastewater-Based Epidemiology provides flexibility and resilience for public health security. • Measurements of target analytes in wastewater are subject to variability and uncertainty. • Identifying and mitigating uncertainty requires multi-disciplinary collaboration. • UK wastewater monitoring programmes have generated a substantial data resource to derive better understanding of uncertainty. [ABSTRACT FROM AUTHOR]