Impact of Recombinant VSV-HIV Prime, DNA-Boost Vaccine Candidates on Immunogenicity and Viremia on SHIV-Infected Rhesus Macaques.

Currently, no effective vaccine to prevent human immunodeficiency virus (HIV) infection is available, and various platforms are being examined. The vesicular stomatitis virus (VSV) vaccine vehicle can induce robust humoral and cell-mediated immune responses, making it a suitable candidate for the development of an HIV vaccine. Here, we analyze the protective immunological impacts of recombinant VSV vaccine vectors that express chimeric HIV Envelope proteins (Env) in rhesus macaques. To improve the immunogenicity of these VSV-HIV Env vaccine candidates, we generated chimeric Envs containing the transmembrane and cytoplasmic tail of the simian immunodeficiency virus (SIV), which increases surface Env on the particle. Additionally, the Ebola virus glycoprotein was added to the VSV-HIV vaccine particles to divert tropism from CD4 T cells and enhance their replications both in vitro and in vivo. Animals were boosted with DNA constructs that encoded matching antigens. Vaccinated animals developed non-neutralizing antibody responses against both the HIV Env and the Ebola virus glycoprotein (EBOV GP) as well as systemic memory T-cell activation. However, these responses were not associated with observable protection against simian-HIV (SHIV) infection following repeated high-dose intra-rectal SHIV SF162p3 challenges.

Comparative assessment of Nanotrap and polyethylene glycol-based virus concentration in wastewater samples.

Wastewater-based epidemiology is now widely used in many countries for the routine monitoring of SARS-CoV-2 and other viruses at a community level. However, efficient sample processing technologies are still under investigation. In this study, we compared the performance of the novel Nanotrap® Microbiome Particles (NMP) concentration method to the commonly used polyethylene glycol (PEG) precipitation method for concentrating viruses from wastewater and their subsequent quantification and sequencing. For this, we first spiked wastewater with SARS-CoV-2, influenza and measles viruses and norovirus and found that the NMP method recovered 0.4%-21% of them depending on virus type, providing consistent and reproducible results. Using the NMP and PEG methods, we monitored SARS-CoV-2, influenza A and B viruses, RSV, enteroviruses and norovirus GI and GII and crAssphage in wastewater using quantitative PCR (qPCR)-based methods and next-generation sequencing. Good viral recoveries were observed for highly abundant viruses using both methods; however, PEG precipitation was more successful in the recovery of low-abundance viruses present in wastewater. Furthermore, samples processed with PEG precipitation were more successfully sequenced for SARS-CoV-2 than those processed with the NMP method. Virus recoveries were enhanced by high sample volumes when PEG precipitation was applied. Overall, our results suggest that the NMP concentration method is a rapid and easy virus concentration method for viral targets that are abundant in wastewater, whereas PEG precipitation may be more suited to the recovery and analysis of low-abundance viruses and for next generation sequencing.

Direct-ink-write cross-linkable bottlebrush block copolymers for on-the-fly control of structural color.

Additive manufacturing capable of controlling and dynamically modulating structures down to the nanoscopic scale remains challenging. By marrying additive manufacturing with self-assembly, we develop a UV (ultra-violet)-assisted direct ink write approach for on-the-fly modulation of structural color by programming the assembly kinetics through photo-cross-linking. We design a photo-cross-linkable bottlebrush block copolymer solution as a printing ink that exhibits vibrant structural color (i.e., photonic properties) due to the nanoscopic lamellar structures formed post extrusion. By dynamically modulating UV-light irradiance during printing, we can program the color of the printed material to access a broad spectrum of visible light with a single ink while also creating color gradients not previously possible. We unveil the mechanism of this approach using a combination of coarse-grained simulations, rheological measurements, and structural characterizations. Central to the assembly mechanism is the matching of the cross-linking timescale with the assembly timescale, which leads to kinetic trapping of the assembly process that evolves structural color from blue to red driven by solvent evaporation. This strategy of integrating cross-linking chemistry and out-of-equilibrium processing opens an avenue for spatiotemporal control of self-assembled nanostructures during additive manufacturing.

Near-source passive sampling for monitoring viral outbreaks within a university residential setting.

Wastewater-based epidemiology (WBE) has proven to be a powerful tool for the population-level monitoring of pathogens, particularly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For assessment, several wastewater sampling regimes and methods of viral concentration have been investigated, mainly targeting SARS-CoV-2. However, the use of passive samplers in near-source environments for a range of viruses in wastewater is still under-investigated. To address this, near-source passive samples were taken at four locations targeting student hall of residence. These were chosen as an exemplar due to their high population density and perceived risk of disease transmission. Viruses investigated were SARS-CoV-2 and its variants of concern (VOCs), influenza viruses, and enteroviruses. Sampling was conducted either in the morning, where passive samplers were in place overnight (17 h) and during the day, with exposure of 7 h. We demonstrated the usefulness of near-source passive sampling for the detection of VOCs using quantitative polymerase chain reaction (qPCR) and next-generation sequencing (NGS). Furthermore, several outbreaks of influenza A and sporadic outbreaks of enteroviruses (some associated with enterovirus D68 and coxsackieviruses) were identified among the resident student population, providing evidence of the usefulness of near-source, in-sewer sampling for monitoring the health of high population density communities.

Innovations in genomic antimicrobial resistance surveillance.

Whole-genome sequencing of antimicrobial-resistant pathogens is increasingly being used for antimicrobial resistance (AMR) surveillance, particularly in high-income countries. Innovations in genome sequencing and analysis technologies promise to revolutionise AMR surveillance and epidemiology; however, routine adoption of these technologies is challenging, particularly in low-income and middle-income countries. As part of a wider series of workshops and online consultations, a group of experts in AMR pathogen genomics and computational tool development conducted a situational analysis, identifying the following under-used innovations in genomic AMR surveillance: clinical metagenomics, environmental metagenomics, gene or plasmid tracking, and machine learning. The group recommended developing cost-effective use cases for each approach and mapping data outputs to clinical outcomes of interest to justify additional investment in capacity, training, and staff required to implement these technologies. Harmonisation and standardisation of methods, and the creation of equitable data sharing and governance frameworks, will facilitate successful implementation of these innovations.

Exploiting genomics for antimicrobial resistance surveillance at One Health interfaces.

The intersection of human, animal, and ecosystem health at One Health interfaces is recognised as being of key importance in the evolution and spread of antimicrobial resistance (AMR) and represents an important, and yet rarely realised opportunity to undertake vital AMR surveillance. A working group of international experts in pathogen genomics, AMR, and One Health convened to take part in a workshop series and online consultation focused on the opportunities and challenges facing genomic AMR surveillance in a range of settings. Here we outline the working group's discussion of the potential utility, advantages of, and barriers to, the implementation of genomic AMR surveillance at One Health interfaces and propose a series of recommendations for addressing these challenges. Embedding AMR surveillance at One Health interfaces will require the development of clear beneficial use cases, especially in low-income and middle-income countries. Evidence of directionality, risks to human and animal health, and potential trade implications were also identified by the working group as key issues. Addressing these challenges will be vital to enable genomic surveillance technology to reach its full potential for assessing the risk of transmission of AMR between the environment, animals, and humans at One Health interfaces.

Comparison of metagenomic and targeted methods for sequencing human pathogenic viruses from wastewater.

Wastewater-based epidemiology is a powerful tool for monitoring the emergence and spread of viral pathogens at the population scale. Typical polymerase chain reaction (PCR)-based methods of quantitative and genomic monitoring of viruses in wastewater provide high sensitivity and specificity. However, these methods are limited to the surveillance of target viruses in a single assay and require prior knowledge of the target genome(s). Metagenomic sequencing methods may represent a target-agnostic approach to viral wastewater monitoring, allowing for the detection of a broad range of target viruses, including potentially novel and emerging pathogens. In this study, targeted and untargeted metagenomic sequencing methods were compared with tiled-PCR sequencing for the detection and genotyping of viral pathogens in wastewater samples. Deep shotgun metagenomic sequencing was unable to generate sufficient genome coverage of human pathogenic viruses for robust genomic epidemiology, with samples dominated by bacteria. Hybrid-capture enrichment of shotgun libraries for respiratory viruses led to significant increases in genome coverage for a range of targets. Tiled-PCR sequencing led to further improvements in genome coverage compared to hybrid capture for severe acute respiratory syndrome coronavirus 2, enterovirus D68, norovirus GII, and human adenovirus F41 in wastewater samples. In conclusion, untargeted shotgun sequencing was unsuitable for genomic monitoring of the low virus concentrations in wastewater samples analyzed in this study. Hybrid-capture enrichment represented a viable method for simultaneous genomic epidemiology of a range of viral pathogens, while tiled-PCR sequencing provided the optimal genome coverage for individual viruses with the minimum sequencing depth. IMPORTANCE Most public health initiatives that monitor viruses in wastewater have utilized quantitative polymerase chain reaction (PCR) and whole genome PCR sequencing, mirroring techniques used for viral epidemiology in individuals. These techniques require prior knowledge of the target viral genome and are limited to monitoring individual or small groups of viruses. Metagenomic sequencing may offer an alternative strategy for monitoring a broad spectrum of viruses in wastewater, including novel and emerging pathogens. In this study, while amplicon sequencing gave high viral genome coverage, untargeted shotgun sequencing of total nucleic acid samples was unable to detect human pathogenic viruses with enough sensitivity for use in genomic epidemiology. Enrichment of shotgun libraries for respiratory viruses using hybrid-capture technology provided genotypic information on a range of viruses simultaneously, indicating strong potential for wastewater surveillance. This type of targeted metagenomics could be used for monitoring diverse targets, such as pathogens or antimicrobial resistance genes, in environmental samples.

Rhesus macaques show increased resistance to repeated SHIV intrarectal exposure following a heterologous regimen of rVSV vector vaccine expressing HIV antigen.

Despite the human immunodeficiency virus (HIV) pandemic continuing worldwide for 40 years, no vaccine to combat the disease has been licenced for use in at risk populations. Here, we describe a novel recombinant vesicular stomatitis virus (rVSV) vector vaccine expressing modified HIV envelope glycoproteins and Ebola virus glycoprotein. Three heterologous immunizations successfully prevented infection by a different clade SHIV in 60% of non-human primates (NHPs). No trend was observed between resistance and antibody interactions. Resistance to infection was associated with high proportions of central memory T-cell CD69 and CD154 marker upregulation, increased IL-2 production, and a reduced IFN-γ response, offering insight into correlates of protection.

Postpandemic rebound of adeno-associated virus type 2 (AAV2) infections temporally associated with an outbreak of unexplained severe acute hepatitis in children in the United Kingdom.

Over 1000 cases of unexplained severe acute hepatitis in children have been reported to date worldwide. An association with adeno-associated virus type 2 (AAV2) infection, a human parvovirus, prompted us to investigate the epidemiology of AAV in the United Kingdom. Three hundred pediatric respiratory samples collected before (April 03, 2009-April 03, 2013) and during (April 03, 2022) the COVID-19 pandemic were obtained. Wastewater samples were collected from 50 locations in London (August 2021-March 2022). Samples were tested for AAV using real-time polymerase chain reaction followed by sequencing. Selected adenovirus (AdV)-positive samples were also sequenced. The detection frequency of AAV2 was a sevenfold higher in 2022 samples compared with 2009-2013 samples (10% vs. 1.4%) and highest in AdV-positive samples compared with negatives (10/37, 27% vs. 5/94, 5.3%, respectively). AAV2-positive samples displayed high genetic diversity. AAV2 sequences were either very low or absent in wastewater collected in 2021 but increased in January 2022 and peaked in March 2022. AAV2 was detected in children in association with AdV of species C, with a highest frequency in 2022. Our findings are consistent with the expansion of the population of children unexposed to AAV2, leading to greater spread of the virus once distancing restrictions were lifted.

Smartphones, social Media and Adolescent mental well-being: the impact of school policies Restricting dayTime use-protocol for a natural experimental observational study using mixed methods at secondary schools in England (SMART Schools Study).

INTRODUCTION: Smartphone and social media use is prevalent during adolescence, with high levels of use associated with lower levels of mental well-being. Secondary schools in the UK have introduced policies that restrict daytime use of smartphones and social media, but there is no evaluation on the impact of these policies on adolescent mental well-being. The SMART Schools Study aims to determine the impact of daytime restrictions of smartphone and social media use on indicators of adolescent mental well-being, anxiety, depression, physical activity, sleep, classroom behaviour, attainment and addictive social media use. METHODS AND ANALYSIS: This is a natural experimental observational study using mixed methods. Secondary schools within a 100 mile radius of the recruiting centre in the West Midlands (UK) have been categorised into two groups: Schools that restrict (intervention) and permit (comparator) daytime use of smartphones. We aim to recruit 30 schools (20 restrictive, 10 permissive) and 1170 pupils aged 12-13 and 14-15 years. We will collect data on mental well-being, anxiety and depressive symptoms, phone and social media use, sleep and physical activity from pupil surveys, and accelerometers. Policy implementation measures and data on individual pupil factors will be collected through school staff surveys, and website/policy analysis. Six case study schools will explore individual, school and family/home factors that influence relationships between school smartphone policies, smartphone/social media use, and mental well-being. Economic evaluation will be completed through a cost-consequence analysis from an education sector perspective. ETHICS AND DISSEMINATION: Ethical approval was obtained from the University of Birmingham's Research Ethics Committee (ERN_22-0723). Parents/carers of pupil participants can complete a form to opt their child out of the study. Pupil, school staff and parent/carer participants are asked to complete online/written consent (or assent). Findings will be disseminated through policy briefings, resources for schools, social media, reports, and open access publications. TRIAL REGISTRATION NUMBER: ISRCTN77948572.

Evaluating the theoretical performance of aircraft wastewater monitoring as a tool for SARS-CoV-2 surveillance.

Air travel plays an important role in the cross-border spread of infectious diseases. During the SARS-CoV-2 pandemic many countries introduced strict border testing protocols to monitor the incursion of the virus. However, high implementation costs and significant inconvenience to passengers have led public health authorities to consider alternative methods of disease surveillance at borders. Aircraft wastewater monitoring has been proposed as one such alternative. In this paper we assess the theoretical limits of aircraft wastewater monitoring and compare its performance to post-arrival border screening approaches. Using an infectious disease model, we simulate an unmitigated SARS-CoV-2 epidemic originating in a seed country and spreading to the United Kingdom (UK) through daily flights. We use a probabilistic approach to estimate the time of first detection in the UK in aircraft wastewater and respiratory swab screening. Across a broad range of model parameters, our analysis indicates that the median time between the first incursion and detection in wastewater would be approximately 17 days (IQR: 7-28 days), resulting in a median of 25 cumulative cases (IQR: 6-84 cases) in the UK at the point of detection. Comparisons to respiratory swab screening suggest that aircraft wastewater monitoring is as effective as random screening of 20% of passengers at the border, using a test with 95% sensitivity. For testing regimes with sensitivity of 85% or less, the required coverage to outperform wastewater monitoring increases to 30%. Analysis of other model parameters suggests that wastewater monitoring is most effective when used on long-haul flights where probability of defecation is above 30%, and when the target pathogen has high faecal shedding rates and reasonable detectability in wastewater. These results demonstrate the potential use cases of aircraft wastewater monitoring and its utility in a wider system of public health surveillance.

Wastewater monitoring can anchor global disease surveillance systems.

To inform the development of global wastewater monitoring systems, we surveyed programmes in 43 countries. Most programmes monitored predominantly urban populations. In high-income countries (HICs), composite sampling at centralised treatment plants was most common, whereas grab sampling from surface waters, open drains, and pit latrines was more typical in low-income and middle-income countries (LMICs). Almost all programmes analysed samples in-country, with an average processing time of 2·3 days in HICs and 4·5 days in LMICs. Whereas 59% of HICs regularly monitored wastewater for SARS-CoV-2 variants, only 13% of LMICs did so. Most programmes share their wastewater data internally, with partnering organisations, but not publicly. Our findings show the richness of the existing wastewater monitoring ecosystem. With additional leadership, funding, and implementation frameworks, thousands of individual wastewater initiatives can coalesce into an integrated, sustainable network for disease surveillance-one that minimises the risk of overlooking future global health threats.

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year.

BACKGROUND: Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. METHODS: A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. RESULTS: We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. CONCLUSIONS: Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study.

Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.

Evaluation of variant calling algorithms for wastewater-based epidemiology using mixed populations of SARS-CoV-2 variants in synthetic and wastewater samples.

Wastewater-based epidemiology has been used extensively throughout the COVID-19 (coronavirus disease 19) pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public-health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants; yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants of concern (VOCs) (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15th and 18th December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers. Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.

Investigation of the yielding transition in concentrated colloidal systems via rheo-XPCS.

We probe the microstructural yielding dynamics of a concentrated colloidal system by performing creep/recovery tests with simultaneous collection of coherent scattering data via X-ray Photon Correlation Spectroscopy (XPCS). This combination of rheology and scattering allows for time-resolved observations of the microstructural dynamics as yielding occurs, which can be linked back to the applied rheological deformation to form structure-property relations. Under sufficiently small applied creep stresses, examination of the correlation in the flow direction reveals that the scattering response recorrelates with its predeformed state, indicating nearly complete microstructural recovery, and the dynamics of the system under these conditions slows considerably. Conversely, larger creep stresses increase the speed of the dynamics under both applied creep and recovery. The data show a strong connection between the microstructural dynamics and the acquisition of unrecoverable strain. By comparing this relationship to that predicted from homogeneous, affine shearing, we find that the yielding transition in concentrated colloidal systems is highly heterogeneous on the microstructural level.

Optimised protocol for monitoring SARS-CoV-2 in wastewater using reverse complement PCR-based whole-genome sequencing.

Monitoring the spread of viral pathogens in the population during epidemics is crucial for mounting an effective public health response. Understanding the viral lineages that constitute the infections in a population can uncover the origins and transmission patterns of outbreaks and detect the emergence of novel variants that may impact the course of an epidemic. Population-level surveillance of viruses through genomic sequencing of wastewater captures unbiased lineage data, including cryptic asymptomatic and undiagnosed infections, and has been shown to detect infection outbreaks and novel variant emergence before detection in clinical samples. Here, we present an optimised protocol for quantification and sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in influent wastewater, used for high-throughput genomic surveillance in England during the COVID-19 pandemic. This protocol utilises reverse compliment PCR for library preparation, enabling tiled amplification across the whole viral genome and sequencing adapter addition in a single step to enhance efficiency. Sequencing of synthetic SARS-CoV-2 RNA provided evidence validating the efficacy of this protocol, while data from high-throughput sequencing of wastewater samples demonstrated the sensitivity of this method. We also provided guidance on the quality control steps required during library preparation and data analysis. Overall, this represents an effective method for high-throughput sequencing of SARS-CoV-2 in wastewater which can be applied to other viruses and pathogens of humans and animals.

Wastewater-based monitoring of SARS-CoV-2 at UK airports and its potential role in international public health surveillance.

It is well established that air travel plays a key role in the global spread of many enteric and respiratory diseases, including COVID-19. Even with travel restrictions (e.g. mask wearing, negative COVID-19 test prior to departure), SARS-CoV-2 may be transmitted by asymptomatic or pre-symptomatic individuals carrying the virus. Due to the limitation of current clinical surveillance approaches, complementary methods need to be developed to allow estimation of the frequency of SARS-CoV-2 entry across international borders. Wastewater-based epidemiology (WBE) represents one such approach, allowing the unbiased sampling of SARS-CoV-2 carriage by passenger cohorts entering via airports. In this study, we monitored sewage in samples from terminals (n = 150) and aircraft (n = 32) at three major international airports in the UK for 1-3 weeks in March 2022. As the raw samples were more turbid than typical municipal wastewater, we used beef extract treatment followed by polyethylene glycol (PEG) precipitation to concentrate viruses, followed by reverse transcription quantitative PCR (RT-qPCR) for the detection of SARS-CoV-2 and a faecal indicator virus, crAssphage. All samples taken from sewers at the arrival terminals of Heathrow and Bristol airports, and 85% of samples taken from sites at Edinburgh airport, were positive for SARS-CoV-2. This suggests a high COVID-19 prevalence among passengers and/or airport staff members. Samples derived from aircraft also showed 93% SARS-CoV-2 positivity. No difference in viral prevalence was found before and after COVID-19 travel restrictions were lifted. Our results suggest that WBE is a useful tool for monitoring the global transfer rate of human pathogens and other disease-causing agents across international borders and should form part of wider international efforts to monitor and contain the spread of future disease outbreaks.

Wastewater-based epidemiology for comprehensive community health diagnostics in a national surveillance study: Mining biochemical markers in wastewater.

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.