Back-estimation of norovirus infections through wastewater-based epidemiology: A systematic review and parameter sensitivity

Urban wastewater-based epidemiology for multi-viral pathogen surveillance in the Valencian region, Spain

Wastewater-based epidemiology (WBE) has lately arised as a promising tool for monitoring and tracking viral pathogens in communities. In this study, we analysed WBE's role as a multi-pathogen surveillance strategy to detect the presence of several viral illness causative agents. Thus, an epidemiological study was conducted from October 2021 to February 2023 to estimate the weekly levels of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Respiratory Syncytial virus (RSV), and Influenza A virus (IAV) in influent wastewater samples (n = 69). In parallel, a one-year study (October 2021 to October 2022) was performed to assess the presence of pathogenic human enteric viruses. Besides, monitoring of proposed viral fecal contamination indicators crAssphage and Pepper mild mottle virus (PMMoV) was also assessed, along with plaque counting of somatic coliphages. Genetic material of rotavirus (RV), human astrovirus (HAStV), and norovirus genogroup I (GI) and GII was found in almost all samples, while hepatitis A and E viruses (HAV and HEV) only tested positive in 3.77 % and 22.64 % of the samples, respectively. No seasonal patterns were overall found for enteric viruses, although RVs had a peak prevalence in the winter months. All samples tested positive for SARS-CoV-2 RNA, with a mean concentration of 5.43 log genome copies per liter (log GC/L). The tracking of the circulating SARS-CoV-2 variants of concern (VOCs) was performed by both duplex RT-qPCR and next generation sequencing (NGS). Both techniques reliably showed how the dominant VOC transitioned from Delta to Omicron during two weeks in Spain in December 2021. RSV and IAV viruses peaked in winter months with mean concentrations 6.40 and 4.10 log GC/L, respectively. Moreover, the three selected respiratory viruses strongly correlated with reported clinical data when normalised by wastewater physico-chemical parameters and presented weaker correlations when normalising sewage concentration levels with crAssphage or somatic coliphages titers. Finally, predictive models were generated for each respiratory virus, confirming high reliability on WBE data as an early-warning system and communities illness monitoring system. Overall, this study presents WBE as an optimal tool for multi-pathogen tracking reflecting viral circulation and diseases trends within a selected area, its value as a multi-pathogen early-warning tool stands out due to its public health interest.

Monitoring viruses and beta-lactam resistance genes through wastewater surveillance during a COVID-19 surge in Suwon, South Korea

The present study reports data on a long-term campaign for monitoring SARS-CoV-2, norovirus, hepatitis A virus, and beta-lactam resistance genes in wastewater samples from a wastewater treatment plant during COVID-19 surge in Suwon, South Korea. Real-time digital PCR (RT-dPCR) assays indicated 100 % occurrence of all but hepatitis A virus and blaNDM gene in influent wastewater samples. CDC-N1 assay detected SARS-CoV-2 in all influent samples with an average log-transformed concentration of 5.1 ± 0.39 and the highest level at 6.02 gene copies/L. All samples were also positive for norovirus throughout the study with a mean concentration 5.67 ± 0.65 log10 gene copies/L. On the contrary, all treated wastewater (effluent) tested negative for both viruses' genetic materials. Furthermore, plasmid-mediated AmpC β-lactamases (PABLs) genes blaDHA, blaACC, and blaFOX, extended-spectrum β-lactamases (ESBLs) genes blaTEM and blaCTX, and Klebsiella pneumoniae carbapenemase (blaKPC) gene were measured at average concentrations of 7.05 ± 0.26, 5.60 ± 0.35, 7.82 ± 0.43, 8.38 ± 0.20, 7.64 ± 0.29, and 7.62 ± 0.41 log10 gene copies/L wastewater, respectively. Beta-lactam resistance genes showed strong correlations (r), the highest being 0.86 for blaKPC - blaFOX, followed by 0.82 for blaTEM - blaCTX and 0.79 for blaTEM - blaDHA. SARS-CoV-2 RNA occurrence in the wastewater was strongly associated (r = 0.796) with COVID-19 cases in the catchment during the initial study period of six months. A positive association of the SARS-CoV-2 RNA with the prevalence of COVID-19 cases showed a promising role of community-scale monitoring of pathogens to provide considerable early signals of infection dynamics. High concentrations of beta-lactam resistance genes in wastewater indicated a high concern for one of the biggest global health threats in South Korea and the need to find control measures. Moreover, antibiotic-resistance genes in treated wastewater flowing through water bodies and agricultural environments indicate further dissemination of antibiotic resistance traits and increasing microbial antibiotic resistance.

Wastewater-Based Epidemiology for Viral Surveillance from an Endemic Perspective: Evidence and Challenges

Wastewater-based epidemiology (WBE) is currently used to monitor not only the spread of the viral SARS-CoV-2 pandemic but also that of other viruses in endemic conditions, particularly in the absence of syndromic surveillance. The continuous monitoring of sewage requires high expenditure and significant time investments, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Tuscany (Italy) and targeted human adenovirus (HAdV), norovirus genogroup II (NoVggII), enterovirus (EV), and SARS-CoV-2. Samples were collected at the entrances of treatment plants and concentrated using PEG/NaCl precipitation, and viral nucleic acids were extracted and detected through real-time reverse transcription qPCR. NoVggII was the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. Compared with data that were previously collected in the same study area (from February 2021 to September 2021), the results for SARS-CoV-2 revealed a shift from an epidemic to an endemic pattern, at least in the region under investigation, which was likely due to viral mutations that led to the spreading of new variants with increased resistance to summer environmental conditions. In conclusion, using standardized methods and an efficient monitoring strategy, WBE proves valuable for viral surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decisions.

Occurrence, transmission and risks assessment of pathogens in aquatic environments accessible to humans

Pathogens are ubiquitously detected in various natural and engineered water systems, posing potential threats to public health. However, it remains unclear which human-accessible waters are hotspots for pathogens, how pathogens transmit to these waters, and what level of health risk associated with pathogens in these environments. This review collaboratively focuses and summarizes the contamination levels of pathogens on the 5 water systems accessible to humans (natural water, drinking water, recreational water, wastewater, and reclaimed water). Then, we showcase the pathways, influencing factors and simulation models of pathogens transmission and survival. Further, we compare the health risk levels of various pathogens through Quantitative Microbial Risk Assessment (QMRA), and assess the limitations of water-associated QMRA application. Pathogen levels in wastewater are consistently higher than in other water systems, with no significant variation for Cryptosporidium spp. among five water systems. Hydraulic conditions primarily govern the transmission of pathogens into human-accessible waters, while environmental factors such as temperature impact pathogens survival. The median and mean values of computed public health risk levels posed by pathogens consistently surpass safety thresholds, particularly in the context of recreational waters. Despite the highest pathogens levels found in wastewater, the calculated health risk is significantly lower than in other water systems. Except pathogens concentration, variables like the exposure mode, extent, and frequency are also crucial factors influencing the public health risk in water systems. This review shares valuable insights to the more accurate assessment and comprehensive management of public health risk in human-accessible water environments.

Estimation of Norovirus infections in Japan: An application of wastewater-based epidemiology for enteric disease assessment

Noroviruses of genogroup I (NoV GI) and NoV GII are the primary causes of acute gastroenteritis (AGE) in developed countries. However, asymptomatic and untested NoV infections lead to an underestimation of AGE cases, and the lack of mandatory viral identification in clinical cases hinders precise estimation of NoV infections. Back estimation of NoV infections in the community using a wastewater-based epidemiology (WBE) approach can provide valuable insights into the disease's extent, progression, and epidemiology, aiding in developing effective control strategies. This study employed a one-step reverse transcription-quantitative PCR to quantify NoVs GI and GII in wastewater samples (n = 83) collected twice a week from June 2022 to March 2023 in Japan. All samples from the Winter-Spring (n = 27) tested positive for NoV GI and GII RNA, while 73 % and 88 % of samples from the Summer-Autumn (n = 56) were positive for NoV GI and NoV GII RNA, respectively. Significantly higher concentrations of NoV GI/GII RNA were found in the Winter-Spring season compared to the Summer-Autumn season. NoV RNA was consistently detected in wastewater throughout the year, demonstrating the persistence of AGE cases in the catchment, suggesting an endemic NoV infection. Estimates of NoV infection incorporated viral RNA concentrations, wastewater parameters, and signal persistence in a mass balance equation using Monte Carlo Simulation. The median estimated NoV GI infections per 100,000 population for Summer-Autumn was 133 and for the Winter-Spring season, it was 881. Estimated NoV GII infections were 1357 for Summer-Autumn and 11,997 for the Winter-Spring season per 100,000 population. The estimated NoV infections exceeded by 3.2 and 23.9 folds than the reported AGE cases in Summer-Autumn and Winter-Spring seasons, respectively. The seasonal trend of estimated NoV infections closely matched that of AGE cases, highlighting the utility of WBE in understanding the epidemiology of enteric infections.

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

United States Influenza 2022-2023 Season Characteristics as Inferred from Wastewater Solids, Influenza Hospitalization, and Syndromic Data

Influenza A virus (IAV) causes significant morbidity and mortality in the United States and has pandemic potential. Identifying IAV epidemic patterns is essential to inform the timing of vaccinations and nonpharmaceutical interventions. In a prospective, longitudinal study design, we measured IAV RNA in wastewater settled solids at 163 wastewater treatment plants across 33 states to characterize the 2022-2023 influenza season at the state, health and human services (HHS) regional, and national scales. Influenza season onset, offset, duration, peak, and intensity using IAV RNA in wastewater were compared with those determined using laboratory-confirmed influenza hospitalization rates and outpatient visits for influenza-like illness (ILI). The onset for HHS regions as determined by IAV RNA in wastewater roughly corresponded with those determined using ILI when the annual geometric mean of IAV RNA concentration was used as a baseline (i.e., the threshold that triggers onset), although offsets between the two differed. IAV RNA in wastewater provided early warning of onset, compared to the ILI estimate, when the baseline was set at twice the limit of IAV RNA detection in wastewater. Peak when determined by IAV RNA in wastewater generally preceded peak determined by IAV hospitalization rate by 2 weeks or less. IAV RNA in wastewater settled solids is an IAV-specific indicator that can be used to augment clinical surveillance for seasonal influenza epidemic timing and intensity.

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

Wastewater-based epidemiology of Campylobacter spp.: A systematic review and meta-analysis of influent, effluent, and removal of wastewater treatment plants

Campylobacter spp. is one of the four leading causes of diarrhoeal diseases worldwide, which are generally mild but can be fatal in children, the elderly, and immunosuppressed persons. The existing disease surveillance for Campylobacter infections is usually based on untimely clinical reports. Wastewater surveillance or wastewater-based epidemiology (WBE) has been developed for the early warning of disease outbreaks and the detection of the emerging new variants of human pathogens, especially after the global pandemic of COVID-19. However, the WBE monitoring of Campylobacter infections in communities is rare due to a few large data gaps. This study is a meta-analysis and systematic review of the prevalence of Campylobacter spp. in various wastewater samples, primarily the influent of wastewater treatment plants. The results showed that the overall prevalence of Campylobacter spp. was 53.26 % in influent wastewater and 52.97 % in all types of wastewater samples. The mean concentration in the influent was 3.31 ± 0.39 log10 gene copies or most probable number (MPN) per 100 mL. The detection method combining culture and PCR yielded the highest positive rate of 90.86 %, while RT-qPCR and qPCR were the two most frequently used quantification methods. In addition, the Campylobacter concentration in influent wastewater showed a seasonal fluctuation, with the highest concentration in the autumn at 3.46 ± 0.41 log10 gene copies or MPN per 100 mL. Based on the isolates of all positive samples, Campylobacter jejuni (62.34 %) was identified as the most prevalent species in wastewater, followed by Campylobacter coli (30.85 %) and Campylobacter lari (4.4 %). These findings provided significant data to further develop and optimize the wastewater surveillance of Campylobacter spp. infections. In addition, large data gaps were found in the decay of Campylobacter spp. in wastewater, indicating insufficient research on the persistence of Campylobacter spp. in wastewater.

Molecular Characterization of Gastroenteric Viruses in Wastewater from Cities in Uruguay

Group A Rotavirus, Human Astrovirus, and Norovirus (RVA, HAstV, and NoV) are recognized as the major causative agents of acute gastroenteritis in children and adults worldwide. The aim of this study was to determine the prevalence and molecular epidemiology of RVA, HAstV, and NoV in wastewater from three cities in Uruguay. Thirty-six samples from Bella Unión, Salto, and Fray Bentos cities were analyzed using quantitative and qualitative PCR. RVA was the most frequently detected virus (50%), followed by HAstV (39%), NoV GII (36%), and NoV GI (25%). RVA strains were characterized as P[8] and G3 based on the VP4 and VP7 genes, respectively. Among NoV-positive samples, genotypes GI.2, GI.3, GI.5, GI.6, GI.7, GII.2, GII.6, and GII.4 were detected, and only one HAstV genotype (MLB1) was found. Our wastewater-based epidemiological approach provides a snapshot of the overall genetic diversity of these viruses in three cities of the Uruguay River basin during 2017-2018. These findings reinforce the importance of this environmental surveillance tool for monitoring epidemiological trends of enteric viruses circulating in the population, which can be used to guide public health intervention.

Development and validation of a duplex RT-qPCR assay for norovirus quantification in wastewater samples

Norovirus (NoV) is a highly contagious enteric virus that causes widespread outbreaks and a substantial number of deaths across communities. As clinical surveillance is often insufficient, wastewater-based epidemiology (WBE) may provide novel pathways of tracking outbreaks. To utilise WBE, it is important to use accurate and sensitive methods for viral quantification. In this study, we developed a one-step duplex RT-qPCR assay to simultaneously test the two main human pathogenic NoV genogroups, GI and GII, in wastewater samples. The assay had low limits of detection (LOD), namely 0.52 genome copies (gc)/µl for NoVGI and 1.37 gc/µl for NoVGII. No significant concentration-dependent interactions were noted for both NoVGI and for NoVGII when the two targets were mixed at different concentrations in the samples. When tested on wastewater-derived RNA eluents, no significant difference between duplex and singleplex concentrations were found for either target. Low levels of inhibition (up to 32 %) were noted due to organic matter present in the wastewater extracts. From these results we argue that the duplex RT-qPCR assay developed enables the sensitive detection of both NoVGI and NoVGII in wastewater-derived RNA eluents, in a time and cost-effective way and may be used for surveillance to monitor public and environmental health.

Passive Sampler Technology for Viral Detection in Wastewater-Based Surveillance: Current State and Nanomaterial Opportunities

Although wastewater-based surveillance (WBS) is an efficient community-wide surveillance tool, its implementation for pathogen surveillance remains limited by ineffective sample treatment procedures, as the complex composition of wastewater often interferes with biomarker recovery. Moreover, current sampling protocols based on grab samples are susceptible to fluctuant biomarker concentrations and may increase operative costs, often rendering such systems inaccessible to communities in low-to-middle-income countries (LMICs). As a response, passive samplers have emerged as a way to make wastewater sampling more efficient and obtain more reliable, consistent data. Therefore, this study aims to review recent developments in passive sampling technologies to provide researchers with the tools to develop novel passive sampling strategies. Although promising advances in the development of nanostructured passive samplers have been reported, optimization remains a significant area of opportunity for researchers in the area, as methods for flexible, robust adsorption and recovery of viral genetic materials would greatly improve the efficacy of WBS systems while making them more accessible for communities worldwide.

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Human norovirus (HuNoV) GII RNA in wastewater solids at 145 United States wastewater treatment plants: comparison to positivity rates of clinical specimens and modeled estimates of HuNoV GII shedders

BACKGROUND

Human norovirus (HuNoV) is a leading cause of disease globally, yet actual incidence is unknown. HuNoV infections are not reportable in the United States, and surveillance is limited to tracking severe illnesses or outbreaks. Wastewater monitoring for HuNoV has been done previously and results indicate it is present in wastewater influent and concentrations are associated with HuNoV infections in the communities contributing to wastewater. However, work has mostly been limited to monthly samples of liquid wastewater at one or a few wastewater treatment plants (WWTPs).

OBJECTIVE

The objectives of this study are to investigate whether HuNoV GII preferentially adsorbs to wastewater solids, investigate concentrations of HuNoV GII in wastewater solids in wastewater treatment plants across the county, and explore how those relate to clinical measures of disease occurrence. In addition, we aim to develop and apply a mass-balance model that predicts the fraction of individuals shedding HuNoV in their stool based on measured concentrations in wastewater solids.

METHODS

We measured HuNoV GII RNA in matched wastewater solids and liquid influent in 7 samples from a WWTP. We also applied the HuNoV GII assay to measure viral RNA in over 6000 wastewater solids samples from 145 WWTPs from across the United States daily to three times per week for up to five months. Measurements were made using digital droplet RT-PCR.

RESULTS

HuNoV GII RNA preferentially adsorbs to wastewater solids where it is present at 1000 times the concentration in influent. Concentrations of HuNoV GII RNA correlate positively with clinical HuNoV positivity rates. Model output of the fraction of individuals shedding HuNoV is variable and uncertain, but consistent with indirect estimates of symptomatic HuNoV infections in the United States.

IMPACT STATEMENT

Illness caused by HuNoV is not reportable in the United States so there is limited data on disease occurrence. Wastewater monitoring can provide information about the community spread of HuNoV. Data from wastewater can be available within 24 h of sample receipt at a laboratory. Wastewater is agnostic to whether individuals seek medical care, are symptomatic, and the severity of illness. Knowledge gleaned from wastewater may be used by public health professionals to make recommendations on hand washing, surface disinfection, or other behaviors to reduce transmission of HuNoV, or medical doctors to inform clinical decision making.

In-sewer decay and partitioning of Campylobacter jejuni and Campylobacter coli and implications for their wastewater surveillance

Campylobacter jejuni and coli are two main pathogenic species inducing diarrhoeal diseases in humans, which are responsible for the loss of 33 million lives each year. Current Campylobacter infections are mainly monitored by clinical surveillance which is often limited to individuals seeking treatment, resulting in under-reporting of disease prevalence and untimely indicators of community outbreaks. Wastewater-based epidemiology (WBE) has been developed and employed for the wastewater surveillance of pathogenic viruses and bacteria. Monitoring the temporal changes of pathogen concentration in wastewater allows the early detection of disease outbreaks in a community. However, studies investigating the WBE back-estimation of Campylobacter spp. are rare. Essential factors including the analytical recovery efficiency, the decay rate, the effect of in-sewer transport, and the correlation between the wastewater concentration and the infections in communities are lacking to support wastewater surveillance. This study carried out experiments to investigate the recovery of Campylobacter jejuni and coli from wastewater and the decay under different simulated sewer reactor conditions. It was found that the recovery of Campylobacter spp. from wastewater varied with their concentrations in wastewater and depended on the detection limit of quantification methods. The concentration reduction of Campylobacter. jejuni and coli in sewers followed a two-phase reduction model, and the faster concentration reduction during the first phase is mainly due to their partitioning onto sewer biofilms. The total decay of Campylobacter. jejuni and coli varied in different types of sewer reactors, i.e. rising main vs. gravity sewer. In addition, the sensitivity analysis for WBE back-estimation of Campylobacter suggested that the first-phase decay rate constant (k₁) and the turning time point (t₁) are determining factors and their impacts increased with the hydraulic retention time of wastewater.

Evaluation of population estimation methods for wastewater-based epidemiology in a metropolitan city

This study evaluated the effect of population estimation on the calculation of drug biomarker consumption using wastewater-based epidemiology. Population estimates using mobile phone data, census data, and wastewater quality parameters, such as biological oxygen demand (BOD), total nitrogen (TN), and total phosphorus (TP), were evaluated in six different wastewater treatment plant catchment areas of Busan Metropolitan City, South Korea. The population based on mobile phone data was affected by the patterns of non-resident population movements in each area. The population-normalized daily loads (PNDLs) of methamphetamine were compared according to the different population results. The PNDLs using the population based on mobile phone data (PNDL_Mobile) was 5.87-27.0 mg/d/1000 people. The PNDL_Mobile values were notably different from the PNDLs using wastewater quality parameters (PNDL_Wastewater) (PNDL_Wastewater/PNDL_Mobile: 51-148 %, mean 93 %, relative standard deviation (RSD) 36 %), indicating the unsuitability of population estimation using BOD, TN, and TP. In areas with a large concentration of workplaces, the PNDLs using census data (PNDL_Census) differed from the PNDL_Mobile values (PNDL_Census/PNDL_Mobile: 57-124 %, mean 94 %, RSD 27 %), whereas other areas showed similar values for PNDL_Census and PNDL_Mobile (PNDL_Census/PNDL_Mobile: 95-108 %, mean 102 %, RSD 4.2 %). In particular, the total population estimates of the six survey areas using census data were approximately the same as those based on mobile phone data (RSD: 0.8 %), indicating a decrease in the influence of the non-residential active population in the entire metropolitan city.