Wastewater pandemic preparedness: Toward an end-to-end pathogen monitoring program.

Molecular analysis of public wastewater has great potential as a harbinger for community health and health threats. Long-used to monitor the presence of enteric viruses, in particular polio, recent successes of wastewater as a reliable lead indicator for trends in SARS-CoV-2 levels and hospital admissions has generated optimism and emerging evidence that similar science can be applied to other pathogens of pandemic potential (PPPs), especially respiratory viruses and their variants of concern (VOC). However, there are substantial challenges associated with implementation of this ideal, namely that multiple and distinct fields of inquiry must be bridged and coordinated. These include engineering, molecular sciences, temporal-geospatial analytics, epidemiology and medical, and governmental and public health messaging, all of which present their own caveats. Here, we outline a framework for an integrated, state-wide, end-to-end human pathogen monitoring program using wastewater to track viral PPPs.

The emergence of a virus variant: dynamics of a competition model with cross-immunity time-delay validated by wastewater surveillance data for COVID-19.

We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of the established strain for the local stability of the established-strain-only boundary equilibrium. To analyze the unique coexistence equilibrium we apply a quasi steady-state argument to reduce the full model to a two-dimensional one that exhibits a global asymptotically stable established-strain-only equilibrium or global asymptotically stable coexistence equilibrium. Our results indicate that the basic reproduction numbers of both strains govern the overall dynamics, but in nontrivial ways due to the inclusion of cross-immunity. The model is applied to study the emergence of the SARS-CoV-2 Delta variant in the presence of the Alpha variant using wastewater surveillance data from the Deer Island Treatment Plant in Massachusetts, USA.

Updated analysis to reject the laboratory-engineering hypothesis of SARS-CoV-2.

A clear understanding of the origin of SARS-CoV-2 is important for future pandemic preparedness. Here, I provided an updated analysis of the type IIS endonuclease maps in genomes of alphacoronavirus, betacoronavirus, and SARS-CoV-2. Scenarios to engineer SARS-CoV-2 in the laboratory and the associated workload was also discussed. The analysis clearly shows that the endonuclease fingerprint does not indicate a synthetic origin of SARS-CoV-2 and engineering a SARS-CoV-2 virus in the laboratory is extremely challenging both scientifically and financially. On the contrary, current scientific evidence does support the animal origin of SARS-CoV-2.

Assessment of a SARS-CoV-2 wastewater monitoring program in El Paso, Texas, from November 2020 to June 2022.

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

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities.

Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States.

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater.

On November 26, 2021, the B.1.1.529 COVID-19 variant was classified as the Omicron variant of concern (VOC). Reports of higher transmissibility and potential immune evasion triggered flight bans and heightened health control measures across the world to stem its distribution. Wastewater-based surveillance has demonstrated to be a useful complement for clinical community-based tracking of SARS-CoV-2 variants. Using design principles of our previous assays that detect SARS-CoV-2 variants (Alpha and Delta), we developed an allele-specific RT-qPCR assay which simultaneously targets the stretch of mutations from Q493R to Q498R for quantitative detection of the Omicron variant in wastewater. We report their validation against 10-month longitudinal samples from the influent of a wastewater treatment plant in Italy. SARS-CoV-2 RNA concentrations and variant frequencies in wastewater determined using these variant assays agree with clinical cases, revealing rapid displacement of the Delta variant by the Omicron variant within three weeks. These variant trends, when mapped against vaccination rates, support clinical studies that found the rapid emergence of SARS-CoV-2 Omicron variant being associated with an infection advantage over Delta in vaccinated persons. These data reinforce the versatility, utility and accuracy of these open-sourced methods using allele-specific RT-qPCR for tracking the dynamics of variant displacement in communities through wastewater for informed public health responses.

Making waves: Wastewater surveillance of SARS-CoV-2 in an endemic future.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor the emergence and spread of SARS-CoV-2 infections in populations during the COVID-19 pandemic. Coincident with the global vaccination efforts, the world is also enduring new waves of SARS-CoV-2 variants. Reinfections and vaccine breakthroughs suggest an endemic future where SARS-CoV-2 continues to persist in the general population. In this treatise, we aim to explore the future roles of wastewater surveillance. Practically, WBS serves as a relatively affordable and non-invasive tool for mass surveillance of SARS-CoV-2 infection while minimizing privacy concerns, attributes that make it extremely suited for its long-term usage. In an endemic future, the utility of WBS will include 1) monitoring the trend of viral loads of targets in wastewater for quantitative estimate of changes in disease incidence; 2) sampling upstream for pinpointing infections in neighborhoods and at the building level; 3) integrating wastewater and clinical surveillance for cost-efficient population surveillance; and 4) genome sequencing wastewater samples to track circulating and emerging variants in the population. We further discuss the challenges and future developments of WBS to reduce inconsistencies in wastewater data worldwide, improve its epidemiological inference, and advance viral tracking and discovery as a preparation for the next viral pandemic.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Lysine ß-Hydroxybutyrylation Improves Stability of COVID-19 Antibody.

ß-Hydroxybutyrate (3HB) is a small molecule produced as a ketone body in mammalian animals. It has been found that 3HB provides not only energy for a body, it also participates in cell signal transduction events as a signal molecule. This study focuses on investigation of 3HB immunomodulatory mechanisms. Proteomic analysis indicates a new post-translational modification of ß-hydroxybutyrylation (Kbhb) on antibodies. Because of the low level of Kbhb antibodies and the associated difficulty in purifying them, simulated Kbhb antibody was produced using chemical modification in vitro. The chemically modified Kbhb antibody was shown to improve the stability of antibodies to protease and heat treatments. Furthermore, Kbhb of antibodies stabilizes the antibodies in plasma. As a remarkable example, COVID-19 neutralizing antibody B38 produced by 293T cells was Kbhb modified and stabilized in vivo, providing a strategy for the possibility of extending the protection effects of COVID-19 antibodies.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020.

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases.

Wastewater surveillance represents a complementary approach to clinical surveillance to measure the presence and prevalence of emerging infectious diseases like the novel coronavirus SARS-CoV-2. This innovative data source can improve the precision of epidemiological modeling to understand the penetrance of SARS-CoV-2 in specific vulnerable communities. Here, we tested wastewater collected at a major urban treatment facility in Massachusetts and detected SARS-CoV-2 RNA from the N gene at significant titers (57 to 303 copies per ml of sewage) in the period from 18 to 25 March 2020 using RT-qPCR. We validated detection of SARS-CoV-2 by Sanger sequencing the PCR product from the S gene. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of 25 March. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks.IMPORTANCE Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is orders of magnitude greater than the number of confirmed clinical cases and therefore may significantly impact efforts to understand the case fatality rate and progression of disease. These data may help inform decisions surrounding the advancement or scale-back of social distancing and quarantine efforts based on dynamic wastewater catchment-level estimations of prevalence.