Epidemiology of the silent polio outbreak in Rahat, Israel, based on modeling of environmental surveillance data

Use of inactivated poliovirus vaccine for poliovirus outbreak response

With continued wild poliovirus transmission in Afghanistan and Pakistan and circulating vaccine-derived poliovirus in certain countries, there exists an ongoing risk of importation of polioviruses into other countries, including those that have been polio-free for decades. Diversifying the poliovirus outbreak response toolkit is essential to account for different public health and epidemiological contexts. In this Personal View, we discuss data on intestinal and pharyngeal mucosal immunity induced by inactivated poliovirus vaccine (IPV), previous programmatic experience of poliovirus outbreak response with IPV, and outbreak response guidelines in countries that exclusively use IPV. With recent reports of poliovirus detection in polio-free countries such as the USA and the UK, it is important to assess the interplay of virus transmission dynamics, vaccine impact on preventing paralysis and virus spread, and regulatory complexities of using oral poliovirus vaccine (OPV) and IPV options for outbreak response. As the global eradication programme navigates through cessation of routine OPV use with replacement by IPV and stockpiling of novel OPVs, clarity on the impact of IPV use will be important for informed decision making by global, regional, and national policy makers.

A comparative analysis of regional infection risk due to wastewater recontamination in the Mezquital Valley, Mexico

Urban wastewater reuse for agriculture provides reliable nutrient-rich water, reduces water stress, and strengthens food systems. However, wastewater reuse also presents health risks and characterizing the spatial dynamics of wastewater can help optimize risk mitigation. We conducted comparative risk analysis of exposure to wastewater in irrigation canals, where we compared those exposed to a) treated vs. untreated wastewater, and b) wastewater upstream vs. downstream from communities in the Mezquital Valley. The canal system with treated wastewater was sampled prior to being treated, directly after treatment, as well as before and after it flowed through a community. Along the canal system that carried untreated wastewater, we sampled before and after a community. We quantified the concentrations of bacterial, protozoal, and viral pathogens in the wastewater. Pathogen concentration data were used to calculate measures of relative risk between sampling points. Wastewater treatment reduced predicted bacterial pathogen infection risk in post-treatment locations (RR = 0.73, 95 % CI 0.61, 0.87), with no evidence of similar reductions in Giardia or viral pathogens (RR = 1.02, 95 % CI 0.56, 1.86 and RR = 1.18, 95 % CI 0.70, 2.02 respectively). Although infection risk decreased further down the canals, infection risk increased for bacterial pathogens after our sentinel community (RR = 1.94, 95 % 1.34, 2.86). For Giardia and viral pathogens infection risk was elevated but not significantly. We found similar evidence for increases in risk when comparing the treated section of the canal system with a canal section whose wastewater was not treated, i.e., the risk benefits of wastewater treatment were lost after our sentinel community for bacteria (RR = 5.27 vs. 2.08 for sampling points before and after our sentinel community respectively) and for Giardia (RR = 6.98 vs. 3.35 respectively). The increase in risk after transit through communities could have resulted from local community recontamination of the treated wastewater stream.

Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology (WBE) for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding WBE for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

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

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

The Israeli health system's rapid responses during the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic posed numerous challenges to health systems around the world. In addressing many of those challenges, Israel responded quite rapidly. While quick action is not an end in it itself, it can be important in responding to disease outbreaks. Some of Israel's rapid responses to the pandemic contributed significantly to population health and provided important learning opportunities for other countries.

MAIN BODY

Some of the most prominent Israeli rapid responses were related to vaccination. Israel led the world in the pace of its initial vaccine rollout, and it was also the first country to approve and administer booster vaccines to broad segments of the population. In addition, Israeli scholars published a series of timely reports analyzing vaccination impact, which informed policy in Israel and other countries. Israel was a rapid responder in additional areas of public health. These include the partial closure of its borders, the adoption of physical distancing measures, the use of digital surveillance technology for contact tracing, the use of wastewater surveillance to monitor viral spread, and the use of vaccine certificates ("green passes") to facilitate a return to routine in the face of the ongoing pandemic. Many factors contributed to Israel's capacity to repeatedly respond rapidly to a broad array of COVID-19 challenges. These include a national health insurance system that promotes public-private coordination, a system of universal electronic health records, a high level of emergency preparedness, a culture of focusing on goal attainment, a culture of innovation, and the presence of a strong scientific community which is highly connected internationally. In addition, some of the rapid responses (e.g., the rapid initial vaccination rollout) facilitated rapid responses in related areas (e.g., the analysis of vaccination impact, the administration of boosters, and the adoption of green passes). While rapid response can contribute to population health and economic resilience, it can also entail costs, risks, and limitations. These include making decisions and acting before all the relevant information is available; deciding without sufficient consideration of the full range of possible effects, costs, and benefits; not providing enough opportunities for the involvement of relevant groups in the decision-making process; and depleting non-renewable resources.

CONCLUSIONS

Based on our findings, we encourage leaders in the Israeli government to ensure that its emergency response system will continue to have the capacity to respond rapidly to large-scale challenges, whether of a military or civilian nature. At the same time, the emergency response systems should develop mechanisms to include more stakeholders in the fast-paced decision-making process and should improve communication with the public. In addition, they should put into place mechanisms for timely reconsideration, adjustment, and-when warranted-reversal of decisions which, while reasonable when reached, turn out to have been ill-advised in the light of subsequent developments and evidence. These mechanisms could potentially involve any or all branches of government, as well as the public, the press, and professional organizations. Our findings also have implications for health system leaders in other countries. The Israeli experience can help them identify key capacities to develop during non-emergency periods, thus positioning themselves to respond more rapidly in an emergency. Finally, health system leaders in other countries could monitor Israel's rapid responses to future global health emergencies and adopt selected actions in their own countries.

An interpretative review of the wastewater-based surveillance of the SARS-CoV-2: where do we stand on its presence and concern?

Wastewater-based epidemiology (WBE) has been used for monitoring infectious diseases like polio, hepatitis, etc. since the 1940s. It is also being used for tracking the SARS-CoV-2 at the population level. This article aims to compile and assess the information for the qualitative and quantitative detection of the SARS-CoV-2 in wastewater. Based on the globally published studies, we highlight the importance of monitoring SARS-CoV-2 presence/detection in the wastewater and concurrently emphasize the development of early surveillance techniques. SARS-CoV-2 RNA sheds in the human feces, saliva, sputum and mucus that ultimately reaches to the wastewater and brings viral RNA into it. For the detection of the virus in the wastewater, different detection techniques have been optimized and are in use. These are based on serological, biosensor, targeted PCR, and next generation sequencing for whole genome sequencing or targeted amplicon sequencing. The presence of the SARS-CoV-2 RNA in wastewater could be used as a potential tool for early detection and devising the strategies for eradication of the virus before it is spread in the community. Additionally, with the right and timely understanding of viral behavior in the environment, an accurate and instructive model that leverages WBE-derived data may be created. This might help with the creation of technological tools and doable plans of action to lessen the negative effects of current viral epidemics or future potential outbreaks on public health and the economy. Further work toward whether presence of viral load correlates with its ability to induce infection, still needs evidence. The current increasing incidences of JN.1 variant is a case in point for continued early detection and surveillance, including wastewater.

Correlation of hepatitis E and rat hepatitis E viruses urban wastewater monitoring and clinical cases

BACKGROUND

Wastewater pathogen monitoring is useful for surveillance of enteric pathogens. Information about the presence of Paslahepevirus balayani (HEV) and emergent Rocahepevirus ratti (RHEV) in untreated water and their correlation with clinical cases is scarce. Aim To longitudinally monitor HEV and RHEV in wastewater and to evaluate their possible correlation with human cases.

METHODS

This study was carried out in the city of Cordoba (southern Spain) from March 2021 to March 2023. HEV and RHEV occurrence were evaluated by PCR in three sample types: i) sera from patients with acute hepatitis attended at the reference hospital, ii) liver and faeces from urban rodents, and iii) grab sewage samples collected weekly from the municipal wastewater treatment plant.

RESULTS

We analysed 106 untreated wastewater samples, 304 individuals with acute hepatitis, and 20 rodents. HEV and RHEV were detected in only one (0.9 %) and almost all samples (94.3 %) of wastewater samples, respectively. A total of 22 cases of acute HEV infection (7.2 %) and two cases of RHEV (0.7 %) were detected from all acute hepatitis cases observed. Only RHEV was found in rodents, with a positive frequency of 55 %. The presence of HEV in wastewater coincided with the detection of one case in which the same HEV genotype was isolated. A concentration of HEV clinical cases between June and July of 2022 was observed but not detected in water. Both RHEV clinical cases were detected in summer 2022, but no correlation was found with wastewater detection.

CONCLUSIONS

Our study shows that there is no correlation between clinical cases and wastewater detection of HEV or RHEV.

Is it time to switch to a formulation other than the live attenuated poliovirus vaccine to prevent poliomyelitis?

The polioviruses (PVs) are mainly transmitted by direct contact with an infected person through the fecal-oral route and respiratory secretions (or more rarely via contaminated water or food) and have a primary tropism for the gut. After their replication in the gut, in rare cases (far less than 1% of the infected individuals), PVs can spread to the central nervous system leading to flaccid paralysis, which can result in respiratory paralysis and death. By the middle of the 20th century, every year the wild polioviruses (WPVs) are supposed to have killed or paralyzed over half a million people. The introduction of the oral poliovirus vaccines (OPVs) through mass vaccination campaigns (combined with better application of hygiene measures), was a success story which enabled the World Health Organization (WHO) to set the global eradication of poliomyelitis as an objective. However this strategy of viral eradication has its limits as the majority of poliomyelitis cases today arise in individuals infected with circulating vaccine-derived polioviruses (cVDPVs) which regain pathogenicity following reversion or recombination. In recent years (between January 2018 and May 2023), the WHO recorded 8.8 times more cases of polio which were linked to the attenuated OPV vaccines (3,442 polio cases after reversion or recombination events) than cases linked to a WPV (390 cases). Recent knowledge of the evolution of RNA viruses and the exchange of genetic material among biological entities of the intestinal microbiota, call for a reassessment of the polio eradication vaccine strategies.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Air travel monitoring does not accelerate outbreak detection in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Simultaneous detection and quantification of multiple pathogen targets in wastewater

Wastewater-based epidemiology has emerged as a critical tool for public health surveillance, building on decades of environmental surveillance work for pathogens such as poliovirus. Work to date has been limited to monitoring a single pathogen or small numbers of pathogens in targeted studies; however, few studies consider simultaneous quantitative analysis of a wide variety of pathogens, which could greatly increase the utility of wastewater surveillance. We developed a novel quantitative multi-pathogen surveillance approach (35 pathogen targets including bacteria, viruses, protozoa, and helminths) using TaqMan Array Cards (TAC) and applied the method on concentrated wastewater samples collected at four wastewater treatment plants in Atlanta, GA from February to October of 2020. From sewersheds serving approximately 2 million people, we detected a wide range of targets including many we expected to find in wastewater (e.g., enterotoxigenic E. coli and Giardia in 97% of 29 samples at stable concentrations) as well as unexpected targets including Strongyloides stercoralis (a human threadworm rarely observed in the USA). Other notable detections included SARS-CoV-2, but also several pathogen targets that are not commonly included in wastewater surveillance like Acanthamoeba spp., Balantidium coli, Entamoeba histolytica, astrovirus, norovirus, and sapovirus. Our data suggest broad utility in expanding the scope of enteric pathogen surveillance in wastewaters, with potential for application in a variety of settings where pathogen quantification in fecal waste streams can inform public health surveillance and selection of control measures to limit infections.

Positive association of SARS-CoV-2 RNA concentrations in wastewater and reported COVID-19 cases in Singapore - A study across three populations

Wastewater testing of SARS-CoV-2 has been adopted globally and has shown to be a useful, non-intrusive surveillance method for monitoring COVID-19 trends. In Singapore, wastewater surveillance has been widely implemented across various sites and has facilitated timely COVID-19 management and response. From April 2020 to February 2022, SARS-CoV-2 RNA concentrations in wastewater monitored across three populations, nationally, in the community, and in High Density Living Environments (HDLEs) were aggregated into indices and compared with reported COVID-19 cases and hospitalisations. Temporal trends and associations of these indices were compared descriptively and quantitatively, using Poisson Generalised Linear Models and Generalised Additive Models. National vaccination rates and vaccine breakthrough infection rates were additionally considered as confounders to shedding. Fitted models quantified the temporal associations between the indices and cases and COVID-related hospitalisations. At the national level, the wastewater index was a leading indicator of COVID-19 cases (p-value <0.001) of one week, and a contemporaneous association with hospitalisations (p-value <0.001) was observed. At finer levels of surveillance, the community index was observed to be contemporaneously associated with COVID-19 cases (p-value <0.001) and had a lagging association of 1-week in HDLEs (p-value <0.001). These temporal differences were attributed to differences in testing routines for different sites during the study period and the timeline of COVID-19 progression in infected persons. Overall, this study demonstrates the utility of wastewater surveillance in understanding underlying COVID-19 transmission and shedding levels, particularly for areas with falling or low case ascertainment. In such settings, wastewater surveillance showed to be a lead indicator of COVID-19 cases. The findings also underscore the potential of wastewater surveillance for monitoring other infectious diseases threats.

Wastewater analysis of Mpox virus in a city with low prevalence of Mpox disease: an environmental surveillance study

Background

Tracking infectious diseases at the community level is challenging due to asymptomatic infections and the logistical complexities of mass surveillance. Wastewater surveillance has emerged as a valuable tool for monitoring infectious disease agents including SARS-CoV-2 and Mpox virus. However, detecting the Mpox virus in wastewater is particularly challenging due to its relatively low prevalence in the community. In this study, we aim to characterize three molecular assays for detecting and tracking the Mpox virus in wastewater from El Paso, Texas, during February and March 2023.

Methods

In this study, a combined approach utilizing three real-time PCR assays targeting the C22L, F3L, and F8L genes and sequencing was employed to detect and track the Mpox virus in wastewater samples. The samples were collected from four sewersheds in the City of El Paso, Texas, during February and March 2023. Wastewater data was compared with reported clinical case data in the city.

Findings

Mpox virus DNA was detected in wastewater from all the four sewersheds, whereas only one Mpox case was reported during the sampling period. Positive signals were still observed in multiple sewersheds after the Mpox case was identified. Higher viral concentrations were found in the pellet than in the supernatant of wastewater. Notably, an increasing trend in viral concentration was observed approximately 1-2 weeks before the reporting of the Mpox case. Further sequencing and epidemiological analysis provided supporting evidence for unreported Mpox infections in the city.

Interpretation

Our analysis suggests that the Mpox cases in the community is underestimated. The findings emphasize the value of wastewater surveillance as a public health tool for monitoring infectious diseases even in low-prevalence areas, and the need for heightened vigilance to mitigate the spread of Mpox disease for safeguarding global health.

Funding

Center of Infectious Diseases at UTHealth, the University of Texas System, and the Texas Epidemic Public Health Institute. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of these funding organizations.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Factors Related to the Compliance of Arab Parents in Israel to the Vaccination of Children and Adolescents against COVID-19

The Arab minority consists of 20% of the Israeli population. Most of the Arab minority live in rural villages, mostly in closed communities, with specific psycho-social and sociodemographic characteristics. Previous studies showed different attitudes to COVID-19 vaccination among Arab adults.

OBJECTIVES

To examine the influence of factors on the willingness of parents to vaccinate their young and adolescent children and if there is a difference between parents' attitudes to both groups.

METHODS AND MATERIALS

The survey examined correlations between variables and attitudes toward the vaccine and the pandemic and was disseminated anonymously to parents of children between the ages of 5 and 18 in the Arab population of Israel through social media networks, using the snowball method. Statistical analyses included the Pearson correlation, MANCOVA, and logistic regression tests.

RESULTS

In total, 361 Arab Israeli parents participated. As mentioned above, 130 parents had both children and adolescents. Overall, 48 parents (36.9%) chose not to vaccinate both their children and adolescents, 52 parents (40.0%) chose to vaccinate only their adolescents, only 1 parent (0.8%) chose to vaccinate only the child, and 29 parents (22.3%) vaccinated both their children and adolescents. Significant correlations were found among a higher age of parents and socioeconomic status, attitudes toward COVID vaccination, subjective norms, perceived severity of the disease, perceived benefits of vaccination, and trust in formal sources.

DISCUSSION

There is a difference between parents' decision to be vaccinated and their willingness to vaccinate their children. There is a difference between their decision to vaccinate their adolescents and their young children. Different factors positively or negatively influenced parents' decisions. Addressing these factors by authorities may increase compliance of Arab minorities with instructions in the future.

Wastewater-based surveillance identifies start to the pediatric respiratory syncytial virus season in two cities in Ontario, Canada

Introduction

Detection of community respiratory syncytial virus (RSV) infections informs the timing of immunoprophylaxis programs and hospital preparedness for surging pediatric volumes. In many jurisdictions, this relies upon RSV clinical test positivity and hospitalization (RSVH) trends, which are lagging indicators. Wastewater-based surveillance (WBS) may be a novel strategy to accurately identify the start of the RSV season and guide immunoprophylaxis administration and hospital preparedness.

Methods

We compared citywide wastewater samples and pediatric RSVH in Ottawa and Hamilton between August 1, 2022, and March 5, 2023. 24-h composite wastewater samples were collected daily and 5 days a week at the wastewater treatment facilities in Ottawa and Hamilton, Ontario, Canada, respectively. RSV WBS samples were analyzed in real-time for RSV by RT-qPCR.

Results

RSV WBS measurements in both Ottawa and Hamilton showed a lead time of 12 days when comparing the WBS data set to pediatric RSVH data set (Spearman's ρ = 0.90). WBS identify early RSV community transmission and declared the start of the RSV season 36 and 12 days in advance of the provincial RSV season start (October 31) for the city of Ottawa and Hamilton, respectively. The differing RSV start dates in the two cities is likely associated with geographical and regional variation in the incidence of RSV between the cities.

Discussion

Quantifying RSV in municipal wastewater forecasted a 12-day lead time of the pediatric RSVH surge and an earlier season start date compared to the provincial start date. These findings suggest an important role for RSV WBS to inform regional health system preparedness, reduce RSV burden, and understand variations in community-related illness as novel RSV vaccines and monoclonal antibodies become available.

Monkeypox viral nucleic acids detected using both DNA and RNA extraction workflows

Molecular methods have been used to detect human pathogens in wastewater with sampling typically performed at wastewater treatment plants (WWTP) and upstream locations within the sewer system. A wastewater-based surveillance (WBS) program was established at the University of Miami (UM) in 2020, which included measurements of SARS-CoV-2 levels in wastewater from its hospital and within the regional WWTP. In addition to the development of a SARS-CoV-2 quantitative PCR (qPCR) assay, qPCR assays to detect other human pathogens of interest were also developed at UM. Here we report on the use of a modified set of reagents published by the CDC to detect nucleic acids of Monkeypox virus (MPXV) which emerged during May of 2022 to become a concern worldwide. Samples collected from the University hospital and from the regional WWTP were processed through DNA and RNA workflows and analyzed by qPCR to detect a segment of the MPXV CrmB gene. Results show positive detections of MPXV nucleic acids in the hospital and wastewater treatment plant wastewater which coincided with clinical cases in the community and mirrored the overall trend of nationwide MPXV cases reported to the CDC. We recommend the expansion of current WBS programs' methods to detect a broader range of pathogens of concern in wastewater and present evidence that viral RNA in human cells infected by a DNA virus can be detected in wastewater.

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.

Wastewater Monitoring for Infectious Disease: Intentional Relationships between Academia, the Private Sector, and Local Health Departments for Public Health Preparedness

The public health emergency caused by the COVID-19 pandemic stimulated stakeholders from diverse disciplines and institutions to establish new collaborations to produce informed public health responses to the disease. Wastewater-based epidemiology for COVID-19 grew quickly during the pandemic and required the rapid implementation of such collaborations. The objective of this article is to describe the challenges and results of new relationships developed in Detroit, MI, USA among a medical school and an engineering college at an academic institution (Wayne State University), the local health department (Detroit Health Department), and an environmental services company (LimnoTech) to utilize markers of the COVID-19 virus, SARS-CoV-2, in wastewater for the goal of managing COVID-19 outbreaks. Our collaborative team resolved questions related to sewershed selection, communication of results, and public health responses and addressed technical challenges that included ground-truthing the sewer maps, overcoming supply chain issues, improving the speed and sensitivity of measurements, and training new personnel to deal with a new disease under pandemic conditions. Recognition of our complementary roles and clear communication among the partners enabled city-wide wastewater data to inform public health responses within a few months of the availability of funding in 2020, and to make improvements in sensitivity and understanding to be made as the pandemic progressed and evolved. As a result, the outbreaks of COVID-19 in Detroit in fall and winter 2021-2022 (corresponding to Delta and Omicron variant outbreaks) were tracked in 20 sewersheds. Data comparing community- and hospital-associated sewersheds indicate a one- to two-week advance warning in the community of subsequent peaks in viral markers in hospital sewersheds. The new institutional relationships impelled by the pandemic provide a good basis for continuing collaborations to utilize wastewater-based human and pathogen data for improving the public health in the future.

Long-term study on wastewater SARS-CoV-2 surveillance across United Arab Emirates

Wastewater-based epidemiology (WBE) demonstrates an efficient tool to monitor and predict SARS-CoV-2 community distribution. Many countries across the world have adopted the technique, however, most of these studies were conducted for a short duration with a limited sampling size. In this study, long-term reliability and quantification of wastewater SARS-CoV-2 surveillance is reported via analyzing 16,858 samples collected from 453 different locations across the United Arab Emirates (UAE) from May 2020 to June 2022. The collected composite samples were first incubated at 60 °C followed by filtration, concentration, and then RNA extraction using commercially available kits. The extracted RNA was then analyzed by one-step RT-qPCR and RT-ddPCR, and the data was compared to the reported clinical cases. The average positivity rate in the wastewater samples was found to be 60.61 % (8.41-96.77 %), however, the positivity rate obtained from the RT-ddPCR was significantly higher than the RT-qPCR suggesting higher sensitivity of RT-ddPCR. Time-lagged correlation analysis indicated an increase in positive cases in the wastewater samples when the clinical positive cases declined suggesting that wastewater data are highly affected by the unreported asymptomatic, pre-symptomatic and recovering individuals. The weekly SARS-CoV-2 viral count in the wastewater samples are positively correlated with the diagnosed new clinical cases throughout the studied period and the studied locations. Viral count in wastewater peaked approximately one to two weeks prior to the peaks appearing in active clinical cases indicating that wastewater viral concentrations are effective in predicting clinical cases. Overall, this study further confirms the long-term sensitivity and robust approach of WBE to detect trends in SARS-CoV-2 spread and helps contribute to pandemic management.

Exploring the role of wastewater-based epidemiology in understanding tuberculosis burdens in Africa

Tuberculosis (TB) remains a persistent challenge to public health and presents a substantial menace, especially in developing nations of sub-Saharan Africa. It exerts a considerable strain on healthcare systems in these regions. Effective control requires reliable surveillance, which can be improved by incorporating environmental data alongside clinical data. Molecular advances have led to the development of alternative surveillance methods, such as wastewater-based epidemiology. This studyinvestigated the presence, concentration, and diversity of Mycobacterium tuberculosis complex, the cause of TB, in from six African countries: Ghana, Nigeria, Kenya, Uganda, Cameroon, and South Africa. Samples were collected from wastewater treatment plants. All samples were found to contain Mycobacterium species that have been linked to TB in both humans and animals, including Mycobacterium tuberculosis complex, Mycobacterium tuberculosis, Mycobacterium bovis, Mycobacterium africanum, and Mycobacterium caprae, at varying concentrations. The highest median concentration was found in Ghana, reaching up to 4.7 Log copies/ml for MTBC, 4.6 Log copies/ml for M. bovis, and 3.4 Log copies/ml for M. africanum. The presence of M. africanum outside of West Africa was found in South Africa, Kenya, and Uganda and could indicate the spread of the pathogen. The study underscores the usefulness of wastewater-based epidemiology for tracking TB and shows that even treated wastewater may contain these pathogens, posing potential public health risks.

Zika virus RNA persistence and recovery in water and wastewater: An approach for Zika virus surveillance in resource-constrained settings

During the 2015-2016 Zika virus (ZIKV) epidemic in the Americas, serological cross-reactivity with other flaviviruses and relatively high costs of nucleic acid testing in the region hindered the capacity for widespread diagnostic testing. In such cases where individual testing is not feasible, wastewater monitoring approaches may offer a means of community-level public health surveillance. To inform such approaches, we characterized the persistence and recovery of ZIKV RNA in experiments where we spiked cultured ZIKV into surface water, wastewater, and a combination of both to examine the potential for detection in open sewers serving communities most affected by the ZIKV outbreak, such as those in Salvador, Bahia, Brazil. We used reverse transcription droplet digital PCR to quantify ZIKV RNA. In our persistence experiments, we found that the persistence of ZIKV RNA decreased with increasing temperature, significantly decreased in surface water versus wastewater, and significantly decreased when the initial concentration of virus was lowered by one order of magnitude. In our recovery experiments, we found higher percent recovery of ZIKV RNA in pellets versus supernatants from the same sample, higher recoveries in pellets using skimmed milk flocculation, lower recoveries of ZIKV RNA in surface water versus wastewater, and lower recoveries from a freeze thaw. We also analyzed samples collected from Salvador, Brazil during the ZIKV outbreak (2015-2016) that consisted of archived samples obtained from open sewers or environmental waters thought to be contaminated by sewage. Although we did not detect any ZIKV RNA in the archived Brazil samples, results from these persistence and recovery experiments serve to inform future wastewater monitoring efforts in open sewers, an understudied and important application of wastewater monitoring.

Human viral nucleic acids concentrations in wastewater solids from Central and Coastal California USA

We measured concentrations of SARS-CoV-2, influenza A and B virus, respiratory syncytial virus (RSV), mpox virus, human metapneumovirus, norovirus GII, and pepper mild mottle virus nucleic acids in wastewater solids at twelve wastewater treatment plants in Central California, USA. Measurements were made daily for up to two years, depending on the wastewater treatment plant. Measurements were made using digital droplet (reverse-transcription-) polymerase chain reaction (RT-PCR) following best practices for making environmental molecular biology measurements. These data can be used to better understand disease occurrence in communities contributing to the wastewater.

Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain

Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 10³ and 10⁶ SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.

SARS-CoV-2 detection and inactivation in water and wastewater: Review on analytical methods, limitations and future research recommendations

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in wastewater. Wastewater-based epidemiology (WBE) is a practical and cost-effective tool for the assessment and controlling of pandemics and probably for examining SARS-CoV-2 presence. Implementation of WBE during the outbreaks is not without limitations. Temperature, suspended solids, pH, and disinfectants affect the stability of viruses in wastewater. Due to these limitations, instruments and techniques have been utilized to detect SARS-CoV-2. SARS-CoV-2 has been detected in sewage using various concentration methods and computer-aided analyzes. RT-qPCR, ddRT-PCR, multiplex PCR, RT-LAMP, and electrochemical immunosensors have been employed to detect low levels of viral contamination. Inactivation of SARS-CoV-2 is a crucial preventive measure against coronavirus disease 2019 (COVID-19). To better assess the role of wastewater as a transmission route, detection, and quantification methods need to be refined. In this paper, the latest improvements in quantification, detection, and inactivation of SARS-CoV-2 in wastewater are explained. Finally, limitations and future research recommendations are thoroughly described.

Oral and fecal polio vaccine excretion following bOPV vaccination among Israeli infants

INTRODUCTION

Inactivated polio virus (IPV) vaccinations are a mainstay of immunization schedules in developed countries, while oral polio vaccine (OPV) is administered in developing countries and is the main vaccine in outbreaks. Due to circulating wild poliovirus (WPV1) detection in Israel (2013), oral bivalent polio vaccination (bOPV) was administered to IPV primed children and incorporated into the vaccination regimen.

OBJECTIVES

We aimed to determine the extent and timeframe of fecal and salivary polio vaccine virus (Sabin strains) shedding following bOPV vaccination among IPV primed children.

METHODS

Fecal samples were collected from a convenience sample of infants and toddlers attending 11 Israeli daycare centers. Salivary samples were collected from infants and toddlers following bOPV vaccination.

RESULTS

398 fecal samples were collected from 251 children (ages: 6-32 months), 168 received bOPV vaccination 4-55 days prior to sample collection. Fecal excretion continued among 80 %, 50 %, and 20 %, 2, 3, and 7 weeks following vaccination. There were no significant differences in the rate and duration of positive samples among children immunized with 3 or 4 IPV doses. Boys were 2.3-fold more likely to excrete the virus (p = 0.006). Salivary shedding of Sabin strains occurred in 1/47 (2 %) and 1/49 (2 %) samples 4, and 6 days following vaccination respectively.

CONCLUSIONS

Fecal detection of Sabin strains among IPV-primed children continues for 7 weeks; additional doses of IPV do not augment intestinal immunity; limited salivary shedding occurs for up to a week. This data can enhance understanding of intestinal immunity achieved by different vaccination schedules and guide recommendations for contact precautions of children following bOPV vaccination.

Taking on Typhoid: Eliminating Typhoid Fever as a Global Health Problem

Typhoid fever is a significant global health problem that impacts people living in areas without access to clean water and sanitation. However, collaborative international partnerships and new research have improved both knowledge of the burden in countries with endemic disease and the tools for improved surveillance, including environmental surveillance. Two typhoid conjugate vaccines (TCVs) have achieved World Health Organization prequalification, with several more in the development pipeline. Despite hurdles posed by the coronavirus disease 2019 pandemic, multiple TCV efficacy trials have been conducted in high-burden countries, and data indicate that TCVs provide a high degree of protection from typhoid fever, are safe to use in young children, provide lasting protection, and have the potential to combat typhoid antimicrobial resistance. Now is the time to double down on typhoid control and elimination by sustaining progress made through water, sanitation, and hygiene improvements and accelerating TCV introduction in high-burden locations.

Wastewater Surveillance Can Function as an Early Warning System for COVID-19 in Low-Incidence Settings

Introduction: During the first two years of the COVID-19 pandemic, Australia implemented a series of international and interstate border restrictions. The state of Queensland experienced limited COVID-19 transmission and relied on lockdowns to stem any emerging COVID-19 outbreaks. However, early detection of new outbreaks was difficult. In this paper, we describe the wastewater surveillance program for SARS-CoV-2 in Queensland, Australia, and report two case studies in which we aimed to assess the potential for this program to provide early warning of new community transmission of COVID-19. Both case studies involved clusters of localised transmission, one originating in a Brisbane suburb (Brisbane Inner West) in July–August 2021, and the other originating in Cairns, North Queensland in February–March 2021. Materials and Methods: Publicly available COVID-19 case data derived from the notifiable conditions (NoCs) registry from the Queensland Health data portal were cleaned and merged spatially with the wastewater surveillance data using statistical area 2 (SA2) codes. The positive predictive value and negative predictive value of wastewater detection for predicting the presence of COVID-19 reported cases were calculated for the two case study sites. Results: Early warnings for local transmission of SARS-CoV-2 through wastewater surveillance were noted in both the Brisbane Inner West cluster and the Cairns cluster. The positive predictive value of wastewater detection for the presence of notified cases of COVID-19 in Brisbane Inner West and Cairns were 71.4% and 50%, respectively. The negative predictive value for Brisbane Inner West and Cairns were 94.7% and 100%, respectively. Conclusions: Our findings highlight the utility of wastewater surveillance as an early warning tool in low COVID-19 transmission settings.

Wastewater concentrations of human influenza, metapneumovirus, parainfluenza, respiratory syncytial virus, rhinovirus, and seasonal coronavirus nucleic-acids during the COVID-19 pandemic: a surveillance study

BACKGROUND

Respiratory disease is a major cause of morbidity and mortality; however, surveillance for circulating respiratory viruses is passive and biased. Wastewater-based epidemiology has been used to understand SARS-CoV-2, influenza A, and respiratory syncytial virus (RSV) infection rates at a community level but has not been used to investigate other respiratory viruses. We aimed to use wastewater-based epidemiology to understand community viral respiratory infection occurrence.

METHODS

A retrospective wastewater-based epidemiology surveillance study was carried out at a large wastewater treatment plant located in California, USA. Using droplet digital RT-PCR, we measured RNA concentrations of influenza A and influenza B viruses, RSV A and RSV B, parainfluenza (1-4) viruses, rhinovirus, seasonal coronaviruses, and metapneumovirus in wastewater solids three times per week for 17 months (216 samples) between Feb 1, 2021, and June 21, 2022. Novel probe-based RT-PCR assays for non-influenza viral targets were developed and validated. We compared viral RNA concentrations to positivity rates for viral infections from clinical specimens submitted to California Sentinel Clinical Laboratories (sentinel laboratories) to assess concordance between the two datasets.

FINDINGS

We detected RNA from all tested viruses in wastewater solids. Human rhinovirus (median concentration 4300 [0-9500] copies per gram dry weight) and seasonal human coronaviruses (35 000 [17 000-56 000]) were found at the highest concentrations. Concentrations of viral RNA correlated significantly and positively with positivity rates of associated viral diseases from sentinel laboratories (tau 0·32-0·57, p<0·0009); the only exceptions were influenza B and RSV A, which were rarely detected in wastewater solids. Measurements from wastewater indicated coronavirus OC43 dominated the seasonal human coronavirus infections whereas parainfluenza 3 dominated among parainfluenza infections during the study period. Concentrations of all tested viral RNA decreased noticeably after the omicron BA.1 surge suggesting a connection between changes in human behaviour during the surge and transmission of all respiratory viruses.

INTERPRETATION

Wastewater-based epidemiology can be used to obtain information on circulation of respiratory viruses at a localised, community level without the need to test many individuals because a single sample of wastewater represents the entire contributing community. Results from wastewater can be available within 24 h of sample collection, generating real time information to inform public health responses, clinical decision making, and individual behaviour modifications.

FUNDING

CDC Foundation.

Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America - Lessons from the past and a look to the future

Wastewater-based epidemiology (WBE) is an approach with the potential to complement clinical surveillance systems. Using WBE, it is possible to carry out an early warning of a possible outbreak, monitor spatial and temporal trends of infectious diseases, produce real-time results and generate representative epidemiological information in a territory, especially in areas of social vulnerability. Despite the historical uses of this approach, particularly in the Global Polio Eradication Initiative, and for other pathogens, it was during the COVID-19 pandemic that occurred an exponential increase in environmental surveillance programs for SARS-CoV-2 in wastewater, with many experiences and developments in the field of public health using data for decision making and prioritizing actions to control the pandemic. In Latin America, WBE was applied in heterogeneous contexts and with emphasis on populations that present many socio-environmental inequalities, a condition shared by all Latin American countries. This manuscript addresses the concepts and applications of WBE in public health actions, as well as different experiences in Latin American countries, and discusses a model to implement this surveillance system at the local or national level. We emphasize the need to implement this sentinel surveillance system in countries that want to detect the early entry and spread of new pathogens and monitor outbreaks or epidemics of infectious agents in their territories as a complement of public health surveillance systems.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

COPMAN: A novel high-throughput and highly sensitive method to detect viral nucleic acids including SARS-CoV-2 RNA in wastewater

During the coronavirus disease 2019 (COVID-19) pandemic, wastewater-based epidemiology (WBE) attracted attention as an objective and comprehensive indicator of community infection that does not require individual inspection. Although several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection methods from wastewater have been developed, there are obstacles to their social implementation. In this study, we developed the COPMAN (Coagulation and Proteolysis method using Magnetic beads for detection of Nucleic acids in wastewater), an automatable method that can concentrate and detect multiple types of viruses from a limited volume (∼10 mL) of wastewater. The COPMAN consists of a high basicity polyaluminum chloride (PAC) coagulation process, magnetic bead-based RNA purification, and RT-preamplification, followed by qPCR. A series of enzymes exhibiting a high tolerance to PCR inhibitors derived from wastewater was identified and employed in the molecular detection steps in the COPMAN. We compared the detectability of viral RNA from 10-mL samples of virus-spiked (heat-inactivated SARS-CoV-2 and intact RSV) or unspiked wastewater by the COPMAN and other methods (PEG-qPCR, UF-qPCR, and EPISENS-S). The COPMAN was the most efficient for detecting spiked viruses from wastewater, detecting the highest level of pepper mild mottle virus (PMMoV), a typical intrinsic virus in human stool, from wastewater samples. The COPMAN also successfully detected indigenous SARS-CoV-2 RNA from 12 samples of wastewater at concentrations of 2.2 × 10⁴ to 5.4 × 10⁵ copies/L, during initial stages of an infection wave in the right and the left bank of the Sagami River in Japan (0.65 to 11.45 daily reported cases per 100,000 people). These results indicate that the COPMAN is suitable for detection of multiple pathogens from small volume of wastewater in automated stations.

A Framework for Public Health Authorities to Evaluate Health Determinants for Wastewater-Based Epidemiology

BACKGROUND

Wastewater-based epidemiology (WBE) is rapidly developing as a powerful public health tool. It can provide information about a wide range of health determinants (HDs), including community exposure to environmental hazards, trends in consumption of licit and illicit substances, spread of infectious diseases, and general community health. As such, the list of possible candidate HDs for WBE is almost limitless. Consequently, a means to evaluate and prioritize suitable candidates for WBE is useful, particularly for public health authorities, who often face resource constraints.

OBJECTIVES

We have developed a framework to assist public health authorities to decide what HDs may be appropriate for WBE and what biomarkers could be used. This commentary reflects the experience of the authors, who work at the interface of research and public health implementation.

DISCUSSION

To be suitable for WBE, a candidate HD should address a public health or scientific issue that would benefit from better understanding at the population level. For HDs where information on individual exposures or stratification by population subgroups is required, WBE is less suitable. Where other methodologies are already used to monitor the candidate HD, consideration must be given to whether WBE could provide better or complementary information to the current approach. An essential requirement of WBE is a biomarker specific for the candidate HD. A biomarker in this context refers to any human-excreted chemical or biological that could act as an indicator of consumption or exposure to an environmental hazard or of the human health state. Suitable biomarkers should meet several criteria outlined in this commentary, which requires background knowledge for both the biomarker and the HD. An evaluation tree summarizing key considerations for public health authorities when assessing the suitability of candidate HDs for WBE and an example evaluation are presented. https://doi.org/10.1289/EHP11115.

Structural identifiability of compartmental models for infectious disease transmission is influenced by data type

If model identifiability is not confirmed, inferences from infectious disease transmission models may not be reliable, so they might result in misleading recommendations. Structural identifiability analysis characterises whether it is possible to obtain unique solutions for all unknown model parameters, given the model structure. In this work, we studied the structural identifiability of some typical deterministic compartmental models for infectious disease transmission, focusing on the influence of the data type considered as model output on the identifiability of unknown model parameters, including initial conditions. We defined 26 model versions, each having a unique combination of underlying compartmental structure and data type(s) considered as model output(s). Four compartmental model structures and three common data types in disease surveillance (incidence, prevalence and detected vector counts) were studied. The structural identifiability of some parameters varied depending on the type of model output. In general, models with multiple data types as outputs had more structurally identifiable parameters, than did models with a single data type as output. This study highlights the importance of a careful consideration of data types as an integral part of the inference process with compartmental infectious disease transmission models.

Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR

Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. Standard processes for purifying viral RNA from municipal wastewater are often time-consuming and require the handling of large quantities of wastewater, negatively affecting throughput, timely reporting, and safety. We demonstrate here an automated, faster system to purify viral RNA from smaller volumes of wastewater but with increased sensitivity for detection of SARS-CoV-2 markers. We document the effectiveness of this new approach by way of comparison to the PEG/NaCl/Qiagen method prescribed by the State of Michigan for SARS-CoV-2 wastewater monitoring and show its application to several Detroit sewersheds. Specifically, compared to the PEG/NaCl/Qiagen method, viral RNA purification using the PerkinElmer Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by ten-fold, increased the amount of RNA isolated per μl of final elution product by approximately five-fold, and effectively removed ddPCR inhibitors from most sewershed samples. For detection of markers on the borderline of viral detectability, we found that use of the Chemagic™ 360 enabled the measurement of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. The improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak. Applied to sewersheds in Detroit, the technique enabled more sensitive detection of SARS-CoV-2 markers with good correlation between wastewater signals and COVID-19 cases in the sewersheds. We also discuss advantages and disadvantages of several automated RNA purification systems, made by Promega, PerkinElmer, and ThermoFisher.

Modeling approaches for early warning and monitoring of pandemic situations as well as decision support

The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare systems against pandemic situations. In response, many population-level computational modeling approaches have been proposed for predicting outbreaks, spatiotemporally forecasting disease spread, and assessing as well as predicting the effectiveness of (non-) pharmaceutical interventions. However, in several countries, these modeling efforts have only limited impact on governmental decision-making so far. In light of this situation, the review aims to provide a critical review of existing modeling approaches and to discuss the potential for future developments.

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.

Wastewater-Based Surveillance Is an Effective Tool for Trending COVID-19 Prevalence in Communities: A Study of 10 Major Communities for 17 Months in Alberta

The correlations between SARS-CoV-2 RNA levels in wastewater from 12 wastewater treatment plants and new COVID-19 cases in the corresponding sewersheds of 10 communities were studied over 17 months. The analysis from the longest continuous surveillance reported to date revealed that SARS-CoV-2 RNA levels correlated well with temporal changes of COVID-19 cases in each community. The strongest correlation was found during the third wave (r = 0.97) based on the population-weighted SARS-CoV-2 RNA levels in wastewater. Different correlations were observed (r from 0.51 to 0.86) in various sizes of communities. The population in the sewershed had no observed effects on the strength of the correlation. Fluctuation of SARS-CoV-2 RNA levels in wastewater mirrored increases and decreases of COVID-19 cases in the corresponding community. Since the viral shedding to sewers from all infected individuals is included, wastewater-based surveillance provides an unbiased and no-discriminate estimation of the prevalence of COVID-19 compared with clinical testing that was subject to testing-seeking behaviors and policy changes. Wastewater-based surveillance on SARS-CoV-2 represents a temporal trend of COVID-19 disease burden and is an effective and supplementary monitoring when the number of COVID-19 cases reaches detectable thresholds of SARS-CoV-2 RNA in wastewater of treatment facilities serving various sizes of populations.

Relationships between SARS-CoV-2 in Wastewater and COVID-19 Clinical Cases and Hospitalizations, with and without Normalization against Indicators of Human Waste

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.

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.

Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposal

Wastewater-based epidemiology (WBE) is drawing increasing attention as a promising tool for an early warning of emerging infectious diseases such as COVID-19. This study demonstrated the utility of a spatial bisection method (SBM) and a global optimization algorithm (i.e., genetic algorithm, GA), to support better designing and operating a WBE program for disease surveillance and source identification. The performances of SBM and GA were compared in determining the optimal locations of sewer monitoring manholes to minimize the difference among the effective spatial monitoring scales of the selected manholes. While GA was more flexible in determining the spatial resolution of the monitoring areas, SBM allows stepwise selection of optimal sampling manholes with equiareal subcatchments and lowers computational cost. Upon detecting disease outbreaks at a regular sewer monitoring site, additional manholes within the catchment can be selected and monitored to identify source areas with a required spatial resolution. SBM offered an efficient method for rapidly searching for the optimal locations of additional sampling manholes to identify the source areas. This study provides strategic and technical elements of WBE including sampling site selection with required spatial resolution and a source identification method.

Wastewater Surveillance for Infectious Disease: A Systematic Review

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been shown to be a valuable source of information regarding SARS-CoV-2 transmission and coronavirus disease 2019 (COVID-19) cases. Although the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens that have been surveilled through wastewater. Herein we identify the infectious diseases that have been previously studied via wastewater surveillance prior to the COVID-19 pandemic. Infectious diseases and pathogens were identified in 100 studies of wastewater surveillance across 38 countries, as were themes of how wastewater surveillance and other measures of disease transmission were linked. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and nonpolio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did, the value reported varied by study. Wastewater surveillance should be considered as a potential public health tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.

Predictive values of time-dense SARS-CoV-2 wastewater analysis in university campus buildings

Wastewater-based SARS-CoV-2 surveillance on college campuses has the ability to detect individual clinical COVID-19 cases at the building-level. High concordance of wastewater results and clinical cases has been observed when calculated over a time window of four days or longer and in settings with high incidence of infection. At Duke University, twice a week clinical surveillance of all resident undergraduates was carried out in the spring 2021 semester. We conducted simultaneous wastewater surveillance with daily frequency on selected residence halls to assess wastewater as an early warning tool during times of low transmission with the hope of scaling down clinical test frequency. We evaluated the temporal relationship of the two time-dense data sets, wastewater and clinical, and sought a strategy to achieve the highest wastewater predictive values using the shortest time window to enable timely intervention. There were 11 days with clinical cases in the residence halls (80-120 occupants) under wastewater surveillance with 5 instances of a single clinical case and 3 instances of two clinical cases which also corresponded to a positive wastewater SARS-CoV-2 signal. While the majority (71%) of our wastewater samples were negative for SARS-CoV-2, 29% resulted in at least one positive PCR signal, some of which did not correlate with an identified clinical case. Using a criteria of two consecutive days of positive wastewater signals, we obtained a positive predictive value (PPV) of 75% and a negative predictive value of 87% using a short 2 day time window for agreement. A conventional concordance over a much longer 4 day time window resulted in PPV of only 60%. Our data indicated that daily wastewater collection and using a criteria of two consecutive days of positive wastewater signals was the most predictive approach to timely early warning of COVID-19 cases at the building level.

Why the Spectral Radius? An intuition-building introduction to the basic reproduction number

The basic reproduction number [Formula: see text] is a fundamental concept in mathematical epidemiology and infectious disease modeling. Loosely speaking, it describes the number of people that an infectious person is expected to infect. The basic reproduction number has profound implications for epidemic trajectories and disease control strategies. It is well known that the basic reproduction number can be calculated as the spectral radius of the next generation matrix, but why this is the case may not be intuitively obvious. Here, we walk through how the discrete, next generation process connects to the ordinary differential equation disease system of interest, linearized at the disease-free equilibrium. Then, we use linear algebra to develop a geometric explanation of why the spectral radius of the next generation matrix is an epidemic threshold. Finally, we work through a series of examples that help to build familiarity with the kinds of patterns that arise in parameter combinations produced by the next generation method. This article is intended to help new infectious disease modelers develop intuition for the form and interpretation of the basic reproduction number in their disease systems of interest.

Comparison of virus concentration methods and RNA extraction methods for SARS-CoV-2 wastewater surveillance

Wastewater surveillance is a promising tool for population-level monitoring of the spread of infectious diseases, such as the coronavirus disease 2019 (COVID-19). Different from clinical specimens, viruses in community-scale wastewater samples need to be concentrated before detection because viral RNA is highly diluted. The present study evaluated eleven different virus concentration methods for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. First, eight concentration methods of different principles were compared using spiked wastewater at a starting volume of 30 mL. Ultracentrifugation was the most effective method with a viral recovery efficiency of 25 ± 6%. The second-best option, AlCl₃ precipitation method, yielded a lower recovery efficiency, only approximately half that of the ultracentrifugation method. Second, the potential of increasing method sensitivity was explored using three concentration methods starting with a larger volume of 1000 mL. Although ultracentrifugation using a large volume outperformed the other two large-volume methods, it only yielded a comparable method sensitivity as the ultracentrifugation using a small volume (30 mL). Thus, ultracentrifugation using less volume of wastewater is more preferable considering the sample processing throughput. Third, a comparison of two viral RNA extraction methods showed that the lysis-buffer-based extraction method resulted in higher viral recovery efficiencies, with cycle threshold (Ct) values 0.9-4.2 lower than those obtained for the acid-guanidinium-phenol-based method using spiked samples. These results were further confirmed by using positive wastewater samples concentrated by ultracentrifugation and extracted separately by the two viral RNA extraction methods. In summary, concentration using ultracentrifugation followed by the lysis buffer-based extraction method enables sensitive and robust detection of SARS-CoV-2 for wastewater surveillance.

Sampling strategies for wastewater surveillance: Evaluating the variability of SARS-COV-2 RNA concentration in composite and grab samples

The shedding of SARS-CoV-2 RNA titers by infected individuals, even asymptomatic and oligosymptomatic ones, allows the use of wastewater monitoring to track the COVID-19 spread in a community. This approach is interesting especially for emerging countries with limited clinical testing capabilities. However, there are still important methodological aspects that need validation so that wastewater monitoring data become more representative and useful for public health. This study evaluated the between-day and within-day variability of SARS-CoV-2 RNA concentrations in 24-hour composite and grab samples from three different sampling points, including two wastewater treatment plants (WTTP) and a sewer manhole. In the between-day evaluation (17 weeks of monitoring), a good agreement between the SARS-CoV-2 RNA concentration of each sampling method was observed. There were no significant differences between the mean concentrations of the grab and composite samples (p-value > 0.05), considering N1 and N2 gene assays. The strong relationship between composite and grab samples was proven by correlation coefficients: Pearson's r of 0.83 and Spearman's rho of 0.78 (p-value < 0.05). In within-day evaluation, 24-hour cycles were analyzed and low variability in hourly viral concentrations was observed for three sampling points. The coefficient of variation (CV) values ranged from 3.0% to 11.5%. Overall, 24-hour profiles showed that viral RNA concentrations had less variability and greater agreement with the mean values between 8 a.m. and 10 a.m, the recommended time for grab sampling. Therefore, this study provides important information on wastewater sampling techniques for COVID-19 surveillance. Wastewater monitoring information will only be useful to public health and decision-makers if we ensure data quality through best practices.

A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities

The COVID-19 pandemic has stimulated wastewater-based surveillance, allowing public health to track the epidemic by monitoring the concentration of the genetic fingerprints of SARS-CoV-2 shed in wastewater by infected individuals. Wastewater-based surveillance for COVID-19 is still in its infancy. In particular, the quantitative link between clinical cases observed through traditional surveillance and the signals from viral concentrations in wastewater is still developing and hampers interpretation of the data and actionable public-health decisions. We present a modelling framework that includes both SARS-CoV-2 transmission at the population level and the fate of SARS-CoV-2 RNA particles in the sewage system after faecal shedding by infected persons in the population. Using our mechanistic representation of the combined clinical/wastewater system, we perform exploratory simulations to quantify the effect of surveillance effectiveness, public-health interventions and vaccination on the discordance between clinical and wastewater signals. We also apply our model to surveillance data from three Canadian cities to provide wastewater-informed estimates for the actual prevalence, the effective reproduction number and incidence forecasts. We find that wastewater-based surveillance, paired with this model, can complement clinical surveillance by supporting the estimation of key epidemiological metrics and hence better triangulate the state of an epidemic using this alternative data source.

Effect of Population Partitioning on the Probability of Silent Circulation of Poliovirus

Polio can circulate unobserved in regions that are challenging to monitor. To assess the probability of silent circulation, simulation models can be used to understand transmission dynamics when detection is unreliable. Model assumptions, however, impact the estimated probability of silent circulation. Here, we examine the impact of having distinct populations, rather than a single well-mixed population, with a discrete-individual model including environmental surveillance. We show that partitioning a well-mixed population into networks of distinct communities may result in a higher probability of silent circulation as a result of the time it takes for the detection of a circulation event. Population structure should be considered when assessing polio control in a region with many loosely interacting communities.