Wastewater surveillance of SARS-CoV-2 and influenza in preK-12 schools shows school, community, and citywide infections

Wastewater threshold as an indicator of COVID-19 cases in correctional facilities for public health response: A modeling study

Although prison facilities are not fully isolated from the communities in which they are located, most of the population is confined and requires high levels of health vigilance and protection. This study aimed to examine the dynamic relationship between facility-level wastewater viral concentrations and the probability of at least one positive COVID-19 case within the facility. The study period was from January 11, 2021 to May 8, 2023. Wastewater samples were collected and analyzed for SARS-CoV-2 (N1) and pepper mild mottle virus (PMMoV) three times weekly across 14 prison facilities in Kentucky (USA). Positive clinical case reports were also provided. A hierarchical Bayesian facility-level temporal model with a latent lagged process was developed. We modeled facility-specific SARS-CoV-2 (N1) normalized by the PMMoV wastewater concentration ratio threshold associated with at least one COVID-19 clinical case at an 80 % probability. The threshold differed among facilities. Across the 14 facilities, our model demonstrates a mean capture rate of 94.95 % via the N1/PMMoV ratio threshold with pts≥0.5. However, as the pts threshold was set higher, such as at ≥0.9, the mean capture rate of the model was reduced to 60 %. This robust performance underscores the effectiveness of the model for accurately detecting the presence of positive COVID-19 cases among incarcerated people. The findings of this study provide a facility-specific threshold model for public health response based on frequent wastewater surveillance.

PreK-12 school and citywide wastewater monitoring of the enteric viruses astrovirus, rotavirus, and sapovirus

Wastewater monitoring is an efficient and effective way to surveil for various pathogens in communities. This is especially beneficial in areas of high transmission, such as preK-12 schools, where infections may otherwise go unreported. In this work, we apply wastewater disease surveillance using school and community wastewater from across Houston, Texas to monitor three major enteric viruses: astrovirus, sapovirus genogroup GI, and group A rotavirus. We present the results of a 10-week study that included the analysis of 164 wastewater samples for astrovirus, rotavirus, and sapovirus in 10 preK-12 schools, 6 wastewater treatment plants, and 2 lift stations using newly designed RT-ddPCR assays. We show that the RT-ddPCR assays were able to detect astrovirus, rotavirus, and sapovirus in school, lift station, and wastewater treatment plant (WWTP) wastewater, and that a positive detection of a virus in a school sample was paired with a positive detection of the same virus at a downstream lift station or wastewater treatment plant over 97 % of the time. Additionally, we show how wastewater detections of rotavirus in schools and WWTPs were significantly associated with citywide viral intestinal infections. School wastewater can play a role in the monitoring of enteric viruses and in the detection of outbreaks, potentially allowing public health officials to quickly implement mitigation strategies to prevent viral spread into surrounding communities.

Porous Agarose Layered Magnetic Graphene Oxide Nanocomposite for Virus RNA Monitoring in Wastewater

The detection of virus RNA in wastewater has been established as a valuable method for monitoring Coronavirus disease 2019. Carbon nanomaterials hold potential application in separating virus RNA owing to their effective adsorption and extraction capabilities. However, carbon nanomaterials have limited separability under homogeneous aqueous conditions. Due to the stabilities in their nanostructure, it is a challenge to efficiently immobilize them onto magnetic beads for separation. Here, we develop a porous agarose layered magnetic graphene oxide (GO) nanocomposite that is prepared by agglutinating ferroferric oxide (Fe3O4) beads and GO with agarose into a cohesive whole. With an average porous size of approximately 500 nm, the porous structure enables the unhindered entry of virus RNA, facilitating its interaction with the surface of GO. Upon the application of a magnetic field, the nucleic acid can be separated from the solution within a few minutes, achieving adsorption efficiency and recovery rate exceeding 90% under optimized conditions. The adsorbed nucleic acid can then be preserved against complex sample matrix for 3 days, and quantitatively released for subsequent quantitative reverse transcription polymerase chain reaction (RT-qPCR) detection. The developed method was successfully utilized to analyze wastewater samples obtained from a wastewater treatment plant, detecting as few as 10 copies of RNA molecules per sample. The developed aMGO-RT-qPCR provides an efficient approach for monitoring viruses and will contribute to wastewater-based surveillance of community infections.

Seasonality of respiratory, enteric, and urinary viruses revealed by wastewater genomic surveillance

Wastewater surveillance can reveal population-level infectious disease burden and emergent public health threats can be reliably assessed through wastewater surveillance. While molecular methods for wastewater monitoring of microorganisms have traditionally relied on PCR-based approaches, next-generation sequencing (NGS) can provide deeper insights via genomic analyses of multiple diverse pathogens. We conducted a year-long sequencing surveillance of 1,408 composite wastewater samples collected from 12 neighborhood-level access points in the greater Tempe area, Arizona, USA, and show that variation in wastewater viruses is driven by seasonal time and location. The temporal dynamics of viruses in wastewater were influenced cyclically, with the most dissimilarity between samples 23 weeks apart (i.e., winter vs summer, spring vs fall). We identified diverse urinary and enteric viruses including polyomaviruses, astroviruses, and noroviruses, and showed that their genotypes/subtypes shifted across seasons. We show that while wastewater data of certain respiratory viruses like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strongly correlate with clinical case rates, laboratory-reported case incidences were discordant with surges of high viral load in wastewater for other viruses like human coronavirus 229E. These results demonstrate the utility of wastewater sequencing for informing decision-making in public health.IMPORTANCEWastewater surveillance can provide insights into the spread of pathogens in communities. Advances in next-generation sequencing (NGS) methodologies allow for more precise detection of viruses in wastewater. Long-term wastewater surveillance of viruses is an important tool for public health preparedness. This system can act as a public health observatory that gives real-time early warning for infectious disease outbreaks and improved response times.

Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater

Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.

SARS-CoV-2 detection in pediatric dental clinic wastewater reflects the number of local COVID-19 cases in children under 10 years old

This was the first longitudinal study to analyze dental clinic wastewater to estimate asymptomatic SARS-CoV-2 infection trends in children. We monitored wastewater over a 14-month period, spanning three major COVID-19 waves driven by the Alpha, Delta, and Omicron variants. Each Saturday, wastewater was sampled at the Pediatric Dental Clinic of the only dental hospital in Japan's Saitama Prefecture. The relationship between the weekly number of cases in Saitama Prefecture among residents aged < 10 years (exposure) and wastewater SARS-CoV-2 RNA detection (outcome) was examined. The number of cases was significantly associated with wastewater SARS-CoV-2 RNA positivity (risk ratio, 5.36; 95% confidence interval, 1.72-16.67; Fisher's exact test, p = 0.0005). A sample from Week 8 of 2022 harbored the Omicron variant. Compared to sporadic individual testing, this approach allows continuous population-level surveillance, which is less affected by healthcare seeking and test availability. Since wastewater from pediatric dental clinics originates from the oral cavities of asymptomatic children, such testing can provide important information regarding asymptomatic COVID-19 in children, complementing clinical pediatric data.

Online trend estimation and detection of trend deviations in sub-sewershed time series of SARS-CoV-2 RNA measured in wastewater

Wastewater surveillance has proven a cost-effective key public health tool to understand a wide range of community health diseases and has been a strong source of information on community levels and spread for health departments throughout the SARS- CoV-2 pandemic. Studies spanning the globe demonstrate the strong association between virus levels observed in wastewater and quality clinical case information of the population served by the sewershed. Few of these studies incorporate the temporal dependence present in sampling over time, which can lead to estimation issues which in turn impact conclusions. We contribute to the literature for this important public health science by putting forward time series methods coupled with statistical process control that (1) capture the evolving trend of a disease in the population; (2) separate the uncertainty in the population disease trend from the uncertainty due to sampling and measurement; and (3) support comparison of sub-sewershed population disease dynamics with those of the population represented by the larger downstream treatment plant. Our statistical methods incorporate the fact that measurements are over time, ensuring correct statistical conclusions. We provide a retrospective example of how sub-sewersheds virus levels compare to the upstream wastewater treatment plant virus levels. An on-line algorithm supports real-time statistical assessment of deviations of virus level in a population represented by a sub-sewershed to the virus level in the corresponding larger downstream wastewater treatment plant. This information supports public health decisions by spotlighting segments of the population where outbreaks may be occurring.

Food and Environmental Virology: Use of Passive Sampling to Characterize the Presence of SARS-CoV-2 and Other Viruses in Wastewater

Fecal shedding of SARS-CoV-2 leads to a renaissance of wastewater-based epidemiology (WBE) as additional tool to follow epidemiological trends in the catchment of treatment plants. As alternative to the most commonly used composite samples in surveillance programs, passive sampling is increasingly studied. However, the many sorbent materials in different reports hamper the comparison of results and a standardization of the approach is necessary. Here, we compared different cost-effective sorption materials (cheesecloths, gauze swabs, electronegative filters, glass wool, and tampons) in torpedo-style housings with composite samples. Despite a remarkable variability of the concentration of SARS-CoV-2-specific gene copies, analysis of parallel-deposited passive samplers in the sewer demonstrated highest rate of positive samples and highest number of copies by using cheesecloths. Using this sorption material, monitoring of wastewater of three small catchments in the City of Dresden resulted in a rate of positive samples of 50% in comparison with composite samples (98%). During the investigation period, incidence of reported cases of SARS-CoV-2 in the catchments ranged between 16 and 170 per 100,000 persons and showed no correlation with the measured concentrations of E gene in wastewater. In contrast, constantly higher numbers of gene copies in passive vs. composite samples were found for human adenovirus and crAssphage indicating strong differences of efficacy of methods concerning the species investigated. Influenza virus A and B were sporadically detected allowing no comparison of results. The study contributes to the further understanding of possibilities and limits of passive sampling approaches in WBE.

A snapshot of SARS-CoV-2 viral RNA throughout wastewater treatment plants in Arkansas

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread the viral RNA in wastewater by the feces of those experience COVID-19 symptoms. While wastewater monitoring of SARS-CoV-2 in the raw sewage has been confirmed as an effective tool to predict COVID-19 infection, the goal of this study is to assess the presence of SARS-CoV-2 viral RNA throughout various wastewater treatment processes. Wastewater samples were collected from wastewater treatment plants (WWTPs) in the state of Arkansas from August 2020 to June 2021 and measured for the relative concentration of SARS-CoV-2 viral RNA using RT-qPCR. The gene concentrations in the raw wastewater measured in this study were similar to other published studies, targeting the N1 and N2 genes of the virus. The viral RNA concentration was measured after each wastewater treatment step within WWTPs, including primary sedimentation, activated sludge, filtration and disinfection. Results show the most viral RNA removal occurred in the secondary treatment (activated sludge). The viral RNA was only occasionally detected after disinfection (chlorination or UV disinfection). Overall, WWTPs can remove the SARS-CoV-2 viral RNA at an average of 98.7%, while complete removal was achieved on 82% of the sampling days. Further investigation is required to ensure complete viral RNA removal from wastewater such as improving existing treatment process or supplementing with additional treatment steps. PRACTITIONER POINTS: The viral RNA of SARS-CoV-2 was detected in Arkansas wastewater treatment plants. SARS-CoV-2 was rarely detected in treated effluent from wastewater treatment plants. Activated sludge was effective removing SARS-CoV-2 viral RNA from wastewater. This study was limited by the direct RNA extraction from wastewater, which lowered the sensitivity of detection.

Precision public health in schools enabled by wastewater surveillance: A case study of COVID-19 in an Upstate New York middle-high school campus during the 2021-2022 academic year

Wastewater surveillance provides a cost-effective and non-invasive way to gain an understanding of infectious disease transmission including for COVID-19. We analyzed wastewater samples from one school site in Jefferson County, New York during the 2021-2022 school year. We tested for SARS-CoV-2 RNA once weekly and compared those results with the clinical COVID-19 cases in the school. The amount of SARS-CoV-2 RNA correlated with the number of incident COVID-19 cases, with the best correlation being one day lead time between the wastewater sample and the number of COVID-19 cases. The sensitivity and positive predictive value of wastewater surveillance to correctly identify any COVID-19 cases up to 7 days after a wastewater sample collection ranged from 82-100% and 59-78% respectively, depending upon the amount of SARS-CoV-2 RNA in the sample. The specificity and negative predictive value of wastewater surveillance to correctly identify when the school was without a case of COVID-19 ranged from 67-78% and 70-80%, respectively, depending upon the amount of SARS-CoV-2 RNA in the sample. The lead time observed in this study suggests that transmission might occur within a school before SARS-CoV-2 is identified in wastewater. However, wastewater surveillance should still be considered as a potential means of understanding school-level COVID-19 trends and is a way to enable precision public health approaches tailored to the epidemiologic situation in an individual school.

A systematic review of influenza virus in water environments across human, poultry, and wild bird habitats

Influenza, a highly contagious acute respiratory disease, remains a major global health concern. This study aimed to comprehensively assess the prevalence of influenza virus in different aquatic environments. Using 43 articles from four databases, we thoroughly examined water matrices from wastewater treatment plants (WTPs) and other human environments, as well as poultry habitats and areas frequented by migratory wild birds. In WTP influents (10 studies), positivity rates for influenza A ranged from 0.0 % to 97.6 %. For influenza B (8 studies), most studies reported no positivity, except for three studies reporting detection in 0.8 %, 5.6 %, and 46.9 % of samples. Within poultry habitats (13 studies), the prevalence of influenza A ranged from 4.3 % to 76.4 %, while in environments frequented by migratory wild birds (11 studies), it ranged from 0.4 % to 69.8 %. Geographically, the studies were distributed as follows: 39.5 % from the Americas, 18.6 % from Europe, 2.3 % from South-East Asia and 39.5 % from the Western Pacific. Several influenza A subtypes were found in water matrices, including avian influenza (H3N6, H3N8, H4N1, H4N2, H4N6, H4N8, H5N1, H5N8, H6N2, H6N6, H7N9, H0N8, and H11N9) and seasonal human influenza (H1N1 and H3N2). The existing literature indicates a crucial requirement for more extensive future research on this topic. Specifically, it emphasizes the need for method harmonization and delves into areas deserving of in-depth research, such as water matrices pertaining to pig farming and prevalence studies in low-income countries.

Comparison of RT-ddPCR and RT-qPCR platforms for SARS-CoV-2 detection: Implications for future outbreaks of infectious diseases

The increased frequency of human infectious disease outbreaks caused by RNA viruses worldwide in recent years calls for enhanced public health surveillance for better future preparedness. Wastewater-based epidemiology (WBE) is emerging as a valuable epidemiological tool for providing timely population-wide surveillance for disease prevention and response complementary to the current clinical surveillance system. Here, we compared the analytical performance and practical applications between predominant molecular detection methods of RT-qPCR and RT-ddPCR on SARS-CoV-2 detection in wastewater surveillance. When pure viral RNA was tested, RT-ddPCR exhibited superior quantification accuracy at higher concentration levels and achieved more sensitive detection with reduced variation at low concentration levels. Furthermore, RT-ddPCR consistently demonstrated more robust and accurate measurement either in the background of the wastewater matrix or with the presence of mismatches in the target regions of the consensus assay. Additionally, by detecting mock variant RNA samples, we found that RT-ddPCR outperformed RT-qPCR in virus genotyping by targeting specific loci with signature mutations in allele-specific (AS) assays, especially at low levels of allele frequencies and concentrations, which increased the possibility for sensitive low-prevalence variant detection in the population. Our study provides insights for detection method selection in the WBE applications for future infectious disease outbreaks.

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

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

Wastewater surveillance of the most common circulating respiratory viruses in Athens: The impact of COVID-19 on their seasonality

Due to governments' actions to contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the activity of common circulating respiratory viruses was significantly disrupted after the COVID-19 pandemic and thorough surveillance of respiratory pathogens was considered essential worldwide. Wastewater-based epidemiology has proven to be a valuable tool, that provides complementary information on disease outbreaks and is increasingly used to study the infection dynamics of other viruses, apart from SARS-CoV-2. The aims of the present study were the detection of four commonly circulating respiratory viruses: SARS-CoV-2, influenza A, B and Human Respiratory Syncytial Virus (RSV), the evaluation of the COVID-19 pandemic impact on their seasonality and the determination of the possible common trends in the viral load of these viruses in the wastewater of the Attica region. A standardized and validated concentration and extraction protocol was used, generic for all four viruses, followed by Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) assays. The study proved that there was a prolonged period when all four viruses circulated in the population and an early outbreak of seasonal influenza and RSV in 2022-2023, compared to data from the pre-COVID-19 period. SARS-CoV-2, influenza A and RSV concentrations showed peak levels during December, followed by a slight decline in influenza A concentrations, followed by steady increase of influenza B concentrations in January 2023. SARS-CoV-2 was the dominant virus throughout the whole study period. This is the first study in Greece that investigated the most common circulating viruses simultaneously and in one of the largest timelines, providing crucial information about their infection dynamics during a period when an outbreak of respiratory diseases was declared by the National Public Health Organization. Presented results highlight the establishment of environmental surveillance as a non-invasive and complementary virus outbreak monitoring tool and the importance of influenza A, B and RSV integration into a wastewater-based surveillance system to help in disease management.

Crykey: Rapid Identification of SARS-CoV-2 Cryptic Mutations in Wastewater

We present Crykey, a computational tool for rapidly identifying cryptic mutations of SARS-CoV-2. Specifically, we identify co-occurring single nucleotide mutations on the same sequencing read, called linked-read mutations, that are rare or entirely missing in existing databases, and have the potential to represent novel cryptic lineages found in wastewater. While previous approaches exist for identifying cryptic linked-read mutations from specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and for tens of thousands of samples and with increased scrutiny, given their potential to represent either artifacts or hidden SARS-CoV-2 lineages. Crykey fills this gap by identifying rare linked-read mutations that pass stringent computational filters to limit the potential for artifacts. We evaluate the utility of Crykey on >3,000 wastewater and >22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over a three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations representing potential cryptic lineages in wastewater.

Development and application of influenza virus wastewater surveillance in Hong Kong

Wastewater surveillance is considered as a powerful tool in providing cost-effective, population-wide and near real-time surveillance results for controlling infectious diseases (i.e., SARS-CoV-2, influenza virus), complementary to clinical surveillance. To facilitate the utility of this emerging tool, we developed two preanalytical protocols (supernatant-based and pellet-based) for influenza A/B virus (IAV/IBV) wastewater surveillance and applied them to the established wastewater surveillance network for large-scale longitudinal monitoring in Hong Kong. We tested 724 wastewater samples from 24 stationary sites for weekly surveillance for 8 months and 458 wastewater samples from 11 wastewater treatment plants (WWTPs) for more frequent (three times per week) city-wide surveillance for 4 months when influenza season commenced. We found the city-wide IAV virus concentration in wastewater were associated with the detection rate and influenza-like illness plus rates (ILI+) of clinical respiratory specimens and increased significantly after the cancelling of mask mandate that was in place for COVID-19. IBV was at low detection rates and low virus concentration levels, consistent with the low detection rates observed by clinical surveillance. In addition, we conducted virus subtype identification in selected wastewater samples, and observed the H1pdm was the major circulation subtype. Moreover, the obtained virus signals were confirmed by Sanger sequencing of PCR products, suggesting the feasibility and applicability of established methods for rapid detection of influenza virus types and subtypes in wastewater surveillance. This study demonstrates the applicability of IAV/IBV wastewater surveillance to current wastewater infrastructures and it could be used as a rapid and cost-effective surveillance strategy to track virus transmission patterns in the community for timely public health actions in the future.

Schools and Wastewater Surveillance: Practical Implications for an Emerging Technology to Impact Child Health

Since the start of the COVID-19 pandemic, wastewater surveillance has emerged as a public health tool that supplements traditional surveillance methods used to detect the prevalence of the SARS-CoV-2 virus in communities. In May 2020, the Houston Health Department (HHD) partnered with a coalition of municipal and academic partners to develop a wastewater monitoring and reporting system for the city of Houston, Texas. The HHD subsequently launched a program to conduct targeted wastewater sampling at 52 school sites located in a large, urban school district in Houston. Data generated by this program are shared with school district officials and nurses from participating schools. Although initial feedback from these stakeholders indicated that they considered the wastewater data valuable, the emergency nature of the pandemic prevented a systematic evaluation of the program. To address this gap in knowledge, the HHD and Rice University conducted a study to determine how wastewater data are used to make decisions about COVID-19 prevention and mitigation practices in schools. Our findings indicate that maximizing the utility of wastewater data in the school context will require the development of communication strategies and education efforts tailored to the needs of specific audiences and improving collaboration between local health departments, school districts, and school nurses.

The Protective Effect of Virus Capsids on RNA and DNA Virus Genomes in Wastewater

Virus concentrations measured in municipal wastewater help inform both the water treatment necessary to protect human health and wastewater-based epidemiology. Wastewater measurements are typically PCR-based, and interpreting gene copy concentrations requires an understanding of the form and stability of the nucleic acids. Here, we study the persistence of model virus genomes in wastewater, the protective effects provided by the virus capsids, and the relative decay rates of the genome and infectious viruses. In benchtop batch experiments in wastewater influent at 25 °C, extraviral (+)ssRNA and dsDNA amplicons degraded by 90% within 15-19 min and 1.6-1.9 h, respectively. When encapsidated, the T90 for MS2 (+)ssRNA increased by 424× and the T90 for T4 dsDNA increased by 52×. The (+)ssRNA decay rates were similar for a range of amplicon sizes. For our model phages MS2 and T4, the nucleic acid signal in untreated wastewater disappeared shortly after the viruses lost infectivity. Combined, these results suggest that most viral genome copies measured in wastewater are encapsidated, that measured concentrations are independent of assay amplicon sizes, and that the virus genome decay rates of nonenveloped (i.e., naked) viruses are similar to inactivation rates. These findings are valuable for the interpretation of wastewater virus measurements.

Wastewater Surveillance Data as a Complement to Emergency Department Visit Data for Tracking Incidence of Influenza A and Respiratory Syncytial Virus - Wisconsin, August 2022-March 2023

Wastewater surveillance has been used to assist public health authorities in tracking local transmission of SARS-CoV-2. The usefulness of wastewater surveillance to track community spread of other respiratory pathogens, including influenza virus and respiratory syncytial virus (RSV), is less clear. During the 2022-23 respiratory diseases season, concentrations of influenza A virus and RSV in wastewater samples in three major Wisconsin cities were compared with emergency department (ED) visits associated with these pathogens. In all three cities, higher concentrations of influenza A virus and RSV in wastewater were associated with higher numbers of associated ED visits (Kendall's tau range = 0.50-0.63 for influenza-associated illness and 0.30-0.49 for RSV-associated illness). Detections of both influenza A virus and RSV in wastewater often preceded a rise in associated ED visits for each pathogen, and virus material remained detectable in wastewater for up to 3 months after pathogen-specific ED visits declined. These results demonstrate that wastewater surveillance has the potential to complement conventional methods of influenza and RSV surveillance, detecting viral signals earlier and for a longer duration than do clinical data. Continued use of wastewater surveillance as a supplement to established surveillance systems such as ED visits might improve local understanding and response to seasonal respiratory virus outbreaks.

Wastewater Surveillance for SARS-CoV-2 at Long-Term Care Facilities: Mixed Methods Evaluation

BACKGROUND

Wastewater surveillance provided early indication of COVID-19 in US municipalities. Residents of long-term care facilities (LTCFs) experienced disproportionate morbidity and mortality early in the COVID-19 pandemic. We implemented LTCF building-level wastewater surveillance for SARS-CoV-2 at 6 facilities in Kentucky to provide early warning of SARS-CoV-2 in populations considered vulnerable.

OBJECTIVE

This study aims to evaluate the performance of wastewater surveillance for SARS-CoV-2 at LTCFs in Kentucky.

METHODS

We conducted a mixed methods evaluation of wastewater surveillance following Centers for Disease Control and Prevention (CDC) guidelines for evaluating public health surveillance systems. Evaluation steps in the CDC guidelines were engaging stakeholders, describing the surveillance system, focusing the evaluation design, gathering credible evidence, and generating conclusions and recommendations. We purposively recruited stakeholders for semistructured interviews and undertook thematic content analysis of interview data. We integrated wastewater, clinical testing, and process data to characterize or calculate 7 surveillance system performance attributes (simplicity, flexibility, data quality, sensitivity and positive predictive value [PPV], timeliness, representativeness, and stability).

RESULTS

We conducted 8 stakeholder interviews. The surveillance system collected wastewater samples (N=811) 2 to 4 times weekly at 6 LTCFs in Kentucky from March 2021 to February 2022. Synthesis of credible evidence indicated variable surveillance performance. Regarding simplicity, surveillance implementation required moderate human resource and technical capacity. Regarding flexibility, the system efficiently adjusted surveillance frequency and demonstrated the ability to detect additional pathogens of interest. Regarding data quality, software identified errors in wastewater sample metadata entry (110/3120, 3.53% of fields), technicians identified polymerase chain reaction data issues (140/7734, 1.81% of reactions), and staff entered all data corrections into a log. Regarding sensitivity and PPV, using routine LTCF SARS-CoV-2 clinical testing results as the gold standard, a wastewater SARS-CoV-2 signal of >0 RNA copies/mL was 30.6% (95% CI 24.4%-36.8%) sensitive and 79.7% (95% CI 76.4%-82.9%) specific for a positive clinical test at the LTCF. The PPV of the wastewater signal was 34.8% (95% CI 27.9%-41.7%) at >0 RNA copies/mL and increased to 75% (95% CI 60%-90%) at >250 copies/mL. Regarding timeliness, stakeholders received surveillance data 24 to 72 hours after sample collection, with delayed reporting because of the lack of weekend laboratory staff. Regarding representativeness, stakeholders identified challenges delineating the population contributing to LTCF wastewater because of visitors, unknown staff toileting habits, and the use of adult briefs by some residents preventing their waste from entering the sewer system. Regarding stability, the reoccurring cost to conduct 1 day of wastewater surveillance at 1 facility was approximately US $144.50, which included transportation, labor, and materials expenses.

CONCLUSIONS

The LTCF wastewater surveillance system demonstrated mixed performance per CDC criteria. Stakeholders found surveillance feasible and expressed optimism regarding its potential while also recognizing challenges in interpreting and acting on surveillance data.

Temporal dynamics of genetically heterogeneous extended-spectrum cephalosporin-resistant Escherichia coli bloodstream infections

Extended-spectrum cephalosporin-resistant Escherichia coli (ESC-R-Ec) is an urgent public health threat with sequence type clonal complex 131 (STc131), phylogroup B2 strains being particularly concerning as the dominant cause of ESC-R-Ec infections. To address the paucity of recent ESC-R-Ec molecular epidemiology data in the United States, we used whole-genome sequencing (WGS) to fully characterize a large cohort of invasive ESC-R-Ec at a tertiary care cancer center in Houston, Texas, collected from 2016 to 2020. During the study time frame, there were 1,154 index E. coli bloodstream infections (BSIs) of which 389 (33.7%) were ESC-R-Ec. Using time series analyses, we identified a temporal dynamic of ESC-R-Ec distinct from ESC-susceptible E. coli (ESC-S-Ec), with cases peaking in the last 6 months of the calendar year. WGS of 297 ESC-R-Ec strains revealed that while STc131 strains accounted for ~45% of total BSIs, the proportion of STc131 strains remained stable across the study time frame with infection peaks driven by genetically heterogeneous ESC-R-Ec clonal complexes. bla CTX-M variants accounted for most β-lactamases conferring the ESC-R phenotype (89%; 220/248 index ESC-R-Ec), and amplification of bla CTX-M genes was widely detected in ESC-R-Ec strains, particularly in carbapenem non-susceptible, recurrent BSI strains. Bla CTX-M-55 was significantly enriched within phylogroup A strains, and we identified bla CTX-M-55 plasmid-to-chromosome transmission occurring across non-B2 strains. Our data provide important information regarding the current molecular epidemiology of invasive ESC-R-Ec infections at a large tertiary care cancer center and provide novel insights into the genetic basis of observed temporal variability for these clinically important pathogens. IMPORTANCE Given that E. coli is the leading cause of worldwide ESC-R Enterobacterales infections, we sought to assess the current molecular epidemiology of ESC-R-Ec using a WGS analysis of many BSIs over a 5-year period. We identified fluctuating temporal dynamics of ESC-R-Ec infections, which have also recently been identified in other geographical regions such as Israel. Our WGS data allowed us to visualize the stable nature of STc131 over the study period and demonstrate a limited but genetically diverse group of ESC-R-Ec clonal complexes are detected during infection peaks. Additionally, we provide a widespread assessment of β-lactamase gene copy number in ESC-R-Ec infections and delineate mechanisms by which such amplifications are achieved in a diverse array of ESC-R-Ec strains. These data suggest that serious ESC-R-Ec infections are driven by a diverse array of strains in our cohort and impacted by environmental factors suggesting that community-based monitoring could inform novel preventative measures.

Dynamic Periodicity of Extended-Spectrum Cephalosporin Resistant Bloodstream Escherichia coli Infections Driven by Non-CC131 Strains

Extended-spectrum cephalosporin resistant (ESC-R) Escherichia coli (ESC-R- Ec ) is an urgent public health threat with clonal complex (CC) 131, phylogroup B2 strains being particularly concerning as the dominant cause of ESC-R- Ec infections. To address the paucity of recent ESC-R- Ec molecular epidemiology data in the United States (US), we used whole genome sequencing (WGS) to fully characterize a large cohort of invasive ESC-R- Ec at a tertiary care cancer center in Houston, Texas collected from 2016-2020. During the study timeframe, there were 1154 index E. coli bloodstream infections (BSIs) of which 389 (33.7%) were ESC-R. Using time series analyses, we identified a temporal dynamic of ESC-R E. coli BSIs ( Ec -BSIs), distinct from ESC-susceptible Ec -BSIs, with cases peaking in the last 6 months of the calendar year. WGS of 297 ESC-R Ec -BSI strains revealed that while CC131 strains accounted for ∼45% of total infections, the proportion of CC131 strains remained stable across the time-period, and infection peaks were driven by genetically diverse, non-CC131 isolates. Bla _CTX-M variants accounted for most β-lactamases conferring the ESC-R phenotype (89%; 220/248 index ESC-R Ec -BSIs), and amplification of bla _CTX-M genes was widely detected in ESC-R Ec -BSI strains, particularly in carbapenem non-susceptible strains and in strains causing recurrent BSIs. Bla _{CTX- M-55} was significantly enriched within phylogroup A strains, and we identified bla _CTX-M-55 plasmid-to-chromosome transmission occurring across non-B2 strains. Our data provide important information regarding the current molecular epidemiology of invasive ESC-R E. coli and provide novel insights into the genetic basis of observed temporal variability for these clinically important pathogens.

IMPORTANCE

Given that E. coli is the leading cause of ESC-R Enterobacterales infection, we sought to assess the current molecular epidemiology of ESC-R- Ec using a WGS based analysis of many BSIs over a several year period. We identified a clear temporal dynamic of ESC-R- Ec infections, which has also recently been identified in other geographical regions such as Israel. Our WGS data allowed us to visualize the stable nature of CC131 over the study period and demonstrate that non-CC131 strains drove the infection peaks. Additionally, we provide the first widespread assessment of β-lactamase gene copy number in ESC-R- Ec infections and delineate mechanisms by which such amplifications are achieved in a diverse array of ESC-R- Ec strains. These data suggest that even for a tertiary care center, serious ESC-R- Ec infections are driven by a diverse array of strains and impacted by environmental factors suggesting that community-based monitoring could inform novel preventative measures.