Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

Comparative Analysis of RNA-Extraction Approaches and Associated Influences on RT-qPCR of the SARS-CoV-2 RNA in a University Residence Hall and Quarantine Location

Wastewater-based epidemiology (WBE) provides an early warning and trend analysis approach for determining the presence of COVID-19 in a community and complements clinical testing in assessing the population level, even as viral loads fluctuate. Here, we evaluate combinations of two wastewater concentration methods (i.e., ultrafiltration and composite supernatant-solid), four pre-RNA extraction modifications, and three nucleic acid extraction kits using two different wastewater sampling locations. These consisted of a quarantine facility containing clinically confirmed COVID-19-positive inhabitants and a university residence hall. Of the combinations examined, composite supernatant-solid with pre-RNA extraction consisting of water concentration and RNA/DNA shield performed the best in terms of speed and sensitivity. Further, of the three nucleic acid extraction kits examined, the most variability was associated with the Qiagen kit. Focusing on the quarantine facility, viral concentrations measured in wastewater were generally significantly related to positive clinical cases, with the relationship dependent on method, modification, kit, target, and normalization, although results were variable-dependent on individual time points (Kendall's Tau-b (τ) = 0.17 to 0.6) or cumulatively (Kendall's Tau-b (τ) = -0.048 to 1). These observations can support laboratories establishing protocols to perform wastewater surveillance and monitoring efforts for COVID-19.

Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada

Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

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

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

Dynamics of SARS-CoV-2 Alpha (B.1.1.7) variant spread: The wastewater surveillance approach

Wastewater based epidemiology (WBE) offers an overview of the SARS-CoV-2 variants circulating among the population thereby serving as a proper surveillance method. The variant of concern (VOC) Alpha was first identified in September 2020 in the United Kingdom, and rapidly became dominant across Europe. Our objective was to elucidate the Alpha VOC outcompetition rate and identify mutations in the spike glycoprotein (S) gene, indicative of the circulation of the Alpha VOC and/or other variants in the population through wastewater analysis. In the period covered by this study (November 2020-April 2021), forteen wastewater treatment plants (WWTPs) were weekly sampled. The total number of SARS-CoV-2 genome copies per L (GC/L) was determined with a Real-Time qPCR, targeting the N gene. Surveillance of the Alpha VOC circulation was ascertained using a duplex RT-qPCR, targeting and discriminating the S gene. Our results showed that in a period of 6 weeks the Alpha VOC was present in all the studied WWTPs, and became dominant in 11 weeks on average. The outcompetition rates of the Alpha VOC were estimated, and their relationship with different parameters statistically analyzed. The rapid spread of the Alpha VOC was influenced by its initial input and by the previous circulation of SARS-COV-2 in the population. This latter point could be explained by its higher transmissibility, particularly advantadgeous when a certain degree of herd immunity exists. Moreover, the presence of signature mutations of SARS-COV-2 variants were established by deep-sequencing of the complete S gene. The circulation of the Alpha VOC in the area under study was confirmed, and additionally two combinations of mutations in the S glycoprotein (T73A and D253N, and S477N and A522S) that could affect antibody binding were identified.

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

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

Novel Nested-Seq Approach for SARS-CoV-2 Real-Time Epidemiology and In-Depth Mutational Profiling in Wastewater

Considering the lack of effective treatments against COVID-19, wastewater-based epidemiology (WBE) is emerging as a cost-effective approach for real-time population-wide SARS-CoV-2 monitoring. Here, we report novel molecular assays for sensitive detection and mutational/variant analysis of SARS-CoV-2 in wastewater. Highly stable regions of SARS-CoV-2 RNA were identified by RNA stability analysis and targeted for the development of novel nested PCR assays. Targeted DNA sequencing (DNA-seq) was applied for the analysis and quantification of SARS-CoV-2 mutations/variants, following hexamers-based reverse transcription and nested PCR-based amplification of targeted regions. Three-dimensional (3D) structure models were generated to examine the predicted structural modification caused by genomic variants. WBE of SARS-CoV-2 revealed to be assay dependent, and significantly improved sensitivity achieved by assay combination (94%) vs. single-assay screening (30%-60%). Targeted DNA-seq allowed the quantification of SARS-CoV-2 mutations/variants in wastewater, which agreed with COVID-19 patients' sequencing data. A mutational analysis indicated the prevalence of D614G (S) and P323L (RdRP) variants, as well as of the Β.1.1.7/alpha variant of concern, in agreement with the frequency of Β.1.1.7/alpha variant in clinical samples of the same period of the third pandemic wave at the national level. Our assays provide an innovative cost-effective platform for real-time monitoring and early-identification of SARS-CoV-2 variants at community/population levels.

Novel Nested-Seq Approach for SARS-CoV-2 Real-Time Epidemiology and In-Depth Mutational Profiling in Wastewater

Considering the lack of effective treatments against COVID-19, wastewater-based epidemiology (WBE) is emerging as a cost-effective approach for real-time population-wide SARS-CoV-2 monitoring. Here, we report novel molecular assays for sensitive detection and mutational/variant analysis of SARS-CoV-2 in wastewater. Highly stable regions of SARS-CoV-2 RNA were identified by RNA stability analysis and targeted for the development of novel nested PCR assays. Targeted DNA sequencing (DNA-seq) was applied for the analysis and quantification of SARS-CoV-2 mutations/variants, following hexamers-based reverse transcription and nested PCR-based amplification of targeted regions. Three-dimensional (3D) structure models were generated to examine the predicted structural modification caused by genomic variants. WBE of SARS-CoV-2 revealed to be assay dependent, and significantly improved sensitivity achieved by assay combination (94%) vs. single-assay screening (30%-60%). Targeted DNA-seq allowed the quantification of SARS-CoV-2 mutations/variants in wastewater, which agreed with COVID-19 patients' sequencing data. A mutational analysis indicated the prevalence of D614G (S) and P323L (RdRP) variants, as well as of the Β.1.1.7/alpha variant of concern, in agreement with the frequency of Β.1.1.7/alpha variant in clinical samples of the same period of the third pandemic wave at the national level. Our assays provide an innovative cost-effective platform for real-time monitoring and early-identification of SARS-CoV-2 variants at community/population levels.

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

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