Application of a high-throughput quantitative PCR system for simultaneous monitoring of SARS-CoV-2 variants and other pathogenic viruses in wastewater.

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are continuously emerging, highlighting the importance of regular surveillance of SARS-CoV-2 and other epidemiologically significant pathogenic viruses in the current context. Reverse transcription-quantitative PCR (RT-qPCR) is expensive, time-consuming, labor-intensive, requires a large reagent volume, and only tests a few targets in a single run. High-throughput qPCR (HT-qPCR) utilizing the Biomark HD system (Fluidigm) can be used as an alternative. This study applied an HT-qPCR to simultaneously detect SARS-CoV-2, SARS-CoV-2 nucleotide substituted RNA, and other pathogenic viruses in wastewater. Wastewater samples were collected from the coronavirus disease 2019 (COVID-19) quarantine facility between October 2020 and February 2021 (n = 4) and from the combined and separated sewer lines of a wastewater treatment plant (WWTP) in Yokkaichi, Mie Prefecture, Japan, between March and August 2021 (n = 23 each). The samples were analyzed by HT-qPCR using five SARS-CoV-2, nine SARS-CoV-2 spike gene nucleotide substitution-specific, five pathogenic viruses, and three process control assays. All samples from the quarantine facility tested positive for SARS-CoV-2 and the nucleotide substitutions N501Y and S69-70 del (Alpha variant) were detected in the December 2020 sample, coinciding with the first clinical case in Japan. Only three WWTP samples were positive when tested with a single SARS-CoV-2 assay, whereas more than eight samples were positive when tested with all assays, indicating that using multiple assays increases the likelihood of detection. The nucleotide substitution L452R (Delta variant) was detected in the WWTP samples of Mie Prefecture in April 2021, but the detection of Delta variant from patients had not been reported until May 2021. Aichi virus 1 and norovirus GII were prevalent in WWTP samples. This study demonstrated that HT-qPCR may be the most time- and cost-efficient method for tracking COVID-19 and broadly monitoring community health.

Wastewater-Based Epidemiology for Cost-Effective Mass Surveillance of COVID-19 in Low- and Middle-Income Countries: Challenges and Opportunities

Wastewater-based epidemiology (WBE) is an approach that can be used to estimate COVID-19 prevalence in the population by detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. As the WBE approach uses pooled samples from the study population, it is an inexpensive and non-invasive mass surveillance method compared to individual testing. Thus, it offers a good complement in low- and middle-income countries (LMICs) facing high costs of testing or social stigmatization, and it has a huge potential to monitor SARS-CoV-2 and its variants to curb the global COVID-19 pandemic. The aim of this review is to systematize the current evidence about the application of the WBE approach in mass surveillance of COVID-19 infection in LMICs, as well as its future potential. Among other parameters, population size contributing the fecal input to wastewater is an important parameter for COVID-19 prevalence estimation. It is easier to back-calculate COVID-19 prevalence in the community with centralized wastewater systems, because there can be more accurate estimates about the size of contributing population in the catchment. However, centralized wastewater management systems are often of low quality (or even non-existent) in LMICs, which raises a major concern about the ability to implement the WBE approach. However, it is possible to mobilize the WBE approach, if large areas are divided into sub-areas, corresponding to the existing wastewater management systems. In addition, a strong coordination between stakeholders is required for estimating population size respective to wastewater management systems. Nevertheless, further international efforts should be leveraged to strengthen the sanitation infrastructures in LMICs, using the lessons gathered from the current COVID-19 pandemic to be prepared for future pandemics.