SARS-CoV-2 Omicron detection by antigen tests using saliva.

The Omicron emerged in November 2021 and became the predominant SARS-CoV-2 variant globally. It spreads more rapidly than ancestral lineages and its rapid detection is critical for the prevention of disease outbreaks. Antigen tests such as immunochromatographic assay (ICA) and chemiluminescent enzyme immunoassay (CLEIA) yield results more quickly than standard polymerase chain reaction (PCR). However, their utility for the detection of the Omicron variant remains unclear. We herein evaluated the performance of ICA and CLEIA in saliva from 51 patients with Omicron and 60 PCR negative individuals. The sensitivity and specificity of CLEIA were 98.0% (95%CI: 89.6-100.0%) and 100.0% (95%CI: 94.0-100.0%), respectively, with fine correlation with cycle threshold (Ct) values. The sensitivity and specificity of ICA were 58.8% (95%CI: 44.2-72.4%) and 100.0% (95%CI: 94.0-100.0%), respectively. The sensitivity of ICA was 100.0% (95%CI: 80.5-100.0%) when PCR Ct was less than 25. The Omicron can be efficiently detected in saliva by CLEIA. ICA also detects high viral load Omicron using saliva.

SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales.

Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.

Impact of COVID-19 Nonpharmaceutical Interventions on the Extent of Norovirus Contamination in Oyster Production Areas in Ireland during Winter 2020 to 2021.

ABSTRACT: A significant decrease in norovirus prevalence and concentration was observed in oyster production areas in Ireland during winter 2020 to 2021. Oyster production areas impacted by human wastewater discharges that had been undergoing norovirus surveillance since 2018 were investigated. Samples collected in the winter seasons of 2018 to 2019 and 2019 to 2020, prior to when the COVID-19 pandemic interventions were applied, showed a prevalence of 94.3 and 96.6%, respectively, and geometric mean concentrations of 533 and 323 genome copies per g, respectively. These values decreased significantly during the winter of 2020 to 2021 (prevalence of 63.2% and geometric concentration of below the limit of quantification), coinciding with the control measures to mitigate the transmission of severe acute respiratory syndrome coronavirus 2 of the genus Betacoronavirus. Divergence between norovirus GI and GII prevalence and concentrations was observed over the 3-year monitoring period. Norovirus GII was the dominant genogroup detected in winter 2020 to 2021, with over half of samples positive, although concentrations detected were significantly lower than prepandemic winters, with a geometric mean concentration of below the limit of quantification.

Highly Selective Multiplex Quantitative Polymerase Chain Reaction with a Nanomaterial Composite Hydrogel for Precise Diagnosis of Viral Infection.

As viruses have been threatening global public health, fast diagnosis has been critical to effective disease management and control. Reverse-transcription quantitative polymerase chain reaction (RT-qPCR) is now widely used as the gold standard for detecting viruses. Although a multiplex assay is essential for identifying virus types and subtypes, the poor multiplicity of RT-qPCR makes it laborious and time-consuming. In this paper, we describe the development of a multiplex RT-qPCR platform with hydrogel microparticles acting as independent reactors in a single reaction. To build target-specific particles, target-specific primers and probes are integrated into the particles in the form of noncovalent composites with boron nitride nanotubes (BNNTs) and carbon nanotubes (CNTs). The thermal release characteristics of DNA, primer, and probe from the composites of primer-BNNT and probe-CNT allow primer and probe to be stored in particles during particle production and to be delivered into the reaction. In addition, BNNT did not absorb but preserved the fluorescent signal, while CNT protected the fluorophore of the probe from the free radicals present during particle production. Bicompartmental primer-incorporated network (bcPIN) particles were designed to harness the distinctive properties of two nanomaterials. The bcPIN particles showed a high RT-qPCR efficiency of over 90% and effective suppression of non-specific reactions. 16-plex RT-qPCR has been achieved simply by recruiting differently coded bcPIN particles for each target. As a proof of concept, multiplex one-step RT-qPCR was successfully demonstrated with a simple reaction protocol.

Estimating the minimum number of SARS-CoV-2 infected cases needed to detect viral RNA in wastewater: To what extent of the outbreak can surveillance of wastewater tell us?

There is increasing interest in wastewater-based epidemiology (WBE) of SARS-CoV-2 RNA to serve as an early warning system for a community. Despite successful detection of SARS-CoV-2 RNA in wastewaters sampled from multiple locations, there is still no clear idea on the minimal number of cases in a community that are associated with a positive detection of the virus in wastewater. To address this knowledge gap, we sampled wastewaters from a septic tank (n = 57) and biological activated sludge tank (n = 52) located on-site of a hospital. The hospital is providing treatment for SARS-CoV-2 infected patients, with the number of hospitalized patients per day known. It was observed that depending on which nucleocapsid gene is targeted by means of RT-qPCR, a range of 253-409 positive cases out of 10,000 persons are required prior to detecting RNA SARS-CoV-2 in wastewater. There was a weak correlation between N1 and N2 gene abundances in wastewater with the number of hospitalized cases. This correlation was however not observed for N3 gene. The frequency of detecting N1 and N2 gene in wastewater was also higher than that for N3 gene. Furthermore, nucleocapsid genes of SARS-CoV-2 were detected at lower frequency in the partially treated wastewater than in the septic tank. In particular, N1 gene abundance was associated with water quality parameters such as total organic carbon and pH. In instances of positive detection, the average abundance of N1 and N3 genes in the activated sludge tank were reduced by 50 and 70% of the levels detected in septic tank, suggesting degradation of the SARS-CoV-2 gene fragments already occurring in the early stages of the wastewater treatment process.

Evaluation of the clinical performance of single-, dual-, and triple-target SARS-CoV-2 RT-qPCR methods.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a pandemic. Reverse transcription quantitative PCR (RT-qPCR) has played a vital role in the diagnosis of COVID-19, but the rates of false negatives is not ideal in dealing with this highly infectious virus. It is thus necessary to systematically evaluate the clinical performance of the single-, dual-, triple-target detection kits to guide the clinical diagnosis of this disease. METHODS: A series of reference materials calibrated by droplet digital PCR (ddPCR) and 57 clinical samples were used to evaluate the clinical performance of six single-, dual-, triple-target SARS-CoV-2 nucleic acid detection kits based on RT-qPCR. RESULTS: The dual-target kits, kit B and kit C had the highest and the lowest detection sensitivity, which was 125 copies/mL and 4000 copies/mL, respectively. Among the 57 clinical samples from patients with COVID-19, 47 were tested positive by the kit B, while 35, 29, 28, 30, and 29 were found positive by the kits A, C, D, E, and F, respectively. The number of targets in a detection kit is not a key factor affecting sensitivity, while the amount of sample loading may influence the performance of a detection kit. CONCLUSIONS: This study provides a guide when choosing or developing a nucleic acid detection kit for the diagnosis of COVID-19. Also, the absolute-quantification feature and high-sensitivity performance of ddPCR, suggesting that it can be used to review clinically suspected samples.