Systematic Review on the Correlation Between SARS-CoV-2 Real-Time PCR Cycle Threshold Values and Epidemiological Trends.

BACKGROUND: The ability to proactively predict the epidemiological dynamics of infectious diseases such as coronavirus disease 2019 (COVID-19) would facilitate efficient public health responses and may help guide patient management. Viral loads of infected people correlate with infectiousness and, therefore, could be used to predict future case rates. AIM: In this systematic review, we determine whether there is a correlation between severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) real-time reverse-transcription polymerase chain reaction (RT-PCR) cycle threshold (Ct) values (a proxy for viral load) and epidemiological trends in patients diagnosed with COVID-19, and whether Ct values are predictive of future cases. METHODS: A PubMed search was conducted on August 22 2022, based on a search strategy of studies reporting correlations between SARS-CoV-2 Ct values and epidemiological trends. RESULTS: Data from 16 studies were relevant for inclusion. RT-PCR Ct values were measured from national (n = 3), local (n = 7), single-unit (n = 5), or closed single-unit (n = 1) samples. All studies retrospectively examined the correlation between Ct values and epidemiological trends, and seven evaluated their prediction model prospectively. Five studies used the temporal reproduction number (Rt) as the measure of the population/epidemic growth rate. Eight studies reported a prediction time in the negative cross-correlation between Ct values and new daily cases, with seven reporting a prediction time of ~1-3 weeks, and one reporting 33 days. CONCLUSION: Ct values are negatively correlated with epidemiological trends and may be useful in predicting subsequent peaks in variant waves of COVID-19 and other circulating pathogens.

Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness.

Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans.

Ct values as a diagnostic tool for monitoring SARS-CoV-2 viral load using the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

OBJECTIVES: Qualitative real-time polymerase chain reaction tests are not designed to provide quantitative or semiquantitative results because cycle threshold (Ct) values are not normalized to standardized controls of known concentration. The aim of this study was to characterize SARS-CoV-2 viral loads based on Ct values, using the QIAstat-Dx® Respiratory SARS-CoV-2 Panel. METHODS: Different lineages of SARS-CoV-2 clinical samples and the World Health Organization international standard were used to assess the linearity of the QIAstat-Dx Respiratory SARS-CoV-2 Panel. Limit of detection for the different lineages was characterized. RESULTS: Comparable efficiencies and linearity for all samples resulted in R2 ≥0.99, covering a dynamic range of 1,000,000-100 copies/mL for the SARS-CoV-2 assay, showing linear correlation between Ct values and viral load down to 300 copies/mL. CONCLUSION: The SARS-CoV-2 Ct values provided by the QIAstat-Dx® Respiratory SARS-CoV-2 Panel could be used as a surrogate for viral load given the linear correlation between Ct values and viral concentration down to limit of detection. This panel allows to obtain reproducible Ct values for SARS-CoV-2 ribonucleic acid downstream of the sample collection, reducing the sample-to-Ct workflow variability. Ct values can help provide a reliable assessment and comparison of viral loads in patients when tested with the QIAstat-Dx Respiratory SARS-CoV-2 Panel.

Systematic review on the association between respiratory virus real-time PCR cycle threshold values and clinical presentation or outcomes.

OBJECTIVES: It is unclear whether real-time (rt)-PCR cycle threshold (Ct) values can be utilized to guide clinical and infection-control decisions. This systematic review assesses the association between respiratory pathogen rt-PCR Ct values and clinical presentation or outcomes. METHODS: We searched MEDLINE, EMBASE and Cochrane library databases on 14-17 January 2020 for studies reporting the presence or absence of an association between Ct values and clinical presentation or outcomes, excluding animal studies, reviews, meta-analyses, and non-English language studies. RESULTS: Among 33 studies identified (reporting on between 9 and 4918 participants by pathogen), influenza (n = 11 studies; 4918 participants), human rhinovirus (HRV, n = 11; 2012) and respiratory syncytial virus (RSV, n = 8; 3290) were the most-studied pathogens. Low influenza Ct values were associated with mortality in 1/3 studies, with increased disease severity/duration or ICU admission in 3/9, and with increased hospitalization or length of hospital stay (LOS) in 1/6. Low HRV Ct values were associated with increased disease severity/duration or ICU admission in 3/10 studies, and with increased hospitalization or LOS in 1/3. Low RSV Ct values were associated with increased disease severity/duration or ICU admission in 3/6 studies, and with increased hospitalization or LOS in 4/4. Contradictory associations were also identified for other respiratory pathogens. CONCLUSIONS: Respiratory infection Ct values may inform clinical and infection-control decisions. However, the study heterogeneity observed in this review highlights the need for standardized workflows to utilize Ct values as a proxy of genomic load and confirm their value for respiratory infection management.

Preliminary Evaluation of QuantiFERON SARS-CoV-2 and QIAreach Anti-SARS-CoV-2 Total Test in Recently Vaccinated Individuals.

INTRODUCTION: There is an increasing body of evidence surrounding the importance of a T cell-mediated response to SARS-CoV-2 infection and after COVID-19 vaccination. In this internal feasibility study, we evaluated both the total antibody (IgA, IgM, and IgG) and T cell responses in a cohort of COVID-19 convalescents and vaccinated individuals. METHODS: Whole blood specimens were collected weekly from 12 subjects at different time points within/after the COVID-19 mRNA vaccination regimen, and from 4 PCR-confirmed convalescent donors to measure durability of humoral and cell-mediated immune response. T cell and antibody responses were evaluated via the QuantiFERON SARS-CoV-2 research use only (QFN SARS-CoV-2) assay which is an interferon gamma release assay (IGRA) and QIAreach Anti-SARS-CoV-2 total (Anti-CoV-2) test, respectively. RESULTS: In a cohort of recently vaccinated individuals, subjects demonstrated robust total antibody and CD4+/CD8+ T cell response to SARS-CoV-2 mRNA vaccines when followed for 2 months post-2nd dose. In most individuals, T cell response declined between the 1st and 2nd doses suggesting a need for a booster or the completion of the 2-dose vaccine series. In a group of convalescent donors tested with QFN SARS-CoV-2 and Anti-CoV-2 tests, all patients had an antibody and T cell response up to 1 year after natural infection. CONCLUSION: This small feasibility study demonstrates that the QFN-SARS-CoV-2 test is able to identify CD4+ and CD8+ T cell-mediated responses in SARS-CoV-2-vaccinated subjects and those recovered from COVID-19, alongside a qualitative antibody response detectable via the QIAreach Anti-CoV2 test.

First performance report of QIAreach™ Anti-SARS-CoV-2 Total Test, an innovative nanoparticle fluorescence digital detection platform.

In 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic. Disease diagnosis, appropriate clinical management and infection control are all important factors in controlling the spread of SARS-CoV-2. The QIAreach™ Anti-SARS-CoV-2 Total Test (Anti-CoV2) is a rapid, qualitative serological test, using proprietary nanoparticle fluorescence technology to detect total antibody (IgA, IgM, and IgG) against SARS-CoV-2. Here we report the results of the US Food and Drug Administration (FDA) clinical agreement study. Thirty positive plasma or serum samples were taken from consenting individuals with polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection ≥14 days from symptom onset. Seventy-five samples from before the believed circulation of SARS-CoV-2 (November 1, 2019) were used to assess specificity. Positive percent agreement (PPA) and negative percent agreement (NPA) were calculated along with the corresponding exact two-sided 95 % confidence intervals (CI) using an FDA Emergency Use Authorized PCR test as the reference method. Anti-CoV2 was shown to have 100 % sensitivity (PPA; 95 % CI 88.4-100 %) and 100 % specificity (NPA; 95 % CI 95.2-100 %). Against 157 pre-pandemic samples, no cross-reactivity was observed with seasonal coronaviruses or other respiratory pathogens tested. Additionally, no interference was observed when samples were spiked with: conjugated bilirubin 0.4 mg/ml; unconjugated bilirubin 0.4 mg/ml; hemoglobin 5 mg/ml; prednisolone 0.12 mg/ml; triglycerides 15 mg/ml. In conclusion, Anti-CoV2 provides accurate qualitative detection of total antibodies against SARS-CoV-2.

A Systematic Review of the Clinical Utility of Cycle Threshold Values in the Context of COVID-19.

BACKGROUND: The ability to predict likely prognosis and infectiousness for patients with COVID-19 would aid patient management decisions. Diagnosis is usually via real-time PCR, and it is unclear whether the semi-quantitative capability of this method, determining viral load through cycle threshold (Ct) values, can be leveraged. OBJECTIVES: We aim to review available knowledge on correlations between SARS-COV-2 Ct values and patient- or healthcare-related outcomes to determine whether Ct values provide useful clinical information. SOURCES: A PubMed search was conducted on 1 June 2020 based on a search strategy of (Ct value OR viral load) AND SARS-CoV-2. Data were extracted from studies reporting on the presence or absence of an association between Ct values, or viral loads determined via Ct value, and clinical outcomes. CONTENT: Data from 18 studies were relevant for inclusion. One study reported on the correlation between Ct values and mortality and one study reported on the correlation between Ct values and progression to severe disease; both reported a significant association (p < 0.001 and p = 0.008, respectively). Fourteen studies reported on the correlation between Ct value or viral loads determined via Ct value and disease severity, and an association was observed in eight (57%) studies. Studies reporting on the correlation of viral load with biochemical and haematological markers showed an association with at least one marker, including increased lactate dehydrogenase (n = 4), decreased lymphocytes (n = 3) and increased high-sensitivity troponin I (n = 2). Two studies reporting on the correlation with infectivity showed that lower Ct values were associated with higher viral culture positivity. IMPLICATIONS: Data suggest that lower Ct values may be associated with worse outcomes and that Ct values may be useful in predicting the clinical course and prognosis of patients with COVID-19; however, further studies are warranted to confirm clinical value.

Correction to: A Systematic Review of the Clinical Utility of Cycle Threshold Values in the Context of COVID-19.

The original article can be found online.

Multiple assays in a real-time RT-PCR SARS-CoV-2 panel can mitigate the risk of loss of sensitivity by new genomic variants during the COVID-19 outbreak.

OBJECTIVES: In this study, five SARS-CoV-2 PCR assay panels were evaluated against the accumulated genetic variability of the virus to assess the effect on sensitivity of the individual assays. DESIGN OR METHODS: As of week 21, 2020, the complete set of available SARS-CoV-2 genomes from GISAID and GenBank databases were used in this study. SARS-CoV-2 primer sequences from publicly available panels (WHO, CDC, NMDC, and HKU) and QIAstat-Dx were included in the alignment, and accumulated genetic variability affecting any oligonucleotide annealing was annotated. RESULTS: A total of 11,627 (34.38%) genomes included single mutations affecting annealing of any PCR assay. Variations in 8,773 (25.94%) genomes were considered as high risk, whereas additional 2,854 (8.43%) genomes presented low frequent single mutations and were predicted to yield no impact on sensitivity. In case of the QIAstat-Dx SARS-CoV-2 Panel, 99.11% of the genomes matched with a 100% coverage all oligonucleotides, and critical variations were tested in vitro corroborating no loss of sensitivity. CONCLUSIONS: This analysis stresses the importance of targeting more than one region in the viral genome for SARS-CoV-2 detection to mitigate the risk of loss of sensitivity due to the unknown mutation rate during this SARS-CoV-2 outbreak.