A simple algorithm based on initial Ct values predicts the duration to SARS-CoV-2 negativity and allows more efficient test-to-release and return-to-work schedules

Especially during global pandemics but also in the context of epidemic waves, the capacity for diagnostic qRT-PCRs rapidly becomes a limiting factor. Furthermore, excessive testing incurs high costs and can result in an overstrained work force in diagnostics departments. Obviously, people aim to shorten their isolation periods, hospitals need to discharge convalescent people, and re-employ staff members after infection. The aim of the study was to optimize retesting regimens for test-to-release from isolation and return-to-work applications. For this purpose, we investigated the association between Ct values at the first diagnosis of SARS-CoV-2 infection and the period until test negativity was reached, or at least until the Ct value exceeded 30, which is considered to indicate the transition to a non-infectious state. We included results from the testing of respiratory material samples for the detection of SARS-CoV-2 RNA, tested from 01 March 2020 to 31 January 2022. Lower initial Ct values were associated with longer periods of SARS-CoV-2 RNA positivity. Starting with Ct values of <20, 20-25, 25-30, 30-35, and >35, it took median intervals of 20 (interval: 14-25), 16 (interval: 10-21), 12 (interval: 7-16), 7 (interval: 5-14), and 5 (interval: 2-7) days, respectively, until the person tested negative. Accordingly, a Ct threshold of 30 was surpassed after 13 (interval: 8-19), 9 (interval: 6-14), 7 (interval: 6-11), 6 (interval: 4-10), and 3 (interval: 1-6) days, respectively, in individuals with aforementioned start Ct values. Furthermore, the time to negativity was longer for adults versus children, wild-type SARS-CoV-2 variant versus other variants of concern, and in patients who were treated in the intensive care units. Based on these data, we propose an adjusted retesting strategy according to the initial Ct value in order to optimize available PCR resources.

Seasonality of non-SARS, non-MERS Corona viruses and the impact of meteorological factors

BackgroundSeasonality is a characteristic of some respiratory viruses. The aim of our study was to evaluate the seasonality and the potential effects of different meteorological factors on the detection rate of the non-SARS Corona Virus detection by PCR. MethodsWe performed a retrospective analysis of 12763 respiratory tract sample results (288 positive and 12475 negative) for non-SARS, non-MERS Corona viruses (NL63, 229E, OC43, HKU1). The effect of seven single weather factors on the Corona virus detection rate was fitted in a logistic regression model with and without adjusting for other weather factors. ResultsCorona virus infections followed a seasonal pattern peaking from December to March and plunging from July to September. The seasonal effect was less pronounced in immunosuppressed patients compared to immunocompetent. Different automatic variable selection processes agreed to select the predictors temperature, relative humidity, cloud cover and precipitation as remaining predictors in the multivariable logistic regression model including all weather factors, with low ambient temperature, low relative humidity, high cloud cover and high precipitation being linked to increased Corona virus detection rates. ConclusionsCorona virus infections followed a seasonal pattern, which was more pronounced in immunocompetent patients compared to immunosuppressed. Several meteorological factors were associated with the Corona virus detection rate. However, when mutually adjusting for all weather factors, only temperature, relative humidity, precipitation and cloud cover contributed independently to predicting the Corona virus detection rate.

A novel in-cell ELISA assay allows rapid and automated quantification of SARS-CoV-2 to analyse neutralizing antibodies and antiviral compounds

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the most pressing medical and socioeconomic challenge. Constituting important correlates of protection, determination of virus-neutralizing antibodies (NAbs) is indispensable for convalescent plasma selection, vaccine candidate evaluation, and immunity certificates. In contrast to standard serology ELISAs, plaque reduction neutralization tests (PRNTs) are laborious, time-consuming, expensive, and restricted to specialized laboratories. To replace microscopic counting-based SARS-CoV-2 PRNTs by a novel assay exempt from genetically modified viruses, which are inapplicable in most diagnostics departments, we established a simple, rapid, and automated SARS-CoV-2 neutralization assay employing an in-cell ELISA (icELISA) approach. After optimization of various parameters such as virus-specific antibodies, cell lines, virus doses, and duration of infection, SARS-CoV-2-infected cells became amenable as direct antigen source for quantitative icELISA. Using commercially available nucleocapsid protein-specific antibodies, viral infection could easily be quantified in human and highly permissive Vero E6 cells by icELISA. Antiviral agents such as human sera containing NAbs or antiviral interferons dose-dependently reduced the SARS-CoV-2-specific signal. Applying increased infectious doses, the icNT was superior to PRNT in discriminating convalescent sera with high from those with intermediate neutralizing capacities. The SARS-CoV-2 icELISA test allows rapid (<48h in total, read-out in seconds) and automated quantification of virus infection in cell culture to evaluate the efficacy of NAbs as well as antiviral drugs, using reagents and equipment present in most routine diagnostics departments. We propose the icELISA and the icNT for COVID-19 research and diagnostics.