Anti-SARS-CoV-2 total immunoglobulin and neutralising antibody responses in healthy blood donors throughout the COVID-19 pandemic: a longitudinal observational study.

INTRODUCTION: Quantifying antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and neutralising antibodies may help to understand protection at the individual and population levels. Determination of neutralising antibodies using classical virus neutralisation tests (VNT) is considered the gold standard, but they are costly and time-intensive. Enzyme-linked immunosorbent assay (ELISA)-based surrogate VNTs (sVNT) or anti-SARS-CoV-2 spike protein receptor binding domain immunoglobulins (anti-S-RBD Ig) may be suitable alternatives to VNTs. We aimed to (a) explore the correlations between anti-S-RBD Ig, VNT, and sVNT measurements and (b) describe humoral immunity against SARS-CoV-2 after vaccination, natural infection, and vaccine breakthrough infection in healthy blood donors. METHODS: We measured total anti-SARS-CoV-2 Ig in 5714 serum samples from 2748 healthy individuals visiting the Swiss Red Cross Blood Donation Centre in Basel from 03/2020 to 04/2022. We used the Elecsys® Anti-SARS-CoV-2 immunoassay (Roche) against the N- and S-receptor binding domain (RBD) proteins. In a subset of 548 samples from 123 donors, we conducted sVNTs against the Wuhan wild-type SARS-CoV-2 (SARS-CoV-2 Neutralizing Antibodies Detection Kit; Adipogen™). In 100 samples from 40 donors, we correlated sVNT and VNTs against the wild-type (D614G WU1) virus. Surveys were sent to the blood donors to collect data on their SARS-CoV-2 infection and vaccination status. Using this data, donors were categorised as "vaccination only", "infection before vaccination", "post-vaccine breakthrough infection", and "natural infection only". RESULTS: Our longitudinal observation study cohort consisted of 50.7% males with a median age of 31 years (range 18-75 y). Anti-SARS-CoV-2 N protein positivity rates per month indicate 57.1% (88/154) of the cohort was infected up to 04/2022. No differences in seropositivity were found between sexes, age groups, blood types (AB0 or RhD), and cytomegalovirus serostatus. We observed a high correlation between anti-S-RBD Ig and inhibition percentage (Spearman's ρ = 0.92, Kendall's τ = 0.77, p <0.0001). We determined the sensitivity and specificity for the manufacturers' thresholds for detecting virus-neutralising effects and computed the "best" cut-off based on our real-world data. We categorised 722/1138 (63.5%) donors as vaccination only (82.3%), post-vaccine breakthrough infection (7.8%), infection before vaccination (5.8%), and natural infection only (4.2%). We observed a lower inhibition percentage in the natural infection-only group than in all other vaccinated groups. The infection before vaccination group had higher anti-S-RBD Ig titres after the first vaccine dose than the other vaccinated groups. CONCLUSION: In total, 57.1% of healthy blood donors were infected with SARS-CoV-2, but natural infection without evidence of vaccination seems to result in substantially lower neutralising antibody levels. An estimate of antibody neutralisation may be helpful to assess reinfection risk. Total anti-S-RBD Ig correlates with surrogate virus neutralisation test results, a surrogate for neutralisation; therefore, we suggest that total anti-S-RBD Ig may estimate the level of neutralising antibodies. The threshold for protection from an unfavourable clinical outcome must be evaluated in prospective clinical cohorts.

Evaluation of the clinical relevance of the Biofire© FilmArray pneumonia panel among hospitalized patients.

PURPOSE: Panel PCR tests provide rapid pathogen identification. However, their diagnostic performance is unclear. We assessed the performance of the Biofire© FilmArray pneumonia (PN)-panel against standard culture in broncho-alveolar lavage (BAL) samples. METHODS: Setting: University Hospital Basel (February 2019 to July 2020), including hospitalized patients with a BAL (± pneumonia). We determined sensitivity and specificity of the PN-panel against standard culture. Using univariate logistic regression, we calculated odds ratios (OR) for pneumonia according to PN-panel and culture status, stratifying by chronic pulmonary disease. We calculated ORs for pneumonia for different pathogens to estimate the clinical relevance. RESULTS: We included 840 adult patients, 60% were males, median age was 68 years, 35% had chronic pulmonary disease, 21% had pneumonia, and 36% had recent antibiotic use. In 1078 BAL samples, bacterial pathogens were detected in 36% and 16% with PN-panel and culture, respectively. The overall sensitivity and specificity of the PN-panel was high, whereas the positive predictive value was low. The OR of pneumonia was 1.1 (95% CI 0.7-1.6) for PN-panel-positive only; 2.6 (95% CI 1.3-5.3) for culture-positive only, and 1.6 (95% CI 1.0-2.4) for PN-panel and culture-positive. The detection rate of Haemophilus influenzae, Staphylococcus aureus, and Moraxella catarrhalis in the PN-panel was high but not associated with pneumonia. CONCLUSION: While sensitivity and specificity of PN-panel are high compared to culture, pathogen detection did not correlate well with a pneumonia diagnosis. Patients with culture-positive BAL had the highest OR for pneumonia-thus the impact of the PN-panel on clinical management needs further evaluation in randomized controlled trials.

Performance of four bacterial cell counting apps for smartphones.

Quantifying bacterial colony forming units is important in microbiological diagnostics. Recent progress in imaging technology allows automation of this tedious and error-prone task. We compared the accuracy of four smartphone colony counter applications conducting standardized measurements, using a self-built apparatus. One app showed high accuracy at lower colony counts.

Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area.

Transmission chains within small urban areas (accommodating ∼30 per cent of the European population) greatly contribute to case burden and economic impact during the ongoing coronavirus pandemic and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in a European urban area, Basel-City (Switzerland). We combined detailed epidemiological, intra-city mobility and socio-economic data sets with whole-genome sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44 per cent of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60 per cent of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare system burden (intensive care unit (ICU) occupancy). Transmissions were driven by socio-economically weaker and highly mobile population groups with mostly cryptic transmissions which lacked genetic and identifiable epidemiological links. Amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90 per cent transmission reduction and 70-90 per cent reduction of severe cases showed that prioritising mobile, socio-economically weaker populations for vaccination would effectively reduce case numbers. However, long-term ICU occupation would also be effectively reduced if senior population groups were prioritised, provided there were no changes in testing and prevention strategies. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area.

Global Genomic Analysis of SARS-CoV-2 RNA Dependent RNA Polymerase Evolution and Antiviral Drug Resistance.

A variety of antiviral treatments for COVID-19 have been investigated, involving many repurposed drugs. Currently, the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp, encoded by nsp12-nsp7-nsp8) has been targeted by numerous inhibitors, e.g., remdesivir, the only provisionally approved treatment to-date, although the clinical impact of these interventions remains inconclusive. However, the potential emergence of antiviral resistance poses a threat to the efficacy of any successful therapies on a wide scale. Here, we propose a framework to monitor the emergence of antiviral resistance, and as a proof of concept, we address the interaction between RdRp and remdesivir. We show that SARS-CoV-2 RdRp is under purifying selection, that potential escape mutations are rare in circulating lineages, and that those mutations, where present, do not destabilise RdRp. In more than 56,000 viral genomes from 105 countries from the first pandemic wave, we found negative selective pressure affecting nsp12 (Tajima's D = -2.62), with potential antiviral escape mutations in only 0.3% of sequenced genomes. Potential escape mutations included known key residues, such as Nsp12:Val473 and Nsp12:Arg555. Of the potential escape mutations involved globally, in silico structural models found that they were unlikely to be associated with loss of stability in RdRp. No potential escape mutation was found in a local cohort of remdesivir treated patients. Collectively, these findings indicate that RdRp is a suitable drug target, and that remdesivir does not seem to exert high selective pressure. We anticipate our framework to be the starting point of a larger effort for a global monitoring of drug resistance throughout the COVID-19 pandemic.

SARS-CoV-2 outbreak in a tri-national urban area is dominated by a B.1 lineage variant linked to a mass gathering event.

The first case of SARS-CoV-2 in Basel, Switzerland was detected on February 26th 2020. We present a phylogenetic study to explore viral introduction and evolution during the exponential early phase of the local COVID-19 outbreak from February 26th until March 23rd. We sequenced SARS-CoV-2 naso-oropharyngeal swabs from 746 positive tests that were performed at the University Hospital Basel during the study period. We successfully generated 468 high quality genomes from unique patients and called variants with our COVID-19 Pipeline (COVGAP), and analysed viral genetic diversity using PANGOLIN taxonomic lineages. To identify introduction and dissemination events we incorporated global SARS-CoV-2 genomes and inferred a time-calibrated phylogeny. Epidemiological data from patient questionnaires was used to facilitate the interpretation of phylogenetic observations. The early outbreak in Basel was dominated by lineage B.1 (83·6%), detected first on March 2nd, although the first sample identified belonged to B.1.1. Within B.1, 68·2% of our samples fall within a clade defined by the SNP C15324T ('Basel cluster'), including 157 identical sequences at the root of the 'Basel cluster', some of which we can specifically trace to regional spreading events. We infer the origin of B.1-C15324T to mid-February in our tri-national region. The other genomes map broadly over the global phylogenetic tree, showing several introduction events from and/or dissemination to other regions of the world via travellers. Family transmissions can also be traced in our data. A single lineage variant dominated the outbreak in the Basel area while other lineages, such as the first (B.1.1), did not propagate. A mass gathering event was the predominant initial source of cases, with travel returners and family transmissions to a lesser extent. We highlight the importance of adding specific questions to epidemiological questionnaires, to obtain data on attendance of large gatherings and their locations, as well as travel history, to effectively identify routes of transmissions in up-coming outbreaks. This phylogenetic analysis in concert with epidemiological and contact tracing data, allows connection and interpretation of events, and can inform public health interventions. Trial Registration: ClinicalTrials.gov NCT04351503.