SARS-CoV-2 vaccine Alpha and Delta variant breakthrough infections are rare and mild, but happen relative early after vaccination

IntroductionCOVID-19 vaccines significantly reduce SARS-CoV-2 (SCoV2)-related hospitalization and mortality in randomized controlled clinical trials, as well as in real-world effectiveness against different circulating SCoV2-lineages. However, some vaccine recipients show breakthrough infection and it remains unknown, which host and viral factors contribute to this risk and how many resulted in severe outcomes. Our aim was to identify demographic and clinical risk factors for SCoV2 breakthrough infections and severe disease in fully vaccinated individuals and to compare patient characteristics in breakthrough infections caused by SCoV2 Alpha or Delta variant. MethodsWe conducted an exploratory retrospective case-control study from 28th of December to 25th of October 2021 dominated by the Delta SCoV2 variant. All cases of infection had to be reported by law to the local health authorities. Vaccine recipients data was anonymously available from the national Vaccination Monitoring Data Lake and the main local vaccine center. We compared anonymized patients characteristics of breakthrough infection (n=492) to two overlapping control groups including all vaccine recipients from the Canton of Basel-City (group 1 n=126586 and group 2 n=109382). We also compared patients with breakthrough infection caused by the Alpha to Delta variant. We used different multivariate generalized linear models (GLM). ResultsWe found only 492/126586 (0.39%) vaccine recipients with a breakthrough infection after vaccination during the 10 months observational period. Most cases were asymptomatic or mild (478/492 97.2%) and only very few required hospitalization (14/492, 2.8%). The time to a positive SCoV2 test shows that most breakthrough infections occurred between a few days to about 170 days after full vaccination, with a median of 78 days (interquartile range, IQR 47-124 days). Factors associated with a lower odds for breakthrough infection were: age (OR 0.987, 95%CI 0.983-0.992), previous COVID-19 infection prior to vaccination (OR 0.296, 95%CI 0.117-0.606), and (self-declared) serious side-effects from previous vaccines (OR 0.289, 95%CI 0.033-1.035). Factors associated with a higher odds for breakthrough infection were: vaccination with the Pfizer/BioNTech vaccine (OR 1.459, 95%CI 1.238-1.612), chronic disease as vaccine indication (OR 2.109, 95%CI 1.692-2.620), and healthcare workers (OR 1.404, 95%CI 1.042-1.860). We did not observe a significantly increased risk for immunosuppressed patients (OR 1.248, 95% CI 0.806-1.849). ConclusionsOur study shows that breakthrough infections are rare and show mild illness, but that it occurs early after vaccination with more than 50% of cases within 70 to 80 days post-full vaccination. This clearly implies that boost vaccination should be much earlier initiated compared to the currently communicated 180-day threshold. This has important implications especially for risk groups associated with more frequent breakthrough infections such as healthcare workers, and people in high-risk care facilities. Due to changes in the epidemiological dynamic with new variants emerging, continuous monitoring of breakthrough infections is helpful to provide evidence on booster vaccines and patient groups at risk for potential complications.

Global surveillance of potential antiviral drug resistance in SARS-CoV-2: proof of concept focussing on the RNA-dependent RNA polymerase

Antiviral treatments for COVID-19 have involved many repurposed drugs. Currently, SARS-CoV-2 RNA-dependent RNA polymerase (RdRp, encoded by nsp12-nsp7-nsp8) has been targeted by numerous inhibitors with debated clinical impact. Among these, remdesivir has been conditionally approved for the treatment of COVID-19 patients. Although the emergence of antiviral resistance, an indirect proxy for antiviral efficacy, poses a considerable healthcare threat, an evolutionary perspective on emerging resistant mutants is still lacking. Here we show that SARS-CoV-2 RdRp is under purifying selection, that potential escape mutations are rare, and unlikely to lead to viral fitness loss. In more than 56,000 viral genomes from 105 countries dating from December 2019 to July 2020 we found negative selective pressure affecting nsp12 (Tajimas D = -2.62), with potential antiviral escape mutations in only 0.3% of sequenced genomes. Those affected known key residues, such as Nsp12:Val473 and Nsp12:Arg555. Of the potential escape mutations found globally, in silico structural models show that this rarely implies loss of stability in RdRp. No potential escape mutation were found in our local cohort of remdesivir treated patients from the first wave (n=8). Our results indicate that RdRp is a suitable drug target, and that remdesivir does not seem to exert high selective pressure. Our study could be the starting point of a larger monitoring effort of drug resistance throughout the COVID-19 pandemic. We recommend the application of repetitive genome sequencing of SARS-CoV-2 from patients treated with antivirals to provide early insights into the evolution or antiviral resistance.

Epidemiology and precision of SARS-CoV-2 detection following lockdown and relaxation measures

Introduction: SARS-CoV-2-detection is critical for clinical and epidemiological assessment of the ongoing CoVID-19 pandemic. Aim: To cross-validate manual and automated high-throughput (Roche-cobas6800-Target1/Target2) testing for SARS-CoV-2-RNA, to describe detection rates following lockdown and relaxation, and to evaluate SARS-CoV-2-loads in different specimens. Method: The validation cohort prospectively compared Basel-S-gene, Roche-E-gene, and Roche-cobas6800-Target1/Target2 in 1344 naso-oropharyngeal swabs (NOPS) taken in calendar week 13 using Basel-ORF8-gene-assay for confirmation. Follow-up-cohort-1 and -2 comprised 12363 and 10207 NOPS taken over 10 weeks until calendar week 24 and 34, respectively. SARS-CoV-2-loads were compared in follow-up NOPS, lower respiratory fluids, and plasma. Results: Concordant results were obtained in 1308 cases (97%) including 97 (9%) SARS-CoV-2-positives showing high quantitative correlations (Spearman r>0.95; p<0.001) for all assays. Discordant samples (N=36) had significantly lower SARS-CoV-2-loads (p<0.001). Following lockdown, weekly detection rates declined to <1% reducing single-test positive predictive values from 99.3% to 85.1%. Following relaxation, rates flared up to 4% with similarly high SARS-CoV-2-loads, but patients were significantly younger than during lockdown (34 vs 52 years, p<0.001). SARS-CoV-2-loads in follow-up NOPS declined by 3log10 copies/mL within 10 days post-diagnosis (p<0.001). SARS-CoV-2-loads in NOPS correlated weakly with those in time-matched lower respiratory fluids and plasma, but remained detectable in 14 and 7 cases of NOPS with undetectable SARS-CoV-2, respectively. Conclusion: Evaluated manual and automated assays are highly concordant and correlate quantitatively. Following successful lockdown, declining positive predictive values require dual-target-assays for clinical and epidemiologic assessment. Confirmatory and quantitative follow-up testing should be considered within <5 days, using lower respiratory fluids in symptomatic patients with SARS-CoV-2-negative NOPS.

SARS-CoV-2 phylogeny during the early outbreak in the Basel area, Switzerland: import and spread dominated by a single B.1 lineage variant (C15324T)

BackgroundThe first case of SARS-CoV-2 in Basel, Switzerland, was detected on February 26th 2020. We present a phylogenetic longitudinal study and explore viral introduction and evolution during the exponential early phase of the local COVID-19 outbreak from February 26th until March 23rd. MethodsWe sequenced SARS-CoV-2 from naso-oropharyngeal swabs, generated 468 high quality genomes, and called variants with our COVID-19 Pipeline (COVGAP). We 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. FindingsThe early outbreak in Basel was dominated by lineage B.1 (83{middle dot}6%), detected from March 2nd, although the first lineage identified was B.1.1. Within B.1, a clade containing 68{middle dot}2% of our samples, defined by the SNP C15324T, suggests local spreading events. We infer the geographic origin of this mutation to our tri-national region. The remaining genomes map broadly over the global phylogenetic tree, evidencing several events of introduction from and/or dissemination to other regions of the world. We also observe family transmission events. InterpretationA single lineage dominated the outbreak in the City of Basel while other lineages such as the first (B1.1) did not propagate. Thus spreading events seem to have contributed most to viral spread, while travel returners and family transmissions were better controlled by the recommended measures. This phylogenetic analysis enriches epidemiological and contact tracing data, allowing connection of seemingly unconnected events, and can inform public health interventions. FundingNo dedicated funding was used for this work.

Epidemiology of SARS-CoV-2 Emergence Amidst Community-Acquired Respiratory Viruses

BackgroundSARS-CoV-2 emerged in China in December 2019 as new cause of severe viral pneumonia (CoVID-19) reaching Europe by late January 2020. We validated the WHO-recommended assay and describe the epidemiology of SARS-CoV-2 and community-acquired respiratory viruses (CARVs). MethodsNaso-oropharyngeal swabs (NOPS) from 7663 individuals were prospectively tested by the Basel-S-gene and the WHO-based E-gene-assay (Roche) using Basel-N-gene-assay for confirmation. CARVs were tested in 2394 NOPS by multiplex-NAT, including 1816 together with SARS-CoV-2. ResultsBasel-S-gene and Roche-E-gene-assays were concordant in 7475 cases (97.5%) including 825 (11%) positive samples. In 188 (2.5%) discordant cases, SARS-CoV-2 loads were significantly lower than in concordant positive ones and confirmed in 105 NOPS. Adults were more likely to test positive for SARS-CoV-2, while children were more likely to test CARV-positive. CARV co-infections with SARS-CoV-2 occurred in 1.8%. SARS-CoV-2 replaced other CARVs within 3 weeks reaching 48% of all detected respiratory viruses followed by rhino/enterovirus (13%), influenzavirus (12%), coronavirus (9%), respiratory syncytial (6%) and metapneumovirus (6%). ConclusionsThe differential diagnosis for respiratory infections was broad during the early pandemic, affecting infection control and treatment decisions. We discuss the role of pre-existing immunity and competitive CARV replication for the epidemiology of SARS-CoV-2 infection among adults and children.

Effect of Systemic Inflammatory Response to SARS-CoV-2 on Lopinavir and Hydroxychloroquine Plasma Concentrations

BackgroundCoronavirus disease 2019 (COVID-19) leads to inflammatory cytokine release, which can downregulate the expression of metabolizing enzymes. This cascade affects drug concentrations in the plasma. We investigated the association between lopinavir (LPV) and hydroxychloroquine (HCQ) plasma concentrations and the values of acute phase inflammation marker C-reactive protein (CRP). MethodsLPV plasma concentrations were prospectively collected in 92 patients hospitalized at our institution. Lopinavir/ritonavir was administered 12-hourly, 800/200 mg on day 1, and 400/100 mg on day 2 until day 5 or 7. HCQ was given at 800 mg, followed by 400 mg after 6, 24 and 48 hours. Hematological, liver, kidney, and inflammation laboratory values were analyzed on the day of drug level determination. ResultsThe median age of study participants was 59 (range 24-85) years, and 71% were male. The median duration from symptom onset to hospitalization and treatment initiation was 7 days (IQR 4-10) and 8 days (IQR 5-10), respectively. The median LPV trough concentration on day 3 of treatment was 26.5 g/mL (IQR 18.9-31.5). LPV plasma concentrations positively correlated with CRP values (r=0.37, p<0.001), and were significantly lower when tocilizumab was preadministrated. No correlation was found between HCQ concentrations and CRP values. ConclusionsHigh LPV plasma concentrations were observed in COVID-19 patients. The ratio of calculated unbound drug fraction to published SARS-CoV-2 EC50 values indicated insufficient LPV concentrations in the lung. CRP values significantly correlated with LPV but not HCQ plasma concentrations, implying inhibition of cytochrome P450 3A4 (CYP3A4) metabolism by inflammation.