SARS-CoV-2 in schools: genome analysis shows that concurrent cases in the second and third wave were often unconnected

BackgroundThe risk of SARS-CoV-2 (SCoV2) infection in schools and student households is typically assessed using classical epidemiology whereby transmission is based on time of symptom onset and contact tracing data. Using such methodologies may be imprecise regarding transmission events of different, simultaneous SCoV2 variants spreading with different rates and directions in a given population. We analysed with high resolution the transmission among different communities, social networks, and educational institutions and the extent of outbreaks using whole genome sequencing (WGS). Methods and FindingsWe combined WGS and contact tracing spanning two pandemic waves from October 2020 to May 2021 in the Canton of Basel-City, Switzerland and performed an in-depth analysis of 235 cases relating to 22 educational institutions. We describe the caseload in educational institutions and the public health measures taken and delineate the WGS-supported outbreak surveillance. During the study period, 1,573 of 24,557 (6.4%) children and 410 of 3,726 (11%) staff members from educational institutions were reported SCoV2 positive. Thereof, WGS data from 83 children, 35 adult staff in 22 educational institutions and their 117 contacts (social network, families) was available and analysed. 353 contextual sequences from residents of the Canton of Basel-City sequenced through surveillance were identified to be related to cases in the educational institutions. In total, we identified 55 clusters and found that coinciding SCoV2-cases in individual educational institutions were mostly introduced from different sources such as social networks or the larger community. More transmission chains started in the community and were brought into the educational institutions than vice versa (31 vs. 13). Adolescents (12-19 years old) had the highest case prevalence over both waves compared to younger children or adults, especially for the emerging Alpha variant. ConclusionsIntroduction of SCoV2 into schools accounts for most events and reflects transmission closely related to social activity, whereby teenagers and young adults contribute to significant parallel activity. Combining WGS with contact tracing is pivotal to properly inform authorities about SCoV2 infection clusters and transmission directions in educational settings and the effectiveness of enacted public health measures. The gathered data showing more clusters to seed in the community than vice versa as well as few subsequent in-school transmissions indicate that the agilely employed health measures for educational institutions helped to prevent outbreaks among staff and children. The clinical trial accession number is NCT04351503 (clinicaltrials.gov).

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.

Sex- and Gender-specific Risk Factors of Post-COVID-19 Syndrome: A Population-based Cohort Study in Switzerland

BackgroundWomen are overrepresented amongst individuals suffering from post-acute sequelae of SARS-CoV-2 infection (PASC). Biological (sex) as well as sociocultural (gender) differences between women and men might account for this imbalance, yet their impact on PASC is unknown. Methods and FindingsBy using Bayesian models comprising >200 co-variates, we assessed the impact of social context in addition to biological data on PASC in a multi-centre prospective cohort study of 2927 (46% women) individuals in Switzerland. Women more often reported at least one persistent symptom than men (43.5% vs 32.0% of men, p<0.001) six (IQR 5-9) months after SARS-CoV-2 infection. Adjusted models showed that women with personality traits stereotypically attributed to women were most often affected by PASC (OR 2.50[1.25-4.98], p<0.001), in particular when they were living alone (OR 1.84[1.25-2.74]), had an increased stress level (OR 1.06[1.03-1.09]), had undergone higher education (OR 1.30[1.08-1.54]), preferred pre-pandemic physical greeting over verbal greeting (OR 1.71[1.44-2.03]), and had experienced an increased number of symptoms during index infection (OR 1.27[1.22-1.33]). ConclusionBesides gender- and sex-sensitive biological parameters, sociocultural variables play an important role in producing sex differences in PASC. Our results indicate that predictor variables of PASC can be easily identified without extensive diagnostic testing and are targets of interventions aiming at stress coping and social support.

Determinants of SARS-CoV-2 transmission to guide vaccination strategy in a city

BackgroundTransmission chains within small urban areas (accommodating[~]30% of the European population) greatly contribute to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of SARS-CoV-2 transmission in a European urban area, Basel-City (Switzerland). Methodology. We combined detailed epidemiological, intra-city mobility, and socioeconomic data-sets with whole-genome-sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44% of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60% 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 occupancy). Principal Findings. Transmissions were driven by socioeconomically weaker and highly mobile population groups with mostly cryptic transmissions, whereas amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90% transmission reduction, and 70-90% reduction of severe cases showed that prioritizing mobile, socioeconomically weaker populations for vaccination would effectively reduce case numbers. However, long-term intensive-care-unit occupation would also be effectively reduced if senior population groups were prioritized, provided there were no changes in testing and prevention strategies. Conclusions. 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. Author summaryWe examined SARS-CoV-2 transmission patterns within a European city (Basel, Switzerland) to infer drivers of the transmission during the first wave in spring 2020. The combination of diverse data (serological, genomic, transportation, socioeconomic) allowed us to combine phylogenetic analysis with mathematical modelling on related cases that were mapped to a residential address. As a result we could evaluate population groups driving SARS-CoV-2 transmission and quantify their effect on the transmission dynamics. We found traceable transmission chains in wealthier or more senior population groups and cryptic transmissions in the mobile, young or socioeconomic weaker population groups - these were identified as transmission drivers of the first wave. Based on this insight, we simulated vaccination scenarios for various vaccine efficacies to reflect different approaches undertaken to handle the epidemic. We conclude that vaccination of the mobile inherently younger population group would be most effective to handle following waves.

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.

Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis

IntroductionSince December 2019, a novel coronavirus (SARS-CoV-2) has triggered a world-wide pandemic with an enormous medical, societal, and economic toll. Thus, our aim was to gather all available information regarding comorbidities, clinical signs and symptoms, outcomes, laboratory findings, imaging features, and treatments in patients with coronavirus disease 2019 (COVID-19). MethodsEMBASE, PubMed/ Medline, Scopus, and Web of Science were searched for studies published in any language between December 1st, 2019 and March 28th. Original studies were included if the exposure of interest was an infection with SARS-CoV-2 or confirmed COVID-19. The primary outcome was the risk ratio of comorbidities, clinical signs and symptoms, imaging features, treatments, outcomes, and complications associated with COVID-19 morbidity and mortality. We performed random-effects pairwise meta-analyses for proportions and relative risks, I2, Tau2, and Cochrane Q, sensitivity analyses, and assessed publication bias. Results148 met the inclusion criteria for the systematic review and meta-analysis with 12149 patients (5739 female) and a median age was 47.0 [35.0-64.6]. 617 patients died from COVID-19 and its complication, while 297 patients were reported as asymptomatic. Older age (SMD: 1.25 [0.78-1.72]; p < 0.001), being male (RR = 1.32 [1.13-1.54], p = 0.005) and pre-existing comorbidity (RR = 1.69 [1.48-1.94]; p < 0.001) were identified as risk factors of in-hospital mortality. The heterogeneity between studies varied substantially (I2; range: 1.5-98.2%). Publication bias was only found in eight studies (Eggers test: p < 0.05). ConclusionsOur meta-analyses revealed important risk factors that are associated with severity and mortality of COVID-19.