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In British Columbia, Canada, initial growth of the SARS-CoV-2 Delta variant was slower than that reported in other jurisdictions. Delta became the dominant variant (>50% prevalence) within ≈7–13 weeks of first detection in regions within the United Kingdom and United States. In British Columbia, it remained at <10% of weekly incident COVID-19 cases for 13 weeks after first detection on March 21, 2021, eventually reaching dominance after 17 weeks. We describe the growth of Delta variant cases in British Columbia during March 1–June 30, 2021, and apply retrospective counterfactual modeling to examine factors for the initially low COVID-19 case rate after Delta introduction, such as vaccination coverage and nonpharmaceutical interventions. Growth of COVID-19 cases in the first 3 months after Delta emergence was likely limited in British Columbia because additional nonpharmaceutical interventions were implemented to reduce levels of contact at the end of March 2021, soon after variant emergence.

Background Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), can lead to hospitalisation, particularly in elderly, immunocompromised, and non-vaccinated or partially vaccinated individuals. Although vaccination provides protection, the duration of this protection wanes over time. Additional doses can restore immunity, but the influence of viral variants, specific sequences, and vaccine-induced immune responses on disease severity remains unclear. Moreover, the efficacy of therapeutic interventions during hospitalisation requires further investigation. The study aims to analyse the clinical course of COVID-19 in hospitalised patients, taking into account SARS-CoV-2 variants, viral sequences, and the impact of different vaccines. The primary outcome is all-cause in-hospital mortality, while secondary outcomes include admission to intensive care unit and length of stay, duration of hospitalisation, and the level of respiratory support required. Methods This ongoing multicentre study observes hospitalised adult patients with confirmed SARS-CoV-2 infection, utilising a combination of retrospective and prospective data collection. It aims to gather clinical and laboratory variables from around 35,000 patients, with potential for a larger sample size. Data analysis will involve biostatistical and machine-learning techniques. Selected patients will provide biological material. The study started on October 14, 2021 and is scheduled to end on October 13, 2026. Discussion The analysis of a large sample of retrospective and prospective data about the acute phase of SARS CoV-2 infection in hospitalised patients, viral variants and vaccination in several European and non-European countries will help us to better understand risk factors for disease severity and the interplay between SARS CoV-2 variants, immune responses and vaccine efficacy. The main strengths of this study are the large sample size, the long study duration covering different waves of COVID-19 and the collection of biological samples that allows future research. Trial registration The trial has been registered on ClinicalTrials.gov. The unique identifier assigned to this trial is NCT05463380.

To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix in 2020 and 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to October 31, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeoff times in each MSA (the times at which sustained transmission began). The estimated infectiousness of Alpha ranged from 1.1x to 1.4x that of viral strains circulating in 2020 and early 2021. The estimated relative infectiousness of Delta was higher in all cases, ranging from 1.6x  to 2.1x. The estimated Alpha takeoff times ranged from February 1 to February 28, 2021. The estimated Delta takeoff times ranged from June 2 to June 26, 2021. Estimated takeoff times are consistent with genomic surveillance data.

Coronavirus disease 2019 (COVID-19) remains a threat with the emergence of new variants, especially Delta and Omicron, without specific effective therapeutic drugs. The infection causes dysregulation of the immune system with a cytokine storm that eventually leads to fatal acute respiratory distress syndrome (ARDS) and further irreversible pulmonary fibrosis. Therefore, the promising way to inhibit infection is to disrupt the binding and fusion between the viral spike and the host ACE2 receptor. A transcriptome-based drug screening platform has been developed for COVID-19 to explore the possibility and potential of the long-established drugs or herbal medicines to reverse the unique genetic signature of COVID-19. In silico analysis showed that Virofree, an herbal medicine, reversed the genetic signature of COVID-19 and ARDS. Biochemical validations showed that Virofree could disrupt the binding of wild-type and Delta-variant spike proteins to ACE2 and its syncytial formation via cell-based pseudo-typed viral assays, as well as suppress binding between several variant recombinant spikes to ACE2, especially Delta and Omicron. Additionally, Virofree elevated miR-148b-5p levels, inhibited the main protease of SARS-CoV-2 (M pro ), and reduced LPS-induced TNF-α release. Virofree also prevented cellular iron accumulation leading to ferroptosis which occurs in SARS-CoV-2 patients. Furthermore, Virofree was able to reduce pulmonary fibrosis-related protein expression levels in vitro . In conclusion, Virofree was repurposed as a potential herbal medicine to combat COVID-19. This study highlights the inhibitory effect of Virofree on the entry of Delta and Omicron variants of SARS-CoV-2, which have not had any effective treatments during the emergence of the new variants spreading.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by fast evolution with the appearance of several variants. Next-Generation Sequencing (NGS) technology is considered the gold standard for monitoring known and new SARS-CoV-2 variants. However, the complexity of this technology renders this approach impracticable in laboratories located in areas with limited resources. We analyzed the capability of the ThermoFisher TaqPath COVID-19 RT-PCR (TaqPath) and the Seegene Novaplex SARS-CoV-2 Variant assay (Novaplex) to detect Omicron variants; the Allplex VariantII (Allplex) was also evaluated for Delta variants. Sanger sequencing (SaS) was the reference method. The results obtained with n = 355 nasopharyngeal samples were: negative with TaqPath, although positive with other qualitative molecular assays (n = 35); undetermined (n = 40) with both the assays; negative for the ∆69/70 mutation and confirmed as the Delta variant via SaS (n = 100); positive for ∆69/70 and confirmed as Omicron BA.1 via SaS (n = 80); negative for ∆69/70 and typed as Omicron BA.2 via SaS (n = 80). Novaplex typed 27.5% of samples as undetermined with TaqPath, 11.4% of samples as negative with TaqPath, and confirmed 100% of samples were Omicron subtypes. In total, 99/100 samples were confirmed as the Delta variant with Allplex with a positive per cent agreement (PPA) of 98% compared to SaS. As undermined samples with Novaplex showed RdRp median Ct values (Ct = 35.4) statistically higher than those of typed samples (median Ct value = 22.0; p < 0.0001, Mann–Whitney test), the inability to establish SARS-CoV-2 variants was probably linked to the low viral load. No amplification was obtained with SaS among all 35 negative TaqPath samples. Overall, 20% of samples which were typed as negative or undetermined with TaqPath, and among them, twelve were not typed even by SaS, but they were instead correctly identified with Novaplex. Although full-genome sequencing remains the elected method to characterize new strains, our data show the high ability of a SNP-based assay to identify VOCs, also resolving samples typed as undetermined with TaqPath.

Small animal models are of crucial importance for assessing COVID-19 countermeasures. Common laboratory mice would be well-suited for this purpose but are not susceptible to infection with wild-type SARS-CoV-2. However, the development of mouse-adapted virus strains has revealed key mutations in the SARS-CoV-2 spike protein that increase infectivity, and interestingly, many of these mutations are also present in naturally occurring SARS-CoV-2 variants of concern. This suggests that these variants might have the ability to infect common laboratory mice. Herein we show that the SARS-CoV-2 beta variant attains infectibility to BALB/c mice and causes pulmonary changes within 2–3 days post infection, consistent with results seen in other murine models of COVID-19, at a reasonable virus dose (2 × 105 PFU). The findings suggest that common laboratory mice can serve as the animal model of choice for testing the effectiveness of antiviral drugs and vaccines against SARS-CoV-2.

The high transmissibility, mortality, and morbidity rate of the SARS-CoV-2 Delta (B.1.617.2) variant have raised concerns regarding vaccine effectiveness (VE). To address this issue, all publications relevant to the effectiveness of vaccines against the Delta variant were searched in the Web of Science, Scopus, EMBASE, and Medline (via PubMed) databases up to 15 October 2021. A total of 15 studies (36 datasets) were included in the meta-analysis. After the first dose, the VE against the Delta variant for each vaccine was 0.567 (95% CI 0.520–0.613) for Pfizer-BioNTech, 0.72 (95% CI 0.589–0.822) for Moderna, 0.44 (95% CI 0.301–0.588) for AstraZeneca, and 0.138 (95% CI 0.076–0.237) for CoronaVac. Meta-analysis of 2,375,957 vaccinated cases showed that the Pfizer-BioNTech vaccine had the highest VE against the infection after the second dose, at 0.837 (95% CI 0.672–0.928), and third dose, at 0.972 (95% CI 0.96–0.978), as well as the highest VE for the prevention of severe infection or death, at 0.985 (95% CI 0.95–0.99), amongst all COVID-19 vaccines. The short-term effectiveness of vaccines, especially mRNA-based vaccines, for the prevention of the Delta variant infection, hospitalization, severe infection, and death is supported by this study. Limitations include a lack of long-term efficacy data, and under-reporting of COVID-19 infection cases in observational studies, which has the potential to falsely skew VE rates. Overall, this study supports the decisions by public health decision makers to promote the population vaccination rate to control the Delta variant infection and the emergence of further variants.

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with higher transmission potential have been emerging globally, including SARS-CoV-2 variants from the United Kingdom and South Africa. We report 4 travelers from Brazil to Japan in January 2021 infected with a novel SARS-CoV-2 variant with an additional set of mutations.

The ability of viruses to mutate and evade the human immune system and neutralizing antibodies remains an obstacle to antiviral and vaccine development. Many neutralizing antibodies, including some approved for emergency use authorization (EUA), reduced or lost activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Here, we introduce a geometric deep learning algorithm that efficiently enhances antibody affinity to achieve broader and more potent neutralizing activity against such variants. We demonstrate the utility of our approach on a human antibody P36-5D2, which is effective against SARS-CoV-2 Alpha, Beta, and Gamma but not Delta. We show that our geometric neural network model optimizes this antibody’s complementarity-determining region (CDR) sequences to improve its binding affinity against multiple SARS-CoV-2 variants. Through iterative optimization of the CDR regions and experimental measurements, we enable expanded antibody breadth and improved potency by ∼10- to 600-fold against SARS-CoV-2 variants, including Delta. We have also demonstrated that our approach can identify CDR changes that alleviate the impact of two Omicron mutations on the epitope. These results highlight the power of our deep learning approach in antibody optimization and its potential application to engineering other protein molecules. Our optimized antibodies can potentially be developed into antibody drug candidates for current and emerging SARS-CoV-2 variants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, is a readily transmissible and potentially deadly pathogen which is currently re-defining human susceptibility to pandemic viruses in the modern world. The recent emergence of several genetically distinct descendants known as variants of concern (VOCs) is further challenging public health disease management, due to increased rates of virus transmission and potential constraints on vaccine effectiveness. We report the isolation of SARS-CoV-2 VOCs imported into Australia belonging to the B.1.351 lineage, first described in the Republic of South Africa (RSA), and the B.1.1.7 lineage originally reported in the United Kingdom, and directly compare the replication kinetics of these two VOCs in Vero E6 cells. In this analysis, we also investigated a B.1.1.7 VOC (QLD1516/2021) carrying a 7-nucleotide deletion in the open reading frame 7a (ORF7a) gene, likely truncating and rendering the ORF7a protein of this virus defective. We demonstrate that the replication of the B.1.351 VOC (QLD1520/2020) in Vero E6 cells can be detected earlier than the B.1.1.7 VOCs (QLD1516/2021 and QLD1517/2021), before peaking at 48 h post infection (p.i.), with significantly higher levels of virus progeny. Whilst replication of the ORF7a defective isolate QLD1516/2021 was delayed longer than the other viruses, slightly more viral progeny was produced by the mutant compared to the unmutated isolate QLD1517/2021 at 72 h p.i. Collectively, these findings contribute to our understanding of SARS-CoV-2 replication and evolutionary dynamics, which have important implications in the development of future vaccination, antiviral therapies, and epidemiological control strategies for COVID-19.