A third mRNA vaccine booster is recommended to improve immunity against SARS-CoV-2 in kidney transplant recipients (KTRs). However, the immunity against SARS-CoV-2 Ancestral strain and Delta and Omicron variants elicited by the third dose of inactivated booster vaccine in KTRs remains unknown.
The blood parameters related to blood cells count, hepatic function, kidney function, heart injury and immunity were explored clinically from laboratory examinations. SARS-CoV-2 specific antibody IgG titer was detected using an enzyme-linked immunosorbent assay. Cellular immunity was analyzed using interferon-γ enzyme-linked immunospot assay.
The results showed that there were no severe adverse effects and apparent changes of clinical laboratory biomarkers in KTRs and healthy volunteers (HVs) after homologous inactivated vaccine booster. A third dose of inactivated vaccine booster significantly increased anti-Ancestral-spike-trimer-IgG and anti-Ancestral-receptor binding domain (RBD)-IgG titers in KTRs and HVs compared with the second vaccination. However, the anti-Delta-RBD-IgG and anti-Omicron-RBD-IgG titers were significantly lower than anti-Ancestral-RBD-IgG titer in KTRs and HVs after the third dose. Notably, only 25.6% (10/39) and 10.3% (4/39) of KTRs had seropositivity for anti-Delta-RBD-IgG and anti-Omicron-RBD-IgG after booster, which were significantly lower than HVs (anti-Delta-RBD-IgG: 100%, anti-Omicron-RBD-IgG: 77.8%). Ancestral strain nucleocapsid protein and spike specific T cell frequency after booster was not significantly increased in KTRs compared with the second dose, significantly lower than that in HVs. Moreover, 33.3% (12/36), 14.3% (3/21) and 14.3% (3/21) of KTRs were positive for the Ancestral strain and Delta and Omicron spike-specific T cells, which were significantly lower than HVs (Ancestral: 80.8%, Delta: 53.8%, and Omicron: 57.7%).
A third dose of inactivated booster vaccine may significantly increase humoral immunity against the Ancestral strain in KTRs, while humoral and cellular immunity against the Delta and Omicron variants were still poor in KTRs.

UNASSIGNED: The Delta variant of concern (VOC) is rapidly becoming the dominant strain globally. We report the clinical characteristics and severity of hospitalized patients infected with Delta and Beta VOCs during the local outbreak in Harbin, Heilongjiang Province, China, and the effect of vaccines on the Delta variant.
UNASSIGNED: We collected a total of 735 COVID-19 patients from the First Affiliated Hospital of Harbin Medical University, including 96 cases infected with the Delta VOC and 639 cases infected with the Beta VOC. Demographic, clinical characteristic and laboratory findings were collected and compared.
UNASSIGNED: Differences in viral shedding, IgG and IgM levels, and the neutrophil-to-lymphocyte ratio were noted between the Delta and Beta VOCs (p < 0.05). Survival analysis of the two groups revealed longer viral shedding of the Delta VOC (p < 0.05). For the Delta VOC, the longer the vaccination period, the lower the IgG and IgM levels. IgM levels were higher in the convalescent plasma group, whereas lymphocyte counts were lower.
UNASSIGNED: Delta VOC virus shedding was longer compared with Beta VOC shedding. Vaccination with inactivated vaccines can reduce the severe illness rate of the Delta VOC. IgG and IgM levels are reduced as the time period between the first and second vaccine doses increases.

To investigate the changes of Spike protein-HLA binding affinity profiles between the Wuhan strain and two dominant variants, the Delta and the Omicron strains, among the Taiwanese, the British and the Russian populations.
The HLA frequencies and the HLA-peptide binding affinity profiles in the T-CoV database were combined to conduct the study. We focused on the public alleles in the three populations (HLA-A, HLA-B, HLA-C, HLA-DRB1, and/or HLA-DPA1/DPB1 alleles) and the altered peptides of the spike protein (compared to the Wuhan strain) in the Delta G/478K·V1 (B.1.617.2 + AY.1 + AY.2) and the Omicron (BA.1) strains.
For the Delta strain, tight bindings of the altered peptides to the HLA alleles decrease in all three populations and almost vanish in the Taiwanese population. For the Omicron strain, tight bindings are mostly preserved for both HLA classes and in the Taiwanese and the British populations, with a slight reduction in HLA class II in the Taiwanese (1.4%), while the Russian population preserves a relatively high fraction of tight bindings for both HLA classes.
We comprehensively reported the changes in the HLA-associated SARS-CoV-2 Spike protein peptide binding profiles among the Taiwanese, the British, and the Russian populations. Further studies are needed to understand the immunological mechanisms and the clinical value of our findings.

The newly discovered COVID variant B.1.1.529 in Botswana has more than 30 mutations in spike and many other in non-spike proteins, far more than any other SARS-CoV-2 variant accepted as a variant of concern by the WHO and officially named Omicron, and has sparked concern among scientists and the general public. Our findings provide insights into structural modification caused by the mutations in the Omicrons receptor-binding domain and look into the effects on interaction with the hosts neutralizing antibodies CR3022, B38, CB6, P2B-2F6, and REGN, as well as ACE2R using an in silico approach. Computational analysis revealed that the Omicron variant has a higher binding affinity for the human ACE2 receptor than the wild and Delta (AY.1 and AY.2 strains), but lower than the Delta AY.3 strain. MD simulation and docking analysis suggest that the omicron and Delta AY.3 were found to have relatively unstable RBD structures and hampered interactions with antibodies more than wild and Delta (AY.1 and AY.2), which may lead to relatively more pathogenicity and antibody escape. In addition, we observed lower binding affinity of Omicron for human monoclonal antibodies (CR3022, B38, CB6, and P2B2F6) when compared to wild and Delta (AY.1 & AY.2). However, the binding affinity of Omicron RBD variants for CR3022, B38, and P2B2F6 antibodies is lower as compared to Delta AY.3, which might promote immune evasion and reinfection and needs further experimental investigation.

Since September 2020, the SARS-CoV-2 variants have gained their dominance worldwide, especially in Kenya, Italy, France, the UK, Turkey, Indonesia, India, Finland, Ireland, Singapore, Denmark, Germany, and Portugal. In this study, we developed a model on the frequency of delta variants across 28 countries (R2= 0.1497), displaying the inheritance of mutations during the generation of the delta variants with 123,526 haplotypes. The country-wise haplotype network showed the distribution of haplotypes in USA (10,174), Denmark (5,637), India (4,089), Germany (2,350), Netherlands (1,899), Sweden (1,791), Italy (1,720), France (1,293), Ireland (1,257), Belgium (1,207), Singapore (1,193), Portugal (1,184) and Spain (1,133). Our analysis shows the highest haplotype in Europe with 84% and the lowest in Australia with 0.00001%. A model of scatter plot was generated with a regression line which provided the estimated rate of mutation, including 24.048 substitutions yearly. Our study concluded that the high global prevalence of the delta variants is due to a high frequency of infectivity, supporting the paradigm shift of the viral variants.

The coronavirus disease 2019 (COVID-19) pandemic has caused a tremendous global impact both socially and economically. The mechanisms behind the disparity in the severity, vaccine coverage, and variant replacement patterns across European countries are unclear. In this work, we aim to reveal the possible reasons via data visualization and model fitting. We developed a model with a vaccination component to simulate the mortality waves in these countries. Deaths averted by the vaccination campaign were estimated. Finally, we discuss the potential reasons behind the differences in vaccine coverage across European countries. Contemporary transportation and global trade bring significant convenience to our daily life but also facilitate the spread of the novel virus COVID-19 to anywhere globally within a short time. The observations and results in this work highlight the importance of the global campaign to mitigate the COVID-19 pandemic and future pandemics under the One Health approach.

Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers (R0) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: -0.38, 1.25) in February 2021, and that the VOC had a relatively high R0. The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed.

To evaluate the necessity of Covid-19 vaccination in children aged < 12 y by comparing the clinical characteristics between unvaccinated children aged < 12 y and vaccinated patients aged ≥ 12y during the Delta surge (B.1.617.2) in Putian, Fujian, China.
A total of 226 patients with SARS-Cov-2 Delta variant (B.1.167.2; confirmed by Real-time PCR positivity and sequencing) were enrolled from Sep 10th to Oct 20th, 2021, including 77 unvaccinated children (aged < 12y) and 149 people aged ≥ 12y, mostly vaccinated. The transmission route was explored and the clinical data of two groups were compared; The effect factors for the time of the nucleic acid negativization (NAN) were examined by R statistical analysis.
The Delta surge in Putian spread from children in schools to factories, mostly through family contact. Compared with those aged ≥ 12y, patients aged < 12y accounted for 34.07% of the total and showed milder fever, less cough and fatigue; they reported higher peripheral blood lymphocyte counts [1.84 (1.32, 2.71)×10^9/L vs. 1.31 (0.94, 1.85)×10^9/L; p<0.05), higher normal CRP rate (92.21% vs. 57.72%), lower IL-6 levels [5.28 (3.31, 8.13) vs. 9.10 (4.37, 15.14); p<0.05]. Upon admission, their COVID19 antibodies (IgM and IgG) and IgG in convalescence were lower [0.13 (0.00, 0.09) vs. 0.12 (0.03, 0.41), p<0.05; 0.02 (0.00, 0.14) vs. 1.94 (0.54, 6.40), p<0.05; 5.46 (2.41, 9.26) vs. 73.63 (54.63, 86.55), p<0.05, respectively], but longer NAN time (18 days vs. 16 days, p=0.13).
Unvaccinated children may be an important link in the transmission of SARS-CoV-2 delta variant (B1.617.2), which indicated an urgent need of vaccination for this particular population.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic. With the continuous evolution of the viral genome, SARS-CoV-2 has evolved many variants. B.1.617.2, also called Delta, is one of the most concerned variants. The Delta variant was first reported in India at the end of 2020 but has spread globally, by now, to 135 countries and is not stand still. Delta shared some mutations with other variants, and owned its special mutations on spike proteins, which may be responsible for its strong transmission and increasing virulence. Under these circumstances, a systematic summary of Delta is necessary. This review will focus on the Delta variant. We will describe all the characteristics of Delta (including biological features and clinical characteristics), analyze potential reasons for its strong transmission, and provide potential protective ways for combating Delta.

Indonesia is one of the Southeast Asian countries with high case numbers of COVID-19 with up to 4.2 million confirmed cases by 29 October 2021. Understanding the genome of SARS-CoV-2 is crucial for delivering public health intervention as certain variants may have different attributes that can potentially affect their transmissibility, as well as the performance of diagnostics, vaccines, and therapeutics.
We aimed to investigate the dynamics of circulating SARS-CoV-2 variants over a 15-month period in Bogor and its surrounding areas in correlation with the first and second wave of COVID-19 in Indonesia.
Nasopharyngeal and oropharyngeal swab samples collected from suspected patients from Bogor, Jakarta and Tangerang were confirmed for SARS-CoV-2 infection with RT-PCR. RNA samples of those confirmed patients were subjected to whole genome sequencing using the ARTIC Network protocol and sequencer platform from Oxford Nanopore Technologies (ONT).
We successfully identified 16 lineages and six clades out of 202 samples (male n = 116, female n = 86). Genome analysis revealed that Indonesian lineage B.1.466.2 dominated during the first wave (n = 48, 23.8%) while Delta variants (AY.23, AY.24, AY.39, AY.42, AY.43 dan AY.79) were dominant during the second wave (n = 53, 26.2%) following the highest number of confirmed cases in Indonesia. In the spike protein gene, S_D614G and S_P681R changes were dominant in both B.1.466.2 and Delta variants, while N439K was only observed in B.1.466.2 (n = 44) and B.1.470 (n = 1). Additionally, the S_T19R, S_E156G, S_F157del, S_R158del, S_L452R, S_T478K, S_D950N and S_V1264L changes were only detected in Delta variants, consistent with those changes being characteristic of Delta variants in general.
We demonstrated a shift in SARS-CoV-2 variants from the first wave of COVID-19 to Delta variants in the second wave, during which the number of confirmed cases surpassed those in the first wave of COVID-19 pandemic. Higher proportion of unique mutations detected in Delta variants compared to the first wave variants indicated potential mutational effects on viral transmissibility that correlated with a higher incidence of confirmed cases. Genomic surveillance of circulating variants, especially those with higher transmissibility, should be continuously conducted to rapidly inform decision making and support outbreak preparedness, prevention, and public health response.