ABSTRACT
Objectives: There is an urgent need to review the status of COVID-19 vaccine immunization in pregnant women globally, so that adverse outcomes may be prevented. In this study, we performed a systematic review to evaluate the probable outcomes of COVID-19 vaccination in pregnant women. Materials and methods:An electronic search over three months (June 15-August 15, 2021) was conducted. Original studies evaluating safety concerns in pregnant women for COVID-19 vaccination were included. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 guidelines were used for data collection and reporting of findings. Results:COVID-19 vaccination in pregnant women was not associated with increased adverse effects or complications to the mother as well as the developing fetus or new-born compared to non-vaccinated pregnant women. Vaccinated pregnant women showed a robust immune response against COVID-19 infection. Conclusion:COVID-19 vaccination during pregnancy causes no significant health risks for the mother or the developing fetus or new-born.
ABSTRACT
Background: Emergence of the new SARS-CoV-2 variant B.1.1.529 worried health policy makers worldwide due to a large number of mutations in its genomic sequence, especially in the spike protein region. The World Health Organization (WHO) designated this variant as a global variant of concern (VOC), which was named "Omicron." Following Omicron's emergence, a surge of new COVID-19 cases was reported globally, primarily in South Africa. Objective: The aim of this study was to understand whether Omicron had an epidemiological advantage over existing variants. Methods: We performed an in silico analysis of the complete genomic sequences of Omicron available on the Global Initiative on Sharing Avian Influenza Data (GISAID) database to analyze the functional impact of the mutations present in this variant on virus-host interactions in terms of viral transmissibility, virulence/lethality, and immune escape. In addition, we performed a correlation analysis of the relative proportion of the genomic sequences of specific SARS-CoV-2 variants (in the period from October 1 to November 29, 2021) with matched epidemiological data (new COVID-19 cases and deaths) from South Africa. Results: Compared with the current list of global VOCs/variants of interest (VOIs), as per the WHO, Omicron bears more sequence variation, specifically in the spike protein and host receptor-binding motif (RBM). Omicron showed the closest nucleotide and protein sequence homology with the Alpha variant for the complete sequence and the RBM. The mutations were found to be primarily condensed in the spike region (n=28-48) of the virus. Further mutational analysis showed enrichment for the mutations decreasing binding affinity to angiotensin-converting enzyme 2 receptor and receptor-binding domain protein expression, and for increasing the propensity of immune escape. An inverse correlation of Omicron with the Delta variant was noted (r=-0.99, P<.001; 95% CI -0.99 to -0.97) in the sequences reported from South Africa postemergence of the new variant, subsequently showing a decrease. There was a steep rise in new COVID-19 cases in parallel with the increase in the proportion of Omicron isolates since the report of the first case (74%-100%). By contrast, the incidence of new deaths did not increase (r=-0.04, P>.05; 95% CI -0.52 to 0.58). Conclusions: In silico analysis of viral genomic sequences suggests that the Omicron variant has more remarkable immune-escape ability than existing VOCs/VOIs, including Delta, but reduced virulence/lethality than other reported variants. The higher power for immune escape for Omicron was a likely reason for the resurgence in COVID-19 cases and its rapid rise as the globally dominant strain. Being more infectious but less lethal than the existing variants, Omicron could have plausibly led to widespread unnoticed new, repeated, and vaccine breakthrough infections, raising the population-level immunity barrier against the emergence of new lethal variants. The Omicron variant could have thus paved the way for the end of the pandemic.
ABSTRACT
BACKGROUND AND OBJECTIVES: India had faced a devastating second outbreak of COVID-19 infection, in which a majority of the viral sequences were found to be of the B.1.617.2 lineage (Delta-variant). While India and the world focused on vaccination, reports of vaccine-immunity evasion by the virus, termed "breakthrough cases", emerged worldwide. Our study was focused on the primary objective to identify the mutations associated with breakthrough infections SARS-CoV-2. METHODS: In our study, we extracted the SARS-CoV-2 RNA (ribonucleic acid) from reverse transcription-polymerase chain reaction (RT-PCR) positive COVID-19 patients, and 150 random samples were sent for sequencing to the Centre for Cellular & Molecular Biology, Hyderabad. Whole genome sequences of 150 SARS-CoV-2 viral samples were analyzed thoroughly. We mostly found B.1.617 and its sub-lineages in the genomic sequencing results. RESULTS AND INTERPRETATION: On further analysis of patient data, it was seen that nine patients had been vaccinated against the SARS-CoV-2 previously. These nine patients had B.1.617/B.1 or A strains, and all of them had similar genomic variations in spike proteins as well as non-structural proteins (NSPs). The mutations seen in these sequences in the Spike (S), NSPs, and open reading frame (ORF) regions would have produced amino acid changes known to improve viral replication, confer drug resistance, influence host-cell interaction, and lead to antigenic drift. CONCLUSIONS: Increased virulence culminating in vaccine immunity evasion may be inferred from these specific mutations. Our study adds to the growing body of evidence linking rapidly emerging mutations in the S (Spike) and ORF genes of the SARS-CoV-2 genome to immune evasion.
ABSTRACT
Background Since the start of the COVID-19 pandemic, health policymakers globally have been attempting to predict an impending wave of COVID-19. India experienced a devastating second wave of COVID-19 in the late first week of May 2021. We retrospectively analyzed the viral genomic sequences and epidemiological data reflecting the emergence and spread of the second wave of COVID-19 in India to construct a prediction model. Objective We aimed to develop a bioinformatics tool that can predict an impending COVID-19 wave. Methods We analyzed the time series distribution of genomic sequence data for SARS-CoV-2 and correlated it with epidemiological data for new cases and deaths for the corresponding period of the second wave. In addition, we analyzed the phylodynamics of circulating SARS-CoV-2 variants in the Indian population during the study period. Results Our prediction analysis showed that the first signs of the arrival of the second wave could be seen by the end of January 2021, about 2 months before its peak in May 2021. By the end of March 2021, it was distinct. B.1.617 lineage variants powered the wave, most notably B.1.617.2 (Delta variant). Conclusions Based on the observations of this study, we propose that genomic surveillance of SARS-CoV-2 variants, complemented with epidemiological data, can be a promising tool to predict impending COVID-19 waves.