Risk of hospitalization and vaccine effectiveness among COVID-19 patients in the UAE during the Delta and Omicron outbreaks.

Introduction: A rapid increase in COVID-19 cases due to the spread of the Delta and Omicron variants in vaccinated populations has raised concerns about the hospitalization risk associated with, and the effectiveness of, COVID-19 vaccines. Method: This case-control study aims to determine the hospitalization risk associated with the inactivated BBIBP-CorV (Sinopharm) and mRNA BNT162b2 (Pfizer-BionTech) vaccines, and their effectiveness reducing the rate of hospital admission between 28 May 2021 and 13 January 2022, during the Delta and Omicron outbreaks. The estimation of vaccine effectiveness of 4,618 samples was based on the number of patients hospitalized at different vaccination statuses, adjusted for confounding variables. Results: Hospitalization risk increases in patients affected with the Omicron variant if patients are aged ≤ 18 years (OR 6.41, 95% CI 2.90 to 14.17; p < 0.001), and in patients affected with the Delta variant if they are aged > 45 years (OR 3.41, 95% CI 2.21 to 5.50; p < 0.001). Vaccine effectiveness reducing the rate of hospital admission for fully vaccinated participants infected with the Delta and Omicron variants was similar for both the BBIBP-CorV (94%, 95% CI 90% to 97%; 90%, 95% CI 74% to 96%) and BNT162b2 vaccines (95%, 95% CI 61% to 99.3%; 94%, 95% CI 53% to 99%), respectively. Discussion: The BBIBP-CorV and BNT162b2 vaccines utilized in the UAE vaccination program were highly effective in reducing the rate of COVID-19-related hospitalization during the Delta and Omicron outbreaks, and further effort must be taken to achieve high vaccine coverage rates in children and adolescents in the global context to reduce the hospitalization risk associated with COVID-19 on an international scale.

Genomic epidemiology and emergence of SARS-CoV-2 variants of concern in the United Arab Emirates.

Since the declaration of SARS-CoV-2 outbreak as a pandemic, the United Arab Emirates (UAE) public health authorities have adopted strict measures to reduce transmission as early as March 2020. As a result of these measures, flight suspension, nationwide RT-PCR and surveillance of viral sequences were extensively implemented. This study aims to characterize the epidemiology, transmission pattern, and emergence of variants of concerns (VOCs) and variants of interests (VOIs) of SARS-CoV-2 in the UAE, followed by the investigation of mutations associated with hospitalized cases. A total of 1274 samples were collected and sequenced from all seven emirates between the period of 25 April 2020 to 15 February 2021. Phylogenetic analysis demonstrated multiple introductions of SARS-CoV-2 into the UAE in the early pandemic, followed by a local spread of root clades (A, B, B.1 and B.1.1). As the international flight resumed, the frequencies of VOCs surged indicating the January peak of positive cases. We observed that the hospitalized cases were significantly associated with the presence of B.1.1.7 (p < 0.001), B.1.351 (p < 0.001) and A.23.1 (p = 0.009). Deceased cases are more likely to occur in the presence of B.1.351 (p < 0.001) and A.23.1 (p = 0.022). Logistic and ridge regression showed that 51 mutations are significantly associated with hospitalized cases with the highest proportion originated from S and ORF1a genes (31% and 29% respectively). Our study provides an epidemiological insight of the emergence of VOCs and VOIs following the borders reopening and worldwide travels. It provides reassurance that hospitalization is markedly more associated with the presence of VOCs. This study can contribute to understand the global transmission of SARS-CoV-2 variants.

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.

BACKGROUND: Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. RESULTS: We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database. CONCLUSIONS: Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.