A systematic review and meta-analysis on the effectiveness of bivalent mRNA booster vaccines against Omicron variants.

BACKGROUND: A global shift to bivalent mRNA vaccines is ongoing to counterbalance the diminishing effectiveness of the original monovalent vaccines due to the evolution of SARS-CoV-2 variants, yet substantial variation in the bivalent vaccine effectiveness (VE) exists across studies and a complete picture is lacking. METHODS: We searched papers evaluating absolute or relative effectiveness of SARS-CoV-2 BA.1 type or BA.4/5 type bivalent mRNA vaccines on eight publication databases published from September 1st, 2022, to November 8th, 2023. Pooled VE against Omicron-associated infection and severe events (hospitalization and/or death) was estimated in reference to unvaccinated, ≥2 original monovalent doses, and ≥ 3 original monovalent doses. RESULTS: From 630 citations identified, 28 studies were included, involving 55,393,303 individuals. Bivalent boosters demonstrated higher effectiveness against symptomatic or any infection for all ages combined, with an absolute VE of 53.5 % (95 % CI: -22.2-82.3 %) when compared to unvaccinated and relative VE of 30.8 % (95 % CI: 22.5-38.2 %) and 28.4 % (95 % CI: 10.2-42.9 %) when compared to ≥ 2 and ≥ 3 original monovalent doses, respectively. The corresponding VE estimates for adults ≥ 60 years old were 22.5 % (95 % CI: 16.8-39.8 %), 31.4 % (95 % CI: 27.7-35.0 %), and 30.6 % (95 % CI: -13.2-57.5 %). Pooled bivalent VE estimates against severe events were higher, 72.9 % (95 % CI: 60.5-82.4 %), 57.6 % (95 % CI: 42.4-68.8 %), and 62.1 % (95 % CI: 54.6-68.3 %) for all ages, and 72.0 % (95 % CI: 51.4-83.9 %), 63.4 % (95 % CI: 41.0-77.3 %), and 60.7 % (95 % CI: 52.4-67.6 %) for adults ≥ 60 years old, compared to unvaccinated, ≥2 original monovalent doses, and ≥ 3 original monovalent doses, respectively. CONCLUSIONS: The bivalent boosters demonstrated superior protection against severe outcomes than the original monovalent boosters across age groups, highlighting the critical need for improving vaccine coverage, especially among the vulnerable older subpopulation.

Multiblock partial least squares and rank aggregation: Applications to detection of bacteriophages associated with antimicrobial resistance in the presence of potential confounding factors.

Urban environments, characterized by bustling mass transit systems and high population density, host a complex web of microorganisms that impact microbial interactions. These urban microbiomes, influenced by diverse demographics and constant human movement, are vital for understanding microbial dynamics. We explore urban metagenomics, utilizing an extensive dataset from the Metagenomics & Metadesign of Subways & Urban Biomes (MetaSUB) consortium, and investigate antimicrobial resistance (AMR) patterns. In this pioneering research, we delve into the role of bacteriophages, or "phages"-viruses that prey on bacteria and can facilitate the exchange of antibiotic resistance genes (ARGs) through mechanisms like horizontal gene transfer (HGT). Despite their potential significance, existing literature lacks a consensus on their significance in ARG dissemination. We argue that they are an important consideration. We uncover that environmental variables, such as those on climate, demographics, and landscape, can obscure phage-resistome relationships. We adjust for these potential confounders and clarify these relationships across specific and overall antibiotic classes with precision, identifying several key phages. Leveraging machine learning tools and validating findings through clinical literature, we uncover novel associations, adding valuable insights to our comprehension of AMR development.