Simultaneous monitoring of SARS-CoV-2 and bacterial profiles from the air of hospital environments with COVID-19-affected patients.

The SARS-CoV-2 presence and the bacterial community profile in air samples collected at the Intensive Care Unit (ICU) of the Operational Unit of Infectious Diseases of Santa Caterina Novella Hospital in Galatina (Lecce, Italy) have been evaluated in this study. Air samplings were performed in different rooms of the ICU ward with and without COVID-19 patients. No sample was found positive to SARS-CoV-2, according to Allplex 2019-nCoV Assay. The airborne bacterial community profiles determined by the 16S rRNA gene metabarcoding approach up to the species level were characterized by richness and biodiversity indices, Spearman correlation coefficients, and Principal Coordinate Analysis. Pathogenic and non-pathogenic bacterial species, also detected in outdoor air samples, were found in all collected indoor samples. Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and others coagulase-negative staphylococci, detected at high relative abundances in all the patients' rooms, were the most abundant pathogenic species. The highest mean relative abundance of S. pettenkoferi and C. tuberculostearicum suggested that they were likely the main pathogens of COVID-19 patients at the ICU ward of this study. The identification of nosocomial pathogens representing potential patients' risks in ICU COVID-19 rooms and the still controversial airborne transmission of the SARS-CoV-2 are the main contributions of this study. Supplementary Information: The online version contains supplementary material available at 10.1007/s10453-022-09754-7.

Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples.

The compositional analysis of 16S rRNA gene sequencing datasets is applied to characterize the bacterial structure of airborne samples collected in different locations of a hospital infection disease department hosting COVID-19 patients, as well as to investigate the relationships among bacterial taxa at the genus and species level. The exploration of the centered log-ratio transformed data by the principal component analysis via the singular value decomposition has shown that the collected samples segregated with an observable separation depending on the monitoring location. More specifically, two main sample clusters were identified with regards to bacterial genera (species), consisting of samples mostly collected in rooms with and without COVID-19 patients, respectively. Human pathogenic genera (species) associated with nosocomial infections were mostly found in samples from areas hosting patients, while non-pathogenic genera (species) mainly isolated from soil were detected in the other samples. Propionibacterium acnes, Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and jeikeium were the main pathogenic species detected in COVID-19 patients' rooms. Samples from these locations were on average characterized by smaller richness/evenness and diversity than the other ones, both at the genus and species level. Finally, the ρ metrics revealed that pairwise positive associations occurred either between pathogenic or non-pathogenic taxa.

Prevalence and distribution of human papillomavirus genotype in south eastern Italy, in the period 2006-2011: implications for intervention.

Persistent infection of High Risk (HR) Human papillomavirus (HPV) infection can lead to cervical cancer. The HPV genotypes are found worldwide, but important regional variations have been found. For a population-based HPV type prevalence study to assess the effect of existing and new prevention methods, frequently updated information on the burden of cervical cancer is essential. We evaluated the prevalence of HPV genotypes in a volunteer population screened for cervical cancer at the Local Health Unit (LHU) of Lecce. A total of 9,720 women were studied. The tests were performed by INNO-Lipa HPV Genotyping and LINEAR ARRAY HPV Genotyping Test. The overall HPV prevalence was 29.7% (95% CI, 28.8-30.6) for any HPV DNA. The prevalent type for all age groups was HPV 16 (7.4%; CI, 6.9-7.9) followed by HPV 31 (3.4%; CI, 3.0-3.7), 51 (3.0%; CI, 2.6-3.3), 52 (2.7%; CI, 2.3-3.0) and 58 (2.4%; CI, 2.1-2.7). HPV 53 was the most common low-risk HPV type with prevalence rate of 3.5 (CI, 3.1-3.8), followed by HPV 66 (3.0; CI, 2.6-3.3), 6 (2.9; CI, 2.6-3.2) and 42 (2.5; CI, 2.2-2.8). Multiple infections were present in 13.6% of HPV-tested women (CI, 12.9-14.3). Among these, the most common combination was of HPV 16 and HPV 52 genotypes. This study reports high prevalence of HPV infection and may serve as a valuable reference for assessing the impact of HPV vaccination programs. Furthermore, it supports the need for new vaccines that contain the most common HPV genotypes present in the population.