Which healthcare workers work with acute respiratory illness? Evidence from Canadian acute-care hospitals during 4 influenza seasons: 2010-2011 to 2013-2014.

BACKGROUND: Healthcare workers (HCWs) are at risk of acquiring and transmitting respiratory viruses while working in healthcare settings. OBJECTIVES: To investigate the incidence of and factors associated with HCWs working during an acute respiratory illness (ARI). METHODS: HCWs from 9 Canadian hospitals were prospectively enrolled in active surveillance for ARI during the 2010-2011 to 2013-2014 influenza seasons. Daily illness diaries during ARI episodes collected information on symptoms and work attendance. RESULTS: At least 1 ARI episode was reported by 50.4% of participants each study season. Overall, 94.6% of ill individuals reported working at least 1 day while symptomatic, resulting in an estimated 1.9 days of working while symptomatic and 0.5 days of absence during an ARI per participant season. In multivariable analysis, the adjusted relative risk of working while symptomatic was higher for physicians and lower for nurses relative to other HCWs. Participants were more likely to work if symptoms were less severe and on the illness onset date compared to subsequent days. The most cited reason for working while symptomatic was that symptoms were mild and the HCW felt well enough to work (67%). Participants were more likely to state that they could not afford to stay home if they did not have paid sick leave and were younger. CONCLUSIONS: HCWs worked during most episodes of ARI, most often because their symptoms were mild. Further data are needed to understand how best to balance the costs and risks of absenteeism versus those associated with working while ill.

High throughput sequencing methods and analysis for microbiome research.

High-throughput sequencing technology is rapidly improving in quality, speed and cost. It is therefore becoming more widely used to study whole communities of prokaryotes in many niches. This review discusses these techniques, including nucleic acid extraction from different environments, sample preparation and high-throughput sequencing platforms. We also discuss commonly used and recently developed bioinformatic tools applied to microbiomes, including analyzing amplicon sequences, metagenome shotgun sequences and metatranscriptome sequences. This field is relatively new and rapidly evolving, thus we hope that this review will provide a baseline for understanding these methods of microbiome analyses. Additionally, we seek to stimulate others to solve the many problems that still exist with the sensitivity, specificity and interpretation of high throughput microbiome sequence analysis.

Comparative meta-RNA-seq of the vaginal microbiota and differential expression by Lactobacillus iners in health and dysbiosis.

BACKGROUND: Bacterial vaginosis (BV), the most common vaginal condition of reproductive-aged women, is associated with a highly diverse and heterogeneous microbiota. Here we present a proof-of-principle analysis to uncover the function of the microbiota using meta-RNA-seq to uncover genes and pathways that potentially differentiate healthy vaginal microbial communities from those in the dysbiotic state of bacterial vaginosis (BV). RESULTS: The predominant organism, Lactobacillus iners, was present in both conditions and showed a differing expression profile in BV compared to healthy. Despite its minimal genome, L. iners differentially expressed over 10% of its gene complement. Notably, in a BV environment L. iners increased expression of a cholesterol-dependent cytolysin, and of mucin and glycerol transport and related metabolic enzymes. Genes belonging to a CRISPR system were greatly upregulated suggesting that bacteriophage influence the community. Reflective of L. iners, the bacterial community as a whole demonstrated a preference for glycogen and glycerol as carbon sources under BV conditions. The predicted end-products of metabolism under BV conditions include an abundance of succinate and other short-chain fatty-acids, while healthy conditions are predicted to largely contain lactic acid. CONCLUSIONS: Our study underscores the importance of understanding the functional activity of the bacterial community in addition to characterizing the population structure when investigating the human microbiome.