ABSTRACT
BACKGROUND: Little has been published on predictors of prolonged sick leaves during the COVID-19 pandemic. This study aims to determine the rate of COVID-19 infections among healthcare workers (HCWs) and to identify the predictors of longer sick leave days. METHODS: We identified predictors of longer sick leave using linear regression analysis in a cross-sectional study design. RESULTS: Thirty-three percent of the total workforce contracted COVID-19. On average, HCWs took 12.5 sick leave days after COVID-19 infection. The regression analysis revealed that older employees, nurses, and those who caught COVID-19 earlier in the pandemic were more likely to take longer sick leave. CONCLUSIONS: Age, job position, and month of infection predicted sick leave duration among HCWs in our sample. Results imply that transmission was most likely community-based. Public health interventions should consider these factors when planning for future pandemics.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , Tertiary Care Centers , Cross-Sectional Studies , Health Personnel , Sick LeaveABSTRACT
Carbapenem resistance in Enterobacteriaceae, Acinetobacter baumannii and Pseudomonas aeruginosa is increasing worldwide, which has led the World Health Organization (WHO) to list these bacteria in the critical priority pathogens group. Infections by such pathogens pose a serious threat to hospitalised patients and are associated with clinical and economic consequences. What worsens the case is the weak pipeline of available antimicrobial agents to treat such infections and the absence of new drugs. The aim of this review was to shed light on all studies tackling carbapenem resistance in Enterobacteriaceae, A. baumannii and P. aeruginosa in the Eastern Mediterranean region, with indication for each country, description of studies timeline, prevalence of carbapenem resistance, and carbapenem resistance-encoding genes detected in these countries.
