Related Experiment Video
Updated: Apr 7, 2026

A Luciferase-fluorescent Reporter Influenza Virus for Live Imaging and Quantification of Viral Infection
Published on: August 14, 2019
Logistic regression of attitudes and coverage for influenza vaccination among Italian Public Health medical residents
Introduction:
A few number of literature specifically addresses vaccination uptake among Public Health Residents (PHRs). Influenza vaccine attitudes and risk perceptions of PHRs across Italy were studied, contributing to literature on influenza vaccination uptake predictors, in particular among young physicians.
Methods:
An online survey was conducted in 25 Schools of Public Health in Italy in 2011-2012. Results were analysed using prevalence and logistic regression methods.
Results:
A total of 365 Italian public health residents were included in the study. Vaccination uptake was confirmed by 22.2 and 33.2% of PHRs in 2010-2011 and 2011-2012, respectively. For the 2010-2011 influenza season, vaccination was associated with male sex (adj-OR 3.43; 95% CI = 1.5-7.84) and vaccination history (adj-OR 29.44; 95% CI = 6.4-135.04). For the 2011-2012 season, vaccination was significantly associated with having had between one and three influenza vaccinations in the previous five years (adj-OR 11.56; 95% CI = 6.44-20.75) or more than three (adj-OR 13643; 95% CI = 30.8-604.7) and with individual participation in general population vaccination campaigns (adj-OR 1.85; 95% CI = 1.01-3.41).
Discussion:
Italian residents in public health have no confidence and a low personal risk perception about vaccinations therefore taking no measures to protect patients, general population and themselves. Annual influenza vaccination acceptance is associated with influenza vaccine uptake in the previous years and personal involvement in general population vaccination campaigns. These factors should be considered for the design of future campaigns targeting public health residents.
Related Concept Videos
Bias in Epidemiological Studies
Statistical Methods for Analyzing Epidemiological Data
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Steps in Outbreak Investigation
Causality in Epidemiology