Epidemiology of viral respiratory infections in Australian working-age adults (20-64 years): 2010-2013.

Acute respiratory infections cause significant morbidity and mortality accounting for 5.8 million deaths worldwide. In Australia, influenza-like illness (ILI), defined as cough, fever and fatigue is a common presentation in general practice and results in reduced productivity and lost working days. Little is known about the epidemiology of ILI in working-age adults. Using data from the ASPREN influenza surveillance network in Australia (2010-2013) we found that working-age adults made up 45.2% of all ILI notifications with 55% of samples positive for at least one respiratory virus. Viruses most commonly detected in our study included influenza A (20.6%), rhinovirus (18.6%), influenza B (6.2%), human meta-pneumovirus (3.4%), respiratory syncytial virus (3.1%), para-influenza virus (2.6%) and adenovirus (1.3%). We also demonstrated that influenza A is the predominant virus that increases ILI (by 1.2% per month for every positive influenza A case) in working-age adults during autumn-winter months while other viruses are active throughout the year. Understanding the epidemiology of viral respiratory infections through a year will help clinicians make informed decisions about testing, antibiotic and antiviral prescribing and when the beginning of the 'flu season' can be more confidently predicted.

Pooled influenza vaccine effectiveness estimates for Australia, 2012-2014.

Data were pooled from three Australian sentinel general practice influenza surveillance networks to estimate Australia-wide influenza vaccine coverage and effectiveness against community presentations for laboratory-confirmed influenza for the 2012, 2013 and 2014 seasons. Patients presenting with influenza-like illness at participating GP practices were swabbed and tested for influenza. The vaccination odds of patients testing positive were compared with patients testing negative to estimate influenza vaccine effectiveness (VE) by logistic regression, adjusting for age group, week of presentation and network. Pooling of data across Australia increased the sample size for estimation from a minimum of 684 to 3,683 in 2012, from 314 to 2,042 in 2013 and from 497 to 3,074 in 2014. Overall VE was 38% [95% confidence interval (CI) 24-49] in 2012, 60% (95% CI 45-70) in 2013 and 44% (95% CI 31-55) in 2014. For A(H1N1)pdm09 VE was 54% (95% CI-28 to 83) in 2012, 59% (95% CI 33-74) in 2013 and 55% (95% CI 39-67) in 2014. For A(H3N2), VE was 30% (95% CI 14-44) in 2012, 67% (95% CI 39-82) in 2013 and 26% (95% CI 1-45) in 2014. For influenza B, VE was stable across years at 56% (95% CI 37-70) in 2012, 57% (95% CI 30-73) in 2013 and 54% (95% CI 21-73) in 2014. Overall VE against influenza was low in 2012 and 2014 when A(H3N2) was the dominant strain and the vaccine was poorly matched. In contrast, overall VE was higher in 2013 when A(H1N1)pdm09 dominated and the vaccine was a better match. Pooling data can increase the sample available and enable more precise subtype- and age group-specific estimates, but limitations remain.