Kylie S Carville1, Kristina A Grant2, Sheena G Sullivan3, James E Fielding4, Courtney R Lane5, Lucinda Franklin6, Julian Druce7, Heath A Kelly8. 1. Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia. Electronic address: kylie.carville@mh.org.au. 2. Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia. Electronic address: kristina.grant@mh.org.au. 3. WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia. Electronic address: sheena.sullivan@influenzacentre.org. 4. Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia. Electronic address: james.fielding@mh.org.au. 5. Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia; National Centre for Epidemiology and Population Health, The Australian National University, Canberra 0200, ACT, Australia. Electronic address: courtney.lane@mh.org.au. 6. Communicable Disease Epidemiology and Surveillance, Health Protection Branch, Victorian Government Department of Health, 14/50 Lonsdale Street, Melbourne 3000, VIC, Australia. Electronic address: Lucinda.Franklin@health.vic.gov.au. 7. Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia. Electronic address: julian.druce@mh.org.au. 8. Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth Street, Melbourne 3000, VIC, Australia; National Centre for Epidemiology and Population Health, The Australian National University, Canberra 0200, ACT, Australia. Electronic address: heath.kelly@mh.org.au.
Abstract
BACKGROUND: The influenza virus undergoes frequent antigenic drift, necessitating annual review of the composition of the influenza vaccine. Vaccination is an important strategy for reducing the impact and burden of influenza, and estimating vaccine effectiveness (VE) each year informs surveillance and preventative measures. We aimed to describe the influenza season and to estimate the effectiveness of the influenza vaccine in Victoria, Australia, in 2013. METHODS: Routine laboratory notifications, general practitioner sentinel surveillance (including a medical deputising service) data, and sentinel hospital admission surveillance data for the influenza season (29 April to 27 October 2013) were collated in Victoria, Australia, to describe influenza-like illness or confirmed influenza during the season. General practitioner sentinel surveillance data were used to estimate VE against medically-attended laboratory confirmed influenza. VE was estimated using the case test negative design as 1-adjusted odds ratio (odds of vaccination in cases compared with controls) × 100%. Cases tested positive for influenza while non-cases (controls) tested negative. Estimates were adjusted for age group, week of onset, time to swabbing and co-morbidities. RESULTS: The 2013 influenza season was characterised by relatively low activity with a late peak. Influenza B circulation preceded that of influenza A(H1)pdm09, with very little influenza A(H3) circulation. Adjusted VE for all influenza was 55% (95%CI: -11, 82), for influenza A(H1)pdm09 was 43% (95%CI: -132, 86), and for influenza B was 56% (95%CI: -51, 87) Imputation of missing data raised the influenza VE point estimate to 64% (95%CI: 13, 85). CONCLUSIONS: Clinicians can continue to promote a positive approach to influenza vaccination, understanding that inactivated influenza vaccines prevent at least 50% of laboratory-confirmed outcomes in hospitals and the community.
BACKGROUND: The influenza virus undergoes frequent antigenic drift, necessitating annual review of the composition of the influenza vaccine. Vaccination is an important strategy for reducing the impact and burden of influenza, and estimating vaccine effectiveness (VE) each year informs surveillance and preventative measures. We aimed to describe the influenza season and to estimate the effectiveness of the influenza vaccine in Victoria, Australia, in 2013. METHODS: Routine laboratory notifications, general practitioner sentinel surveillance (including a medical deputising service) data, and sentinel hospital admission surveillance data for the influenza season (29 April to 27 October 2013) were collated in Victoria, Australia, to describe influenza-like illness or confirmed influenza during the season. General practitioner sentinel surveillance data were used to estimate VE against medically-attended laboratory confirmed influenza. VE was estimated using the case test negative design as 1-adjusted odds ratio (odds of vaccination in cases compared with controls) × 100%. Cases tested positive for influenza while non-cases (controls) tested negative. Estimates were adjusted for age group, week of onset, time to swabbing and co-morbidities. RESULTS: The 2013 influenza season was characterised by relatively low activity with a late peak. Influenza B circulation preceded that of influenza A(H1)pdm09, with very little influenza A(H3) circulation. Adjusted VE for all influenza was 55% (95%CI: -11, 82), for influenza A(H1)pdm09 was 43% (95%CI: -132, 86), and for influenza B was 56% (95%CI: -51, 87) Imputation of missing data raised the influenza VE point estimate to 64% (95%CI: 13, 85). CONCLUSIONS: Clinicians can continue to promote a positive approach to influenza vaccination, understanding that inactivated influenza vaccines prevent at least 50% of laboratory-confirmed outcomes in hospitals and the community.
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