Real-time real-world analysis of seasonal influenza vaccine effectiveness: method development and assessment of a population-based cohort in Stockholm County, Sweden, seasons 2011/12 to 2014/15

Abstract

Real-world estimates of seasonal influenza vaccine effectiveness (VE) are important for early detection of vaccine failure. We developed a method for evaluating real-time in-season vaccine effectiveness (IVE) and overall seasonal VE. In a retrospective, register-based, cohort study including all two million individuals in Stockholm County, Sweden, during the influenza seasons from 2011/12 to 2014/15, vaccination status was obtained from Stockholm’s vaccine register. Main outcomes were hospitalisation or primary care visits for influenza (International Classification of Disease (ICD)-10 codes J09-J11). VE was assessed using Cox multivariate stratified and non-stratified analyses adjusting for age, sex, socioeconomic status, comorbidities and previous influenza vaccinations. Stratified analyses showed moderate VE in prevention of influenza hospitalisations among chronically ill adults ≥ 65 years in two of four seasons, and lower but still significant VE in one season; 53% (95% confidence interval (CI): 33–67) in 2012/13, 55% (95% CI: 25–73) in 2013/14 and 18% (95% CI: 3–31) in 2014/15. In conclusion, seasonal influenza vaccination was associated with substantial reductions in influenza-specific hospitalisation, particularly in adults ≥ 65 years with underlying chronic conditions. With the use of population-based patient register data on influenza-specific outcomes it will be possible to obtain real-time estimates of seasonal influenza VE.

Mid-season real-time estimates of seasonal influenza vaccine effectiveness in persons 65 years and older in register-based surveillance, Stockholm County, Sweden, and Finland, January 2017

“…Data from VAL, Vaccinera and SmiNet were linked using the same PIN (for details on data sources see [1,3,4]). VAL was used for obtaining data on in- and outpatient diagnoses, comorbidities, age and sex as well as the Stockholm Mosaic system.…”

“…In Stockholm County, we used the central database (VAL) for healthcare utilisation, consultations and diagnoses, the vaccination register (Vaccinera) and for the outcome, the national electronic surveillance system (SmiNet) for the reporting of communicable diseases. Data from VAL, Vaccinera and SmiNet were linked using the same PIN (for details on data sources see [ 1 , 3 , 4 ]). VAL was used for obtaining data on in- and outpatient diagnoses, comorbidities, age and sex as well as the Stockholm Mosaic system.…”

“…Systems for register-based monitoring of vaccine effectiveness (VE) against laboratory-confirmed influenza (LCI) in real time were set up in Stockholm County, Sweden, and in Finland, before the start of the 2016/17 influenza season, using population-based cohort studies [ 1 , 2 ]. In both locations, after an initial moderately high VE of about 50%, a rapid and sharp 20% decline in VE was observed.…”

Immunogenicity of influenza vaccine in elderly people: a systematic review and meta-analysis of randomized controlled trials, and its association with real-world effectiveness

“…Seasonal influenza vaccination is associated with a significant reduction in influenza-specific hospitalizations, especially in elderly people with underlying chronic diseases, 45 and improving the influenza vaccine coverage rates remains a very important goal for this age group. At present, the vaccine coverage for a population of over 65 years old was still below the 75-80% target, 46 even in some highly developed countries or regions.…”

Cohort study design for estimating the effectiveness of seasonal influenza vaccines in real time based on register data: The Finnish example

“…Denmark [22, 23], England [24], the Netherlands [25, 26], Norway [27], and Scotland [28, 29]) or subnational level (e.g. Navarre, Spain [30, 31] and Stockholm, Sweden [6, 32]) monitoring vaccinations and influenza cases in the total population or defined subpopulations including representative samples of the total population. Administrative databases and medical registers are widely recognised tools for signal detection and hypothesis generation [33].…”