Influenza vaccine effectiveness in the portuguese elderly during 2016-17 season

Every year the influenza vaccine is reformulated,so estimating the influenza vaccine effectiveness (IVE) every season in an early stage is of major importance to support public health decisions. Since 2008-09, Portugal and other European countries implemented a common protocol using the test negative design (TND) at Primary Care level (PC) and since 2015-16 at Hospital Level (HL), framed by the IMOVE+ multicentric study. We aimed to estimate IVE against confirmed medically attended influenza and against confirmed hospitalized influenza in the Portuguese population aged 65 years or more, during the 2016-17 season. We used the TND in both PC and HL. For the PC setting, medically attended influenza positive patients were compared to influenza negative patients, whereas at HL laboratory confirmed influenza positive SARI patients were compared to negative ones. Epidemiological data was collected via questionnaire and the influenza (type/subtype) diagnosis in nasopharyngeal swabs by RT-PCR. The set of collected variables included sociodemographics, chronic conditions, health behaviour, severity, previous influenza and pneumococcal vaccination, functional status, health seeking behaviour and belonging to target group for vaccination. IVE was estimated as 1 – OR of being vaccinated in cases vs controls, adjusted for age, having 2 or more underlying conditions and time trough non-conditional logistic regression. The adjusted IVE was 11% in the Primary Care setting and 49% in Hospital Level, which indicates a low protection of the seasonal 2016/17 vaccine in the elderly population. Even though the small sample size should be considered in the interpretation of results, it should be noted that the IVE estimates are according to results from IMOVE+ study group and other international estimates. A suboptimal IVE against influenza A(H3N2) continues to be observed as in previous seasons.The IMOVE+ project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 634446.N/