Data dashboard to support meta-analyses on influenza vaccine effectiveness across regions, influenza seasons and outcomes

Evaluating influenza vaccine effectiveness is essential for identifying gaps in influenza prevention strategies. We developed an open-source dashboard-ready dataset with vaccine effectiveness data from 45 index countries in the inter-pandemic period between 2011 and 2019, based on a systematic literature review. We show how it can be used to estimate pooled vaccine effectiveness using fixed and/or random-effects meta-analyses. The full dataset contains 9,632 vaccine effectiveness estimates from 239 peer-reviewed studies. Individual data points are available on vaccine valency, type, and dose. The meta-analyses dataset can be subset by model, geographic region, influenza season, measure (adjusted, unadjusted), outcome (lab-confirmed infection, influenza-like illness, influenza-associated complications) age groups, comorbidity- or age-based risk groups, influenza type, and medical attendance type. As an example, we used a subset (with data from 2,128,431 participants) of this data to calculate the fixed effects pooled vaccine effectiveness for laboratory-confirmed influenza, which was 39.4% (for all). Vaccine effectiveness was lowest in the elderly (65+: 27.4%) compared to the general population; against A/H3N2 (23.9%) compared to A/H1N1 (49.0%) or B (46.7%); and in 2014, when there was mismatch between the circulating A/H3N2 strain and vaccine antigen. Our open-source datasets enable policy makers and researchers to assess vaccine effectiveness in different regions and contexts. Given the notably low vaccine effectiveness for the elderly, complementary strategies to further reduce the yearly worldwide burden of influenza infections are needed.