Abstract
Estimation of the national-level incidence of seasonal influenza is notoriously challenging. Surveillance of influenza-like illness is carried out in many countries using a variety of data sources, and several methods have been developed to estimate influenza incidence. Our aim was to obtain maximally informed estimates of the proportion of influenza-like illness that is true influenza using all available data. We combined data on weekly general practice sentinel surveillance consultation rates for influenza-like illness, virologic testing of sampled patients with influenza-like illness, and positive laboratory tests for influenza and other pathogens, applying Bayesian evidence synthesis to estimate the positive predictive value (PPV) of influenza-like illness as a test for influenza virus infection. We estimated the weekly number of influenza-like illness consultations attributable to influenza for nine influenza seasons, and for four age groups. The estimated PPV for influenza in influenza-like illness patients was highest in the weeks surrounding seasonal peaks in influenza-like illness rates, dropping to near zero in between-peak periods. Overall, 14.1% (95% credible interval [CrI]: 13.5%, 14.8%) of influenza-like illness consultations were attributed to influenza infection; the estimated PPV was 50% (95% CrI: 48%, 53%) for the peak weeks and 5.8% during the summer periods. The model quantifies the correspondence between influenza-like illness consultations and influenza at a weekly granularity. Even during peak periods, a substantial proportion of influenza-like illness-61%-was not attributed to influenza. The much lower proportion of influenza outside the peak periods reflects the greater circulation of other respiratory pathogens relative to influenza.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.