Applying symptom dynamics to accurately predict influenza virus infection: An international multicenter influenza-like illness surveillance study.

ABSTRACT:

Background

Public health organizations have recommended various definitions of influenza-like illnesses under the assumption that the symptoms do not change during influenza virus infection. To explore the relationship between symptoms and influenza over time, we analyzed a dataset from an international multicenter prospective emergency department (ED)-based influenza-like illness cohort study.

Methods

We recruited patients in the US and Taiwan between 2015 and 2020 with: (1) flu-like symptoms (fever and cough, headache, or sore throat), (2) absence of any of the respiratory infection symptoms, or (3) positive laboratory test results for influenza from the current ED visit. We evaluated the association between the symptoms and influenza virus infection on different days of i

SUBMITTER: Li JH 

PROVIDER: S-EPMC9835452 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature