Coughing, sneezing, and aching online: Twitter and the volume of influenza-like illness in a pediatric hospital.

ABSTRACT: This study investigates the relation of the incidence of georeferenced tweets related to respiratory illness to the incidence of influenza-like illness (ILI) in the emergency department (ED) and urgent care clinics (UCCs) of a large pediatric hospital. We collected (1) tweets in English originating in our hospital's primary service area between 11/1/2014 and 5/1/2015 and containing one or more specific terms related to respiratory illness and (2) the daily number of patients presenting to our hospital's EDs and UCCs with ILI, as captured by ICD-9 codes. A Support Vector Machine classifier was applied to the set of tweets to remove those unlikely to be related to ILI. Time series of the pooled set of remaining tweets involving any term, of tweets involving individual terms, and of the ICD-9

SUBMITTER: Hartley DM 

PROVIDER: S-EPMC5533314 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature