Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study.

ABSTRACT:

Background

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study.

Objective

This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset.

Methods

This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting b

SUBMITTER: Daughton AR 

PROVIDER: S-EPMC7210500 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature