Estimating influenza incidence using search query deceptiveness and generalized ridge regression.

ABSTRACT: Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response. The current state of the art is to gather this knowledge using in-person patient contact. While accurate, this is time-consuming and expensive. This has motivated inquiry into new approaches using internet activity traces, based on the theory that lay observations of health status lead to informative features in internet data. These approaches risk being deceived by activity traces having a coincidental, rather than informative, relationship to disease incidence; to our knowledge, this risk has not yet been quantitatively explored. We evaluated both simulated and re

SUBMITTER: Priedhorsky R 

PROVIDER: S-EPMC6771994 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature