This paper is in the following e-collection/theme issue:

Public Health Surveillance Practice (162) Validity, Reliability, and Bias (89)

Published on in Vol 10, No 1 (2018):

Evaluation of approaches that adjust for biases in participatory surveillance systems

Evaluation of approaches that adjust for biases in participatory surveillance systems

Evaluation of approaches that adjust for biases in participatory surveillance systems

Authors of this article:

Kristin Baltrusaitis1 ;   Kathleen Noddin2 ;   Colleen Nguyen2 ;   Adam Crawley3 ;   John S. Brownstein4 ;   Laura F. White1
The full text of this article is available as a PDF download by clicking here.
Article Authors Cited by (2) Tweetations Metrics

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  1. Morris M, Hayes P, Cox I, Lampos V, Lofgren E. Neural network models for influenza forecasting with associated uncertainty using Web search activity trends. PLOS Computational Biology 2023;19(8):e1011392 View
  2. Harvey E, Trent J, Mackenzie F, Turnbull S, O’Neale D. Calculating incidence of Influenza-like and COVID-like symptoms from Flutracking participatory survey data. MethodsX 2022;9:101820 View