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

Surveillance Systems (519) Influenza and Influenza-Like-Illness (ILI) Surveillance (238) Infectious Diseases (non-STD/STI) (1738) Outbreak and Pandemic Preparedness and Management (1839)

Published on in Vol 10 (2024)

This is a member publication of University of Pittsburgh

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57349, first published .
A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation

Authors of this article:

John M Aronis1 Author Orcid Image ;   Ye Ye1 Author Orcid Image ;   Jessi Espino1 Author Orcid Image ;   Harry Hochheiser1 Author Orcid Image ;   Marian G Michaels2 Author Orcid Image ;   Gregory F Cooper1 Author Orcid Image
Article Authors Cited by (1) Tweetations (1) Metrics

Journals

  1. Sahin O, Phung H, Standke A, Rajmokan M, Raulli A, York A, Lee P. Integrating Surveillance and Stakeholder Insights to Predict Influenza Epidemics: A Bayesian Network Study in Queensland, Australia. International Journal of Environmental Research and Public Health 2026;23(1):69 View