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

Outbreak and Pandemic Preparedness and Management (1774) Clinical Informatics (1112) Public (e)Health, Digital Epidemiology and Public Health Informatics (830) Surveillance Systems (484) Machine Learning (1639) Infectious Diseases (non-STD/STI) (1638) Use Cases in Human, Animal, and Zoonotic Communicable/Infectious Disease Surveillance (136)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59971, first published .
Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Authors of this article:

Ravikiran Keshavamurthy1, 2 Author Orcid Image ;   Karl T Pazdernik1, 3 Author Orcid Image ;   Colby Ham1 Author Orcid Image ;   Samuel Dixon1 Author Orcid Image ;   Samantha Erwin1 Author Orcid Image ;   Lauren E Charles1, 2 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Ravikiran Keshavamurthy   1, 2 , BVSc, MVSc, PhD ;   Karl T Pazdernik   1, 3 , PhD ;   Colby Ham   1 , BS ;   Samuel Dixon   1 , MS ;   Samantha Erwin   1 , MS, PhD ;   Lauren E Charles   1, 2 , DVM, MS, PhD

1 Artificial Intelligence and Data Analytics Division, Pacific Northwest National Laboratory, Richland, WA, United States

2 Paul G. Allen School for Global Health, Washington State University, Pullman, WA, United States

3 Department of Statistics, North Carolina State University, Raleigh, NC, United States

Corresponding Author:

  • Lauren E Charles, DVM, MS, PhD
  • Artificial Intelligence and Data Analytics Division
  • Pacific Northwest National Laboratory
  • 902 Battelle Boulevard
  • Richland, WA, 99354
  • United States
  • Email: lauren.charles@pnnl.gov