Machine Learning-Driven COVID-19 Hospitalization Forecasting: From Theory to Practice in a Major Northeastern Academic Medical Center.

Journal: Open forum infectious diseases
Published Date: Jun 12, 2025

Abstract

BACKGROUND: Predicting seasonal and emerging waves of respiratory viruses is crucial for effective public health responses. Despite significant efforts in developing coronavirus disease 2019 (COVID-19) forecast models, there remains a need for improvement in model performances.

Authors

  • Alexander Y Tulchinsky
    One Health Trust, Washington, District of Columbia, USA.
  • Xihan Zhao
    Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
  • Nodar Kipshidze
    One Health Trust, Washington, District of Columbia, USA.
  • Jeremiah Hinson
    Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Fardad Haghpanah
    One Health Trust, Washington, District of Columbia, USA.
  • Eili Y Klein
    Center for Disease Dynamics, Economics & Policy, Silver Spring, Maryland, United States.

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