Influenza forecast optimization when using different surveillance data types and geographic scale

Abstract

Advance warning of influenza incidence levels from skillful forecasts could help public health officials and healthcare providers implement more timely preparedness and intervention measures to combat outbreaks. Compared to influenza predictions generated at regional and national levels, those generated at finer scales could offer greater value in determining locally appropriate measures; however, to date, the various influenza surveillance data that are collected by state and county departments of health have not been well utilized in influenza prediction.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 21, 2018
Source ID
10.1111/irv.12594

Entities

People

  • Alexandra Heaney
  • Harold Gil
  • Haruka Morita
  • Jeffrey Shaman
  • Sarah C Kramer

Organizations

  • Columbia University
  • Defense Threat Reduction Agency
  • National Institute of Environmental Health Sciences
  • National Institutes of Health

Tags

Fields of Study

  • Medicine

Readers

  • Computational Modeling and Simulation
  • Infectious Disease/Epidemiology
  • Systems Analysis and Design