Introduction

This dashboard is part of the epiENGAGE project, a CDC-funded collaboration involving over 20 research labs and public health departments dedicated to developing science-based tools and training programs that help local agencies detect, forecast, and respond to outbreaks more effectively.

This particular dashboard is designed for the Flu MetroCast hub, a national platform enabling collaborative, local-level forecasting of influenza-related emergency department visits and hospital admissions.

View The Latest Forecasts

Current Metro Areas

• New York City
  • Target: Percent of ED visit due to ILI (Influenza-like Illness)
  • Data source : New York City Department of Health and Mental Hygiene
  • Target areas: NYC (citywide)

• Local Flu Activity Across U.S. Metro Areas
  • Target: Percentage of ED visits due to flu
  • Data Source : CDC’s Emergency Department Visits for Viral Respiratory Illness
  • Target areas: 51 metropolitan Health Service Areas (HSAs) across Colorado, Georgia, Indiana, Maine, Maryland, Massachusetts, Minnesota, South Carolina, Texas, Utah, and Virginia.
    A full list of included HSAs is available here.
  • Note: These HSAs include a central city and its surrounding counties, and we include all HSAs with populations of at least 250,000 (with the exception of Massachusetts).

• North Carolina
  • Target: Percentage of ED visits due to flu
  • Data Source: North Carolina Division of Public Health’s (NC DPH) statewide syndromic surveillance system
  • Target areas: 7 geographic regions comprised of adjacent counties

Models Included

• epiENGAGE-GBQR : A machine learning method that combines gradient boosting and quantile regression to predict conditional quantiles
• epiENGAGE-INFLAenza : A spatial time-series model that uses the R-INLA package for estimating forecast posterior distributions.
• epiENGAGE-Copycat : A pattern matching model that matches growth rate trends to historic growth rate curves.
• Epiforecasts-dyngam : A Bayesian hierarchical GAM with a univariate AR(1) process
• epiENGAGE-baseline : simple time series model as a reference model
• epiENGAGE-ensemble_mean : An equally weighted mean ensemble that takes the mean at each quantile level of all eligible forecasts
• epiENGAGE-log_norm : Linear pool (a.k.a. distributional mixture) ensemble of quantile forecast submissions.

Information for Modelers

Anyone interested in submitting a model should review the guidelines for the 2025/2026 season on the Flu MetroCast Hub repository.

The latest-data.csv file in the Flu MetroCast Hub target data directory provides data that modelers can use to fit a model. Latest-data is specially formatted target data that includes the most up-to-date values for all dates for which target data is available, not just dates corresponding to the subset of target_end_dates for which the Hub provides forecasts.

Latest-data is the best source for modelers to get a single version of the target data with only the most recent observations, and including all historical data available from past seasons.