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COVID-19 Scenario Modeling Hub - Research

This repository follows the guidelines and standards outlined by the hubverse, which provides a set of data formats and open source tools for modeling hubs.

The Consortium of Infectious Disease Modeling Hubs. The hubverse: open tools for collaborative modeling. GitHub release v2.0.0, 14 Jul 2023. URL: https://github.com/Infectious-Disease-Modeling-Hubs

How to participate

The Scenario Modeling Hub is open to any team willing to provide projections at the right temporal and spatial scales, with minimal gatekeeping. We only require that participating teams share point estimates and uncertainty bounds, along with a short model description and answers to a list of key questions about design. A major output of the projection hub is ensemble estimates of epidemic outcomes (e.g., infection, hospitalizations, and deaths), for different time points, intervention scenarios, and US jurisdictions.

Those interested to participate, please read the README file and email us at [email protected]

Target Data

The repository contains a target-data folder relevant to the modeling efforts. It contains COVID-19 case and death time series by race/ethnicity.

For more information, please consult the associated README file

Data license and reuse

All source code that is specific to the overall project is available under an open-source MIT license. We note that this license does NOT cover model code from the various teams, model scenario data (available under specified licenses as described above) and auxiliary data.

Computational power

Those teams interested in accessing additional computational power should contact Katriona Shea at [email protected]. Additional resources might be available from the ]MIDAS Coordination Center](https://midasnetwork.us/) - please contact [email protected] for information.

The Scenario Modeling Hub Coordination Team

  • Shaun Truelove, Johns Hopkins University
  • Cécile Viboud, NIH Fogarty
  • Justin Lessler, University of North Carolina
  • Sara Loo, Johns Hopkins University
  • Lucie Contamin, University of Pittsburgh
  • Emily Howerton, Penn State University
  • Claire Smith, Johns Hopkins University
  • Harry Hochheiser, University of Pittsburgh
  • Katriona Shea, Penn State University
  • Michael Runge, USGS
  • Erica Carcelen, John Hopkins University
  • Sung-mok Jung, University of North Carolina
  • Jessi Espino, University of Pittsburgh
  • John Levander, University of Pittsburgh
  • Samantha Bents, NIH Fogarty
  • Katie Yan, Penn State University