Online Portal for COVID-19 Modeling Research

Information and Resources for COVID-19 Modeling Research

MIDAS Catalog

The MIDAS Coordinating Center has curated a collection of more than 300 digital resources relevant to COVID modeling.  The Data Catalog includes datasets, software, dashboards, catalogs, and repositories described with rich metadata.  Contents of the data catalog will also be made available via an application programming interface in the near future.

COVID-19 Scenario Modeling Hub (SMH)

This platform, coordinated by a large team of researchers, aims to build on the experiences of MMODS and the COVID-19 Forecasting Hub and provide a hub to bring together more than 10 COVID-19 models to produce longer-term, 6-month scenario projections of SARS-CoV-2 and COVID-19 in the US. These scenarios are designed to address the current areas of uncertainty and decision points as the pandemic continues to evolve in the U.S. The goal of long-term projections is to compare outbreak trajectories under different scenarios of what “could” happen, as opposed to offering a specific, unconditional estimate of what “will” happen.

This project, coordinated by Dr. Katriona Shea at Penn State University aims to combine COVID-19 modeling results from different groups into one decision-analytic framework to support decision-making to mitigate the impact of the pandemic.


Update (7/1/2020):  This project is now underway and is currently closed to new participants. If you would like to be contacted with information regarding future elicitations, please email the project coordinators at

This platform, coordinated by Dr. Nick Reich at the University of Massachusetts at Amherst brings together over 20 COVID-19 forecasting models into one comparative framework that displays the expected COVID-19 trajectory 4 weeks out and compares forecasts to data retrospectively.

Modeling Strategies for Reopening Universities

This collaboration is exploring modeling approaches to help Universities determine strategies for reopening during the fall 2020 term. The group is being coordinated by Drs. Kate Gabrowski and Justin Lessler at Johns Hopkins University. The first group meeting took place on Wed July 1st and follow-up is currently being determined and could include additional meetings, a joint list of modeling resources for opening strategies, a Slack channel, or other options. If you are interested in participating, please register here and complete the initial group survey here

For questions or ideas regarding COVID-19 modeling collaborations, contact

COVID-19 General Announcements

High Performance Computing Resources available for COVID-19 modeling research

The COVID-19 High Performance Computing (HPC) Consortium is providing free access to an unprecedented amount of HPC resources in support of COVID-19 research. The Consortium is a private-public effort bringing together partners from the federal government, industry, and academia. Interested researchers may submit proposals to the Consortium via an online portal, maintained by the Extreme Science and Engineering Discovery Environment (XSEDE). XSEDE is an NSF-funded virtual organization that integrates and coordinates the sharing of advanced digital services.  The Consortium steering group will  review proposals for matching with computing resources from one of the partner institutions. Infectious disease modelers working in collaboration with US CDC can also contact the Principal Investigator of XSEDE, John Towns at the University of Illinois directly (

COVID-19 GitHub Repository

The MIDAS Network has created a GitHub Repository for COVID-19 modeling research. The repository includes data and information, listed on this website, in computational form, mostly structured CSV files and rich metadata.

How to Participate

Mailing List:

Any infectious disease scientist, practitioner, or student interested in COVID-19 modeling research can join this mailing list. Subscription requests will be reviewed and approved by a moderator.


Visit the COVID-19 Modeling Collaborations section of this page to view collaborations that are relevant to the MIDAS Network.  For questions or ideas regarding COVID-19 modeling collaborations, contact

Contribute to the MIDAS COVID-19 Repository:

We encourage community members to contribute resources to the repository and thus support the overall COVID-19 research effort. Contact for any questions or ideas for improvements, or to send/request any material to be included.


A Slack workspace is being maintained by Caitlin Rivers ( The workspace includes various channels: general, importation, news, random, publications, forecasting, data, and announcements.

Review COVID-19 Preprints on Outbreak Science Rapid PREreview Platform:

This rapid pre-review platform enables the community to give feedback on pre-prints coming out with modeling and other analyses of the COVID-19 and other outbreaks. Visit the platform here.

For questions or concerns, contact the MIDAS Coordination Center via

MIDAS Members Working on COVID-19

Dan Han

Assistant Professor
University of Louisville

Darcy Rao

Acting Assistant Professor
University of Washington

Donald Burke

Distinguished University Professor of Health Science and Policy
University of Pittsburgh

Evan Ray

Research Assistant Professor
Mount Holyoke College

Gloria Kang

Postdoctoral Fellow
Centers for Disease Control and Prevention

Jin Wang

Professor and UNUM Chair of Excellence
University of Tennessee Chattanooga

John Drake

Distinguished Research Professor
University of Georgia

Kekun Wu

Assistant Professor
Zhongnan University of Economics and Law

Kim Wong

Research Assistant Professor
University of Pittsburgh

Marc Choisy

Senior Research Scientist
French National Institute for Sustainable Development

Mark Jit

Professor of Vaccine Epidemiology
London School of Hygiene & Tropical Medicine

Steven Riley

Professor of Infectious Disease Dynamics
Imperial College London

John Edmunds

Professor of Infectious Disease Modelling
London School of Hygiene & Tropical Medicine

Wei Luo

Research Associate
Boston Children’s Hospital

Yao Li

Doctoral Candidate
University of Maryland