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MIDAS

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 mmods@midasnetwork.us.

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.

For questions or ideas regarding COVID-19 modeling collaborations, contact questions@midasnetwork.us.

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 (jtowns@ncsa.illinois.edu).

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

Collaborations:

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 questions@midasnetwork.us.

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 questions@midasnetwork.us 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 (caitlin.rivers@gmail.com). 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 questions@midasnetwork.us.

MIDAS Members Working on COVID-19

Yao_Li
Yao Li

Doctoral Candidate
University of Maryland