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.
Not sure where to start with the MIDAS Catalog? Try one of these popular entries:
  • COVID-19 Data Lake
    • The Microsoft Azure COVID-19 Data Lake contains COVID-19 related datasets from various sources. The datasets include multiple topics: testing and patient outcome tracking data, social distancing policy, hospital capacity, mobility, and so on.
  • COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University
    • This is the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). It includes the daily number of confirmed cases, recovered cases, deaths, and daily reports related to COVID-19 across the world since 2020-01-21. .

  • COVID-19 Mobility Report
    • The community mobility reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential areas at national.
  • Delphi’s Epidata API
    • An open API for real-time access to epidemiological surveillance data maintained by the Carnegie Mellon University Delphi research group. The Epidata API contains: COVIDcast API that provides daily updates about COVID-19 activity across the United States, and data about other epidemics including influenza, dengue, norovirus.
  • KAP COVID Vaccine Acceptance Around the World 
    • The dashboard includes data on vaccine acceptance from 67 countries worldwide including how acceptance has changed over time and who has the greatest potential to influence those who are vaccine hesitant. The visualization show data by country, by WHO region, and by survey wave. The data are available on request.
  • NCATS National COVID Cohort Collaborative (N3C) Data Enclave
    • The N3C Data Enclave is a secure platform through which harmonized clinical data provided by our contributing members are stored. The Enclave includes demographic and clinical characteristics of patients who have been tested for or diagnosed with COVID-19, and further information about the strategies and outcomes of treatments for those suspected or confirmed to have the virus.

COVID-19 Modeling Collaborations

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, combines COVID-19 modeling results from multiple groups into a formal decision analytic framework to support decision-making to mitigate the impact of the pandemic.


Update (12/1/2020):  This case study project is complete, and MMODS now contributes to the COVID-19 Scenario Modeling Hub. Please email the project coordinators at for more information.

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

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 (

How to Participate


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

Omayra Ortega

Assistant Professor of Mathematics & Statistics
Sonoma State University

Paul Rathouz
Paul Rathouz

Professor, and Director of Biomedical Data Science Hub
University of Texas at Austin

Phoebe Lu

Research Analyst
University of California San Francisco