MIDAS Online Portal for COVID-19 Modeling Research
Internal Dataset

UID: 84


The MIDAS Online Portal for COVID-19 Modeling Research is a clearinghouse for sharing datasets, published estimates on epidemiological characteristics (both peer-reviewed and non-), and software for dashboard monitoring, data processing, modeling, and visualization related to the 2019 novel coronavirus pandemic (formerly referred to as 2019-nCoV acute respiratory disease). Information in the portal has been selected from reputable scientific sources and from the computational modeling community within MIDAS, the Models of Infectious Disease Agent Study whose coordination center is located at the University of Pittsburgh.

Public-access data collections are shared via the MIDAS Github repository. Peer-reviewed parameter estimates have been compiled separately from non-peer-reviewed parameter estimates, and both are shared via the Github repository. Software is hosted at each creator's own Github repository (or another site) and is not maintained by the MIDAS portal. This is a developing resource and is subject to change. Direct links to all resources are available from the portal linked from this record.

2019 -
Subject of Study
Subject Sex
Access via MIDAS

Public-access data collections, parameter estimates, and community-created software

Access Restrictions
Free to all
Access Instructions
Access data and software via the MIDAS COVID-19 Portal. Datasets and parameters are hosted via the MIDAS Github; software packages are hosted on external contributor sites.
Data Type
Resource Type(s)
Database, Software
Data Catalog Record Updated

Notice and Disclaimer: Please note that the information in this catalog is provided as a courtesy, as is, and with no representations or warranties of any kind. When you contact the responsible individual(s) listed in each record, or, where applicable, access a data repository listed, you will be subject to terms and conditions required by the data custodian/data repository. The University of Pittsburgh does not attempt to judge the scholarly quality of the data referenced and relies on the judgment and research expertise of those who created and/or deposited it.