Close

MIDAS — Models of Infectious Disease Agent Study

MIDAS

MODELS OF INFECTIOUS DISEASE AGENT STUDY​

MIDAS is a global network of scientists and practitioners who develop and use computational, statistical and mathematical models to improve the understanding of infectious disease dynamics. Through education, research, service, and sharing of ideas, the MIDAS network aims to advance science to improve global preparedness and response.

MIDAS
Models of Infectious Disease Agent Study (MIDAS) is a global network of scientists and practitioners using computational, statistical, and mathematical models to understand infectious disease dynamics — from pathogenesis and transmission to control strategies and forecasting. Through collaboration and open science, MIDAS advances global preparedness and response.
Reproducibility and Reusability
Guidelines, standards, and tools to help the infectious disease modeling community achieve greater reproducibility and reusability through FAIR data practices.
Browse Reproducibility & Reusability

Events

Head shot of Omar Ureña
Person typing on a laptop displaying an online form

Don't forget to submit by 08/14
Free 3-day workshop at @LSHTM : Modeling Epidemics with Julia 🧬

16-18 Sept 2026

Learn to build epidemic models in Julia — from SIR/ODEs to stochastic processes & real-data observation models.

Submit EOI by Aug 14:

LinkedIn

This link will take you to a page that’s not on LinkedIn

lnkd.in

📢 The #AfricaHealthCollaborative, with the @MastercardFdn is inviting Expressions of Interest for its 2026 Research Fund.

🔬 Open to Early Career Researchers at AHC member institutions.

📅 Deadline: 15 Aug

🔗 Learn more: https://shorturl.at/KR34K

The Duke Multiscale Immune Systems Modeling (MISM) Center of Excellence is accepting applications for its inaugural 1-year Scholars Program for early-stage investigators conducting research on infectious and immune-mediated diseases.
https://redcap.duke.edu/redcap/surveys/

Datasets, tools, and resources for infectious disease modeling.

MIDAS Catalog

Searchable collection of curated datasets and software resources for infectious disease modeling, filterable by disease, topic, location, and time period.

The MIDAS Catalog is the community’s centralized index of resources for infectious disease modeling. Through a single searchable interface, researchers can browse and access datasets, software, and analytical methods used across the field. Content comes from sources including the MIDAS Curated Archive of Global Public Health Data and Project Tycho — covering disease surveillance data, modeling software, and analytical tools. Faceted search supports filtering by disease, topic, geographic location, time period, and more — making it straightforward to find resources matching specific research needs. By bringing these resources together in one place, the catalog supports findable, accessible, interoperable, and reusable (FAIR) data practices across the community.

Screenshot of the MIDAS Catalog search interface showing filter panels for diseases, location, and topic alongside a results table listing digital objects with descriptions.

Data Visualizations

Interactive tools for exploring MIDAS network research, collaborations, and publication trends.

Interactive search interface for exploring the MIDAS network. Find researchers by topic, view collaboration networks across papers and grants, and discover the breadth of research across the field.

Interactive visualization showing how research themes across MIDAS publications have evolved since 2013. Themes flow as ribbons, with band thickness showing each theme’s prevalence over time.

Data Resources

Public health datasets curated, standardized, or maintained by the MIDAS community and partners.

Worldwide archive of official public health data including case counts, deaths, hospitalizations, demographics, and vaccinations from government sources at country and sub-national levels.

Standardized public health data including case counts for 78 conditions across the US and dengue data for 100 countries, formatted to meet FAIR guidelines.

Community effort producing scenario projections to guide pandemic and epidemic response, designed with decision makers.

Reproducibility & Sharing

Guidelines, standards, and tools to help the infectious disease modeling community achieve greater reproducibility and reusability through FAIR data practices.

Community best practices, data models, and terminologies for integrating and comparing datasets and analytic methods.

Formal ontology for describing datasets and software in the MIDAS Catalog, covering biological scale, artifact type, and modeling topics.

Recommendations for describing and sharing datasets and code with clear metadata to encourage reuse.

The people, research, and projects of the MIDAS network.

1,200+

MIDAS members

MIDAS members from academia, industry, government, and non-governmental agencies. Search the directory by name, research topic, pathogen or disease, or country of work.

Latest Projects

Learn more about the MIDAS network.

MIDAS is a global network of scientists and practitioners who develop and use computational, statistical, and mathematical models to improve the understanding of infectious disease dynamics. The network supports open science practices and aims to advance global preparedness for, and response against, infectious disease threats.

The MIDAS Coordination Center supports the network through annual meetings, training and outreach, data services, and member communications. The MCC connects researchers, students, and public health practitioners.

MIDAS membership is open to any infectious disease scientist, practitioner, or student. Join a collaborative, multidisciplinary community defined by broad inclusivity — free of charge.

A subnetwork connecting students and post-docs across MIDAS. Build professional relationships, foster collaborations, share research, and access educational resources.

MIDAS creates educational, training, mentoring, and career development opportunities in computational, statistical, and mathematical modeling — with a focus on training underrepresented groups and low-resource settings.

Reproducibility and Reusability

Share your work using best practices

Reproducibility and Reusability best practices is important to making your work impactful. By ensuring that your research can be replicated and built upon, you contribute to the integrity and advancement of the field. These practices not only foster trust and collaboration but also empower others to leverage your work for new breakthroughs. We recommend that MIDAS members adhere to these principles and provide reference documentation in this section.

Reproducibility and Reusability are considered vital aspects of modern science. Achieving these goals requires a variety of measures, including community best practices, data models, and terminologies, designed to provide a common basis for integrating and comparing datasets and analytic methods.

 

View the guidelines.

As part of the MIDAS Coordination Center’s efforts to bring increased reproducibility and FAIR (Findable, Accessible, Reusable, and Interoperable)1 data principles to infectious disease modeling research, we have developed this series of recommendations for sharing of relevant software and data artifacts.

View the recommendations.

All research proposals submitted to the NIH are now subject to the 2023 NIH Data Management and Sharing policy.  The policy encourages data sharing and requires the submission of a Data Management and Sharing Plan.  NIH applicants must have a firm understanding of the new policy.

MIDAS Member Helenmary Sheridan prepared a webinar explaining the new policy and makes recommendations for the MIDAS network.

View the webinar.

The MIDAS Network Visualization is an interactive view of collaborators within MIDAS.  In the visualization, collaborators are assigned to one of five distinct research clusters and linked to one another in a force directed graph.

 

MIDAS members are assigned to a research cluster by a Non-negative Matrix Factorization (NMF) algorithm which classifies members based on their published works.  Specifically, the visualization uses the abstract and MeSH keywords associated with the publication in the PubMed database.

 

Notable features:

    • Search for a member by name to find their location in the graph.
    • View the details of a member, including their photo, institution, social media links, collaborators, and papers (this information is shown when a user clicks on a node).
    • Show/hide research clusters.
    • Link collaborators by either paper co-authorship, or grant co-membership.

 

Please explore the visualization and send any comments/bugs/suggestions to [email protected].  

 

Visit the MIDAS Network Visualization.

MIDAS membership is open to any infectious disease scientist, practitioner, or student who supports the mission and vision of the network. MIDAS is defined by broad inclusivity and diversity of its members, fostering collaboration to advance the science and application of infectious disease modeling. MIDAS members enjoy many advantages of being part of the network, free of charge.

MIDAS at a Glance

Our Vision and Mission

MIDAS is a global network of scientists and practitioners who develop and use computational, statistical and mathematical models to improve the understanding of infectious disease dynamics.

Membership

MIDAS network membership is open to any infectious disease scientist, practitioner, or student who supports our mission. The MIDAS network is defined by its broad member inclusivity.

Coodination Center

MIDAS creates educational, training, mentoring and career development opportunities in computational and statistical modeling, and is dedicated to train a broad community of scientists and practitioners.

Training

MIDAS creates educational, training, mentoring and career development opportunities in computational and statistical modeling, and is dedicated to train a broad community of scientists and practitioners.

Computing

HPC Services are funded by the NIH National Institute of General Medical Sciences (NIGMS) and are free of charge for MIDAS members from non-commercial organizations. 

Students

MIDAS enables students to create professional relationships across the network, foster future collaborations, share educational resources, and provide a relaxed environment to share research and progress.

MIDAS Member Papers

Infectious Disease Papers

Prevalence of hypertension and cross-sectional associations between household air pollution exposure and blood pressure among children in rural Rwanda.

Environmental research, health : ERH
Sewor C, Tanner K, Cleveland V, Young BN, L’Orange C, Witinok-Huber R, Balmes J, Kalisa E, Zurba L, Ntakirutimana T, P Keller K, Chang HH, Volckens J, Clark ML
2026-08-06 Continue Reading Prevalence of hypertension and cross-sectional associations between household air pollution exposure and blood pressure among children in rural Rwanda.

MIDAS Member Projects