What MIDAS is about

The MIDAS network aims to advance science to improve global preparedness and response against infectious disease threats through research, training, promotion, and service.


MIDAS members use computational, statistical, and mathematical modeling for basic, applied, and translational research on various aspects of infectious disease dynamics, such as disease pathogenesis, pathogen transmission, control interventions, and forecasting. MIDAS research is characterized by:
  • Highest scientific quality and dedication to improving public health

  • Inclusivity, diversity and integrity

  • Open science best practices, including data, model, software, and workflow sharing

  • Applying existing and establishing new modeling methods

  • Creating custom modeling software, often highly specific to research objectives

  • Using observational, real-world data, often not primarily collected for research purposes

  • Studying infectious disease dynamics relevant to human health

  • Studying infectious disease dynamics at all biological scales, from molecularto population-level

  • Global geographical scope

  • Multidisciplinary collaborations, including (but not limited to): epidemiologists, statisticians, clinicians, public health practitioners, climate scientists, demographers, ecologists, mathematicians, geographers, molecular biologists, virologists, microbiologists, and others

  • Collaboration for model development, testing, and application

  • Translating modeling research into software and data resources for the global community

  • Translating research findings into public health policy and action through collaboration with public health stakeholders

  • Commitment to supporting infectious disease modeling research and practice in low resource settings

MIDAS creates educational, training, mentoring and career development opportunities in computational, statistical and mathematical modeling. MIDAS is dedicated to train a broad community of scientists and practitioners including those from underrepresented groups and low-resource settings. MIDAS training activities include:
  • Curriculum development

  • In-person and online workshops and webinars

  • Tutorials

  • Exchanges and internships

  • Field placements and fellowships

  • Conferences targeting specific groups of scientists, practitioners, or students


MIDAS promotes the value of computational, statistical, and mathematical modeling of infectious disease dynamics for global health. Collaboration between infectious disease modelers and practitioners is essential to translate modeling research into public health impact and to ensure modelers address priority questions with their research. MIDAS promotion includes:
  • Physical and virtual promotional material, including the MIDAS website and social media channels
  • Presentation of infectious disease modeling research at global, national, and local meetings of health and related communities
  • Reaching out to students, researchers, and practitioners in a broad range of disciplines to broaden awareness of infectious disease modeling and to widen the range of methods and skills applied against infectious disease threats


MIDAS delivers services to translate computational, statistical and mathematical modeling research into public health policy and action. Departing from MIDAS responsibilities in the past, the current network will not be required to support government agencies in need of modeling expertise. Instead, MIDAS researchers will collaborate with government, and other, agencies to conduct research or to translate research into public health impact, as determined by the scope of individual researchers’ projects and by regulations of individual researchers’ funding agencies. MIDAS services include:
  • Creating datasets, models, software, and workflows that can be used by the broader scientific and practice community
  • Engaging with public health practitioners and other stakeholders to improve the application and translation of research into preparedness and response against infectious disease threats
  • Engaging with the funder community to align funding mechanisms to public health needs
  • Engaging with the data science community to improve the reuse of MIDAS data, models, software, and workflows by others
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