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MIDAS Coordination Center
University of Pittsburgh
A737 Public Health
130 DeSoto Street
Pittsburgh PA 15261
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Mission
What MIDAS is about
Research
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
Promotion
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
Service
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