SHEDDING HUBÂ Â Â |Â Â Â VAXIMPACTMAPÂ Â Â |Â Â Â DATA HUBÂ Â Â Â |Â Â Â PUBLICLY AVAILABLE DATA
Curated Datasets
Standardized biomarker shedding data from published studies, spanning multiple pathogens and specimen types
Statistical Models
Bayesian workflows and tutorials for modeling shedding dynamics, including time-course analysis and decay models
Python Tools
Programmatic access to data and analysis tools through our open-source Python package and interactive visualizations
Fewer children are receiving recommended vaccines, resulting in additional cases of vaccine-preventable diseases. Developed by CIDMATH researchers, VaxImpactMap is an interactive tool that can be toggled to project the costs of increased disease burden under various scenarios.
For your customized parameters, VaxImpactMap projects the following outcomes at the state and national levels:
- Disease cases
- Hospitalizations
- Deaths
- Workdays lost
- Productivity costs
- Healthcare costs
The CIDMATH Data Hub is a comprehensive platform designed to centralize the collection, processing, storage, analysis, modeling, visualization, and sharing of data from public, commercial, partner, and CIDMATH sources. This hub supports and enhances CIDMATH and partner projects and operations. Currently, the CIDMATH Data Hub provides CIDMATH researchers and partners with access to centralized data from Merative MarketScan and Epic Cosmos.
Click here for the full Data Hub poster from the 2026 Insight Net Forum
Data Hub Team
Connor Van Meter, MSPH
Data Scientist, Department of Epidemiology, Emory University Rollins School of Public Health, CIDMATH
Contact
Publication Link
Machi Shiiba, MPH
Public Health Program Associate, Department of Epidemiology, Emory University Rollins School of Public Health, CIDMATH
nomatch R package for matching alternative that more efficiently estimates effectiveness of interventions using observational data
Check back for more!
As more resources are developed and published they will be added to this page. Stay tuned!