Shedding Hub

Curated Datasets

Access 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.

At a Glance

60617 biomarker measurements for 27328 participants from 39 studies. And counting.

Interactive Data Explorer

Explore biomarker shedding data interactively through our dashboard. Visualize time-course patterns, compare across studies, and analyze shedding dynamics.

Why Focus on Shedding Data?

Understanding pathogen shedding dynamics is critical for infectious disease transmission modeling, wastewater-based epidemiology, and public health surveillance. However, shedding data is often scattered across publications, stored in heterogeneous formats, and difficult to access for meta-analysis and model development.

Shedding Hub addresses these challenges by providing a centralized platform with standardized data, statistical modeling resources, and interactive tools. Our platform enables researchers to explore shedding patterns across studies, develop and validate models, and generate insights for evidence-informed public health decision-making.

Our Approach for Data Curation

Shedding Hub provides high-quality, curated pathogen shedding data extracted from published scientific literature. Since May 2024, our team of human biocurators has meticulously extracted biomarker shedding data from peer-reviewed studies, with rigorous quality assurance and quality control processes ensuring data accuracy and consistency.

Beginning in June 2025, we enhanced our curation pipeline by integrating large language models (LLMs) to power the data discovery and extraction process. This AI-assisted approach allows us to scale our efforts significantly while maintaining the high quality standards established by our human curation workflow. All LLM-extracted data undergoes expert review to ensure reliability and completeness.

Get Started

Access and analyze Shedding Hub data in just a few lines of Python code. Watch this quick tutorial to see how easy it is to get started.

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Leadership

Core Team

Yuke (Andrew) Wang

Co-founder

Assistant Research Professor, Rollins School of Public Health, Emory University

Yuke (Andrew) Wang sets the overall direction of the Shedding Hub project and leads the teams to build the AI-powered multi-agent system for data curation.

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Till Hoffmann

Co-founder

Research Associate, Harvard T.H. Chan School of Public Health

Till Hoffmann sets the overall technology vision of the Shedding Hub project and oversees the technical implementation and software engineering.

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Scientific Advisors

Dr. Christine Moe

Eugene J. Gangarosa Professor of Safe Water and Sanitation, Hubert Department of Global Health, Rollins School of Public Health, Emory University

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Dr. Peter Teunis

Visiting Professor, Hubert Department of Global Health, Rollins School of Public Health, Emory University

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Dr. Benjamin Lopman

Professor, Department of Epidemiology, Rollins School of Public Health, Emory University, Director and Co-Principal Investigator, CIDMATH

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Dr. Katia Koelle

Professor, Department of Biology, College of Arts and Sciences, Emory University, Director of Scientific Initiatives and Co-Principal Investigator, CIDMATH

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Contribute Data

Help expand the Shedding Hub database by contributing your pathogen shedding datasets. We welcome data on biomarker shedding dynamics across various pathogens, specimen types, and populations. Our team will work with you to ensure proper data formatting and integration into the platform.

Whether you have data from a single subject or multiple studies, we're here to help. Contributions undergo quality review and are credited appropriately in our database.

Contact Us to Contribute

Funding

The Shedding Hub was made possible by the Insight Net cooperative agreement CDC-RFA-FT-23-0069 from the CDC’s Center for Forecasting and Outbreak Analytics. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention. Support for the Shedding Hub is provided by the Emory Center for Infectious Disease Modeling and Analytics & Training Hub (CIDMATH).