Using wastewater to unlock public health insights
Widespread national wastewater surveillance started in 2020, as part of the pandemic response for COVID-19, making sewer systems a valuable source for public health data. Wastewater surveillance can detect outbreaks before symptoms begin, track trends in infections, and locate hotspots of infection. Every day as more data are collected, researchers advance and expand current techniques and develop new tools to utilize wastewater data.
CIDMATH’s Wastewater Epidemiology team uses wastewater data to advance the science of modeling and forecasting for public health preparedness and response. The team is led by Dr. Katia Koelle and builds upon Dr. Marlene Wolfe’s leadership as a Program Director of WastewaterSCAN, a national wastewater monitoring system that informs public health responses, along with Dr. Yuke Wang’s work on spatial mapping of sewer networks and Dr. Anne Piantadosi’s expertise in sample sequencing.Â
Projects
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Shedding Hub
Led by Dr. Yuke Wang (), the Shedding Hub is an open science initiative dedicated to centralizing biomarker shedding data and models into one easy, publicly accessible resource. Hosted on GitHub, the Shedding Hub extracts, compiles, standardizes, and validates biomarker shedding data from published literature.
To keep pace with the exponential growth of biomedical research, we are deploying an AI-powered multi-agent system that automates literature discovery and data extraction. Currently available datasets span 12 biomarkers including SARS-CoV-2, norovirus, rotavirus, and 12 specimen types, including stool, naso- and oropharyngeal swabs, and saliva.Â
All data and code created by the Shedding Hub team are open access for anyone to use for their own research projects.
Learn More: https://shedding-hub.github.io/Â
Access Data: https://github.com/shedding-hub
Wastewater Sample Sequencing
The research groups of Dr. Anne Piantadosi and Dr. Marlene Wolfe are analyzing banked samples from WastewaterSCAN and the Georgia Department of Public Health. Pathogens of interest include SARS-CoV-2 (COVID-19), Influenza A, Influenza B, and respiratory syncytial virus (RSV). Sequencing provides higher resolution understanding of circulating viruses, including which strains are increasing in frequency. Sequencing can also provide insight into the spatial spread of viral pathogens over time and inform disease modeling and prediction efforts.
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Machine Learning for Forecasting
Researchers are leveraging machine learning techniques and combining wastewater data with other surveillance data streams to improve the ability to generate real-time estimates of disease spread and enhance forecasting methods. More info on our Machine Learning page.
Latest Works
Preprint: A bootstrap particle filter for viral Rt inference and forecasting using wastewater data
Wenfei Fiona Xiao, Yuke Wang, Nikunj Goel, Marlene Wolfe, Katia Koelle
Preprint: Where do We Poop? City-Wide Simulation of Defecation Behavior for Wastewater-Based Epidemiology
Hossein Amiri, Akshay Deverakonda, Yuke Wang, Andreas Zufle
TEAM
Anne Piantadosi, MD/PhD
Assistant Professor, Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Co-Investigator, CIDMATH
Contact
Publication Link
Emory Profile
Marlene Wolfe, PhD
Assistant Professor, Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Co-Investigator, CIDMATH
Katia Koelle, PhD
Director of Scientific Initiatives and Co-Principal Investigator
Professor, Department of Biology, Emory University College of Arts and Sciences
Max Lau, PhD
Assistant Professor, Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Co-Investigator, CIDMATH
Yuke “Andrew” Wang, PhD
Research Assistant Professor, Hubert Department of Global Health, Emory University Rollins School of Public Health, Co-Investigator, CIDMATH
Personal Website