Jing Huang, PhD
Assistant Professor of Biostatistics
Dr. Huang’s research focuses on methodology development to understand the dynamics of disease activities and inform health management using multivariate longitudinal health data. She is currently the PI of a R01 project for characterizing disease trajectory and an MPI of a Patient-Centered Outcomes Research Institute (PCORI) funded project for data integration from different institutions. Dr. Huang works in several exciting research areas, including risk prediction of adverse events in congenital heart disease patients using registry, hospital and claims data, dynamic intervention-based on mobile health data, knowledge discovery using electronic health records data, pharmacovigilance using safety reports from the Food Drug Administration and Centers for Disease Control and Prevention funded post-market surveillance systems, and evidence generation in pediatric distributed research networks.
Dr. Huang has been leading the statistical modeling of infectious disease transmission (COVID-Lab: Mapping COVID-19 In Your Community) at the PolicyLab in CHOP since the start of the COVID-19 pandemic. This group is the first in the United States to model county-level COVID-19 transmission levels across the entire country. It has been and continues to track coronavirus transmission, hospitalization, and test positivity rates across all U.S. counties, and projects weekly incidence rates per population and for more than 800 counties. This study has received national attention and has been used by the White House Coronavirus Task Force to inform their state-level guidance during the first year of the pandemic. The models also informed PolicyLab Director’s engagement with the Governor’s crisis team in Pennsylvania and with local and county officials throughout the Commonwealth. These projections were able to detect the transmission trends and identify surges earlier than most other models, including predicting the massive June 2020 surge in Houston, Texas, and the somewhat unexpected 2021 summer surges in many other southern U.S. locations.
Content Area Specialties
health policy, inflammatory bowel disease, pediatrics, pharmacoepidemiology, psychology, renal disorders
Methods for analysis of multivariate longitudinal health data, functional data analysis, predictive modeling