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Drs. Kerr and Zheng receive funding from National Institutes of Health
Jelani Kerr, PhD, MSPH, Associate Professor in the Department of Health Promotion and Behavioral Sciences, is the recipient of a $643,160 grant from the National Institutes of Health (NIH). His project will examine HIV-related stigma and testing among African American young adults who have a history of incarceration. The purpose of this project is to understand relationships between various aspects of HIV-related stigma and HIV testing.
Despite declining HIV rates nationally, African American communities continue to experience high HIV burden and account for the largest share of HIV-related deaths in the United States. African American youth with a history of incarceration are at heightened HIV risk. Early detection among this group is critical for linkage to prevention and care services, improving survival prospects, and reducing racial disparities in HIV. Despite the benefits of testing, HIV-related stigma remains a significant barrier to timely HIV diagnosis.
Dr. Kerr said, “The results of this study will be used to help develop interventions to improve HIV programming and testing for formerly incarcerated African American youth.”
Qi Zheng, PhD, Assistant Professor in the Department of Bioinformatics and Biostatistics, has received a $150,000 award from the National Institutes of Health (NIH) for his research project "Functional Censored Quantile Regression for Investigating Heterogeneous Effects in Survival Data.” For this two-year award, Dr. Zheng will develop functional censored quantile regression methods and statistical software to explore the effects of functional biomarkers on censored survival time. This project will allow researchers to more efficiently and thoroughly evaluate the functional biomarkers for prognosis of disease.
Zheng also received a $150,000 award from the National Science Foundation (NSF) for his collaborative research project "Quantile-based Modeling for Large-Scale Heterogeneous Data." Both grants use quantile regression as a tool to investigate the heterogeneous covariates-response association in different types of data. The NSF focus is on the inference part in high dimensional survival data while the NIH investigates the functional data.