Paul Zivich, PhD

About

Paul Zivich is an assistant professor in the Department of Epidemiology at University of North Carolina at Chapel Hill. His interests are in causal inference with potential outcomes, with a focus on HIV prevention and treatment. Dr. Zivich also focuses on computational aspects of epidemiology. His work has ranged from assessing the performance of estimators through simulation studies to free and open source software (FOSS) to collection of contact network data with electronic sensors to machine learning to application of causal inference in the context of infectious disease and social epidemiology.

Research Activities

- Causal inference

- Machine learning

- Infectious disease epidemiology

Key Publications

Machine learning for causal inference: on the use of cross-fit estimators. Zivich PN, Breskin A.  (2021). Epidemiology, 32(3), 393-401.

Targeted maximum likelihood estimation of causal effects with interference: a simulation study. Zivich PN, Hudgens MG, Brookhart MA, Moody J, Weber DJ, Aiello AE.  (2022). Statistics in Medicine, 41(23), 4554– 4577.

Introducing Proximal Causal Inference in Epidemiology. Zivich PN, Cole SR, Edwards JK, Mulholland GE, Shook-Sa BE, Tchetgen Tchetgen E. (2023). American Journal of Epidemiology, 192(7), 1224-1227.

Education