Chernyavskiy, Pavel, Ph.D.

Pavel Chernyavskiy, Ph.D.Dr. Pavel Chernyavskiy joined the University of Virginia as an Assistant Professor in January 2021. His methodological work is motivated by the analysis of correlated data, broadly construed. Correlated data arise from taking multiple observations on the same subject or cluster of subjects, taking observations near one another in space, in time, or jointly in space and time. His areas of collaborative research have spanned public health, education, psychology, and ecology, to name a few.

Prior to UVA, Dr. Chernyavskiy was an Assistant Professor of Statistics at the University of Wyoming (2018-2020) and a Postdoctoral Fellow at the National Cancer Institute – Division of Cancer Epidemiology and Genetics (2015-2018).

Assistant Professor
Department of Public Health Sciences, Division of Biostatistics
Ph.D., Statistics, University of Nebraska-Lincoln, 2015

Public Health Sciences
P.O. Box 800717
Charlottesville, VA 22908-0717

Tel: (434)923-4745
3rd floor of the Old Medical School Room 3883


spatial statistics, hierarchical models, Bayesian statistics, statistics education

Research Interests:

health disparities, population health, non-stationary spatial correlation, intervention efficacy


Selected Work

* indicates mentee co-author


  • Narr, C. F.*Chernyavskiy, P., and Collins, S. M.. (2022)Partitioning macroscale and microscale ecological processes using covariate-driven non-stationary spatial modelsEcological Applications 32(1):e02485. 10.1002/eap.2485
  • Froelicher, J. H.*, Forjaz, G., Rosenberg, P. S., and Chernyavskiy, P. (2021). Geographic disparities of breast cancer incidence in Portugal at the district level: A spatial age-period-cohort analysis, 1998-2011. Cancer Epidemiology74
  • Chernyavskiy, P., Little, M. P., & Rosenberg, P. S. (2020). Spatially varying age–period–cohort analysis with application to US mortality, 2002–2016, Biostatistics, Volume 21, Issue 4, Pages 845–859,
  • Chernyavskiy, P., Little, M. P., & Rosenberg, P. S. (2019). A unified approach for assessing heterogeneity in age–period–cohort model parameters using random effects. Statistical Methods in Medical Research28(1), 20–34.
  • Chernyavskiy, P., Kennerley, V. M.*, Jemal, A., Little, M. P., & Rosenberg, P. S. (2019). Heterogeneity of colon and rectum cancer incidence across 612 SEER counties, 2000–2014. International Journal of Cancer144(8), 1786-1795.
  • Chernyavskiy, P., Little, M. P., & Rosenberg, P. S. (2018). Correlated Poisson models for age‐period‐cohort analysis. Statistics in medicine, 37(3), 405-424.


  • Davis Lynn, B. C., Chernyavskiy, P., Gierach, G. L., & Rosenberg, P. S. (2022). Decreasing Incidence of Estrogen Receptor–Negative Breast Cancer in the United States: Trends by Race and Region. JNCI: Journal of the National Cancer Institute114(2), 263-270.
  • Stephens KE, Chernyavskiy P, Bruns DR (2021) Impact of altitude on COVID-19 infection and death in the United States: A modeling and observational study. PLoS ONE 16(1): e0245055.
    • Interactive COVID-19 Dashboard, updated daily: link
  • Shiels MS, Chernyavskiy P, Anderson WF, Best AF, Haozous EA, Hartge P, Rosenberg PS, Thomas D, Freedman ND, Berrington de Gonzalez A. Trends in premature mortality in the USA by sex, race, and ethnicity from 1999 to 2014: an analysis of death certificate data. Lancet. (2017); 389(10073):1043-1054.

Active projects (Pre-prints)


Links to More Information:

Code and data on GitHub: GitHub page

ResearchGate: ResearchGate profile

Google Scholar: Google Scholar profile

Applied Bayesian Statistics course on YouTube: Applied Bayes course

Introduction to Spatial Statistics course on YouTube: Intro to Spatial Statistics