Juste Goungounga
  • E-mail :[email]
  • Phone : 0299022776
  • Location : Rennes, France

Version françaiseJuste Goungounga

Last update 2022-12-23 11:23:30.226

Juste Goungounga M.D.,PhD in clinical research and public health (Biostatistics)

Course and current status

I am qualified in medicine in Burkina and worked as a clinician before entering methodological research. I completed in 2014 a Master of public heath (oriented in quantitative and econometric methods) and in 2018, a PhD in full-time in clinical research and public heath (option biostatistics), both at Aix Marseille University, France. My PhD thesis topic was the extension of excess mortality analysis in to the field of clinical research. Previously, I worked in the SESSTIM research unit, as a biostatistician, mainly working on excess hazard and net survival methods in the field of clinical research. I joined the Bourguignon Digestive Cancer Registry/Université de Bourgogne ( EPICAD team - UMR 1231) in January 2020 as a postdoctoral research fellow.  I'm currently associate professor of Biostatistics and health data at the French School of Public Health (EHESP ). Here is a link to my updated list of publications: Updated Publications LIST.

Scientific summary

My research interests lie principally, but not exclusively in the field of statistical methods in cancer epidemiology and more generally in non-communicable diseases to evaluate care practices, identify and quantify the dynamics of inequalities in non-communicable diseases outcomes using:

- Cure models and time-to-cure estimators

- Excess hazard modeling in different data setting (e.g., population-based studies or hospital-based registries).

- Statistical methods for disease mapping (e.g., cluster detection methods, SPatial Oblique Decision Tree, Bayesian hierarchical modeling, multivariate disease mapping).

- Supervised classification methods: CART regression tree, PLS regression

- Development of R package (xhaz https://cran.r-project.org/package=xhaz)

- Application of statistical models/estimators to population data (population-based registries for non-communicable diseases such as cancer, end-stage renal disease, etc.), cohort data and clinical trials

Image d’exemple