Nifarta Andrew Peingurta, PhD

Nifarta Andrew Peingurta, PhD

Nifarta Andrew Peingurta is an experienced monitoring and evaluation specialist and public health data scientist with strong analytical skills and expertise in big data analytics and visualization. She provides technical leadership in developing, managing, and maintaining health research databases including clinical trials databases and statistical modelling of public health data. She has a proven success record of technical leadership for data management and statistical analysis that optimized and improved monitoring and evaluation processes in a large CDC/PEPFAR funded HIV/AIDS program in Nigeria. She currently leads the data unit that supports all research projects in IRCE including the INFORM Africa project. Her research focuses on the application of complex statistical models and computational methods for the analysis of public health outcomes and their social determinants with the hope of translating scientific research findings into policy and patient education programs in order to change patient behaviour, promote self-advocacy and improve health-seeking behaviour and outcomes. She holds a PhD in social and educational policy from University of Korinthos, Greece, MSc and BSc in Statistics (Bio-statistics) from the Universities of Ibadan and Maiduguri respectively. She is a WHO TDR fellow, trained on clinical data management and statistical modelling at the Luxembourg Institute of Health, Luxembourg. She implemented a WHO TDR reintegration grant where she trained over 25 data managers, analysts, scientists and researchers in clinical data management and statistical modelling using R. Recently, she completed a Swiss TPH certificate course in Epidemiology from the European Education Programme in Epidemiology (EEPE) in Florence, Italy and currently pursuing a Master of Public Health (MPH) degree from Texila American University. She is passionate about mentoring and building capacity of young researchers in clinical data management, statistical analysis and modelling of public health data and scientific writing.

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