John Gitau

John Gitau is a PhD student under the Malaria Modelling for Sustainable Public Health Policies in Africa (MaModAfrica) consortium. He is a promising data scientist, and emerging African mathematical infectious disease modeler. With four years of research and leadership experience, John is adept at Epidemiology, bioinformatics and biostatistics. John is driven by a passion to apply quantitative data science techniques to understand the transmission dynamics of infectious diseases, aiming to contribute to the development of effective, evidence-based interventions and policy formulation. John is proficient in disease modeling and analysis of biological data, including genomics and transcriptomics, allowing him to inform health outcomes and public health policies. John is skilled in creating bioinformatics pipelines for omics data analysis, demonstrating expertise in the R programming language, Git and GitHub, Conda package management, and Unix for high-performance computing. Having previously worked on Rift-Valley Fever, a zoonotic disease, John brings to the team, a multidimensional, data-centric approach to understanding disease pathogenesis and management.