MR. ADEWEMIMO CHARLES

Adewemimo Charles is a public health researcher, data manager, and implementation scientist with extensive experience in infectious disease surveillance, vaccine safety, antimicrobial resistance, and digital health systems across Africa. He holds a first degree in Statistics and a second degree in Biostatistics, providing a strong quantitative foundation for his work in public health research, surveillance, and data-driven decision-making.
He currently serves as Country Data Manager for the BRAVE Study in Nigeria, where he leads national data management and surveillance activities supporting the evaluation of vaccine safety and adverse events of special interest.
Over the course of his career, Charles has contributed to a wide range of major public health initiatives, including the BRAVE Study, CAMRA, MERCK-IPD, PROVE in Africa, invasive pneumococcal disease and meningitis surveillance, antimicrobial resistance research, and COVID-19 vaccine safety surveillance. His work has included study coordination, data management, quality assurance, surveillance system strengthening, protocol and database development, implementation research, and advanced statistical analysis.
Charles has particular expertise in the design and implementation of digital platforms for public health data systems. He has led the development and integration of electronic data capture systems, REDCap-based surveillance platforms, automated laboratory data pipelines, and AI-enabled tools to support disease surveillance, clinical decision-making, and research implementation. His current interests focus on integrating phenotypic, genomic, and clinical data to strengthen antimicrobial resistance surveillance and outbreak response in Africa.
He is currently an External PhD Candidate at Utrecht University and UMC Utrecht, where his research focuses on strengthening antimicrobial resistance surveillance in African laboratories through interoperable digital platforms that integrate phenotypic and genomic data. His work combines digital health, surveillance systems, implementation science, and public health informatics to support evidence-based decision-making.