Bio
Yu Chen is a PhD student in the CDT StatML programme at Imperial College London, specialising in Bayesian Statistics with applications in public health, epidemiology, and infectious diseases. Under the supervision of Dr Oliver Ratmann, her current research focuses on high-resolution modelling of sexual networks for HIV transmission analysis using Bayesian inference. Additionally, she is involved in longitudinal studies modelling the number of children affected by leading causes of death in the U.S. and various crises. Yu is a member of the Machine Learning and Global Health Network (https://mlgh.net/author/yu-chen/).
Research interests
Deaths of parents and grandparent caregivers due to social and health crises pose significant threats to child wellbeing, resulting in losses of care, financial support, physical safety, and family stability. The full burden of cause-specific orphanhood and caregiver death remains largely unknown. Excess deaths, which reflect additional deaths during the pandemic compared to a pre-pandemic period, are often used as a proxy when true mortality data are of poor quality. Estimating excess deaths can be achieved through advanced statistical modelling. At Turing, Yu aims to develop and integrate a Bayesian probabilistic programming model for excess death estimation into her orphanhood estimation pipeline. This approach will provide a comprehensive understanding of the pandemic's impact on vulnerable children and inform effective prevention and protection programs for affected children and their caregivers.