First Trainees Join the Center
Claudia Nau is a demographer and social epidemiologist with interests in measurement issues in health research, and contextual and neighborhood effects on health and obesity. She received both her M.A. and Ph.D. in Sociology and Demography from the Pennsylvania State University and an undergraduate degree in Economic and Social History from the University of Geneva, Switzerland. Claudia has trained in formal demography, spatial analysis and multi-level models. In her work she has paid particular attention to the potentials and limitations of quantitative methods to unravel the complexity of the phenomena they are trying to explain. In her M.A. thesis, she developed a variance decomposition method that decomposes population differences in mortality inequality into their cause-of-death specific underpinnings. Her dissertation grafts a Monte Carlo Simulation experiment on census data to assess the bias introduced into the results of multi-level models by mis-measuring neighborhoods.
In addition to her methodological research, she has conducted research on family and school influences on adolescent obesity, and contextual determinants of obesity-related health behaviors in the elderly. She has also contributed to the quasi-experimental Philadelphia Neighborhood, Food environment, Health and Diet Study, which examines the effects of a grocery store intervention in a food desert. Her research has been published in Social Science and Medicine, Demography and Demographic Methods.
Hong Xue is a second year doctoral student in the Human Nutrition program in International Health at the Bloomberg School of Public Health. He was trained as a health economist and has a PhD in econometric modeling and quantitative methods. His research areas include systems modeling of obesity, chronic disease epidemiology, and quantitative methods in health data analysis. His current research focuses on complex systems analysis of the global childhood obesity epidemic and related non-communicable chronic diseases. In the next three years, his research will be directed toward comparative studies of the childhood obesity between China and the US using a combination of traditional statistical approaches and innovative systems models. Specifically, he would like to examine the longitudinal changes in the food system and dietary patterns since the early 1990s in China, to identify the key contextual drivers of childhood obesity in China’s fast changing economic, social and cultural environment. Comparing these drivers with those found in the US based studies, and developing a generic simulation platform for comparative study, will lead to the development of systems models to assess the cost-effectiveness of potential interventions. In the long term, he plans to integrate economics, nutrition epidemiology, and systems science in the research of obesity and obesity-related non-communicable chronic diseases in the global context.
Mehdi Jalalpour is a PhD candidate at the Whiting School of Engineering with extensive systems-oriented research experience. He received the Meyerhoff Fellowship from the department of civil engineering to start his graduate studies. His research involves mathematical modeling of complex systems and has evolved from analysis of engineering structures to more transdisciplinary fields, currently focusing on public health issues such as disaster readiness and epidemic prediction using complex modeling. Recent projects have included CDC funded research interfacing building response with human behavior during seismic events, which uses Agent Based Modeling (ABM) to visualize and explain the evacuation of buildings during and following an earthquake. He is also working on a collaborative project with the School of Medicine to predict influenza outbreaks in Baltimore using time series modeling techniques on publicly available Google data. He has just started work with Dr. Thomas Glass and Dr. Brian Schwartz building systems models for Project 1:“Dynamics of Childhood Obesity in Pennsylvania from Community to Epigenetics”. He has gained first hand experience of agent-based modeling, system dynamics modeling, GIS, and data mining and is looking forward to developing and applying his skills within the framework of childhood obesity research.