Koichiro Shiba

Koichiro Shiba’s overarching research goal is using rigorous causal inference thinking and methods to improve evidence on social determinants of health and health disparities. Rather than merely applying complex methods, his motto is to harness their full potential by identifying and applying the methods to the unique challenges in social epidemiologic studies where they truly shine. Shiba leads a multitude of projects spanning a broad spectrum of methodological issues, including but not limited to: analyzing time-varying treatments to derive different, policy-relevant insights, and identifying when conventional single-point exposure analysis may be misleading; the use of machine learning methods for robust effect estimation and assessing high-dimensional heterogeneous exposure effects, capturing the intersectionality; the consideration of causal estimands and selection bias in trauma studies with sample attrition; novel approaches to characterize and operationalize neighborhood characteristics; and a novel causal inference method to simulate the impacts of realistic hypothetical interventions on health disparities.

In addition to these methodological focuses, Shiba has worked on several key substantive areas that address urgent public health concerns, including: 1) the effects of stressful experiences and traumatic events (such as climate change, disasters, child adversity, pandemics, and global financial crises) on population health, with a particular focus on older adult populations, and 2) the roles of social relationships, social engagement (e.g., volunteering), and related exposures such as loneliness and social isolation) in promoting the health of older adults and fostering resilience. He has also explored how internet-based social interactions can influence population health. 3) Shiba studies the impacts of positive psychological factors (for instance, purpose in life, Ikigai) on health. His research further delves into inequalities in and determinants of multidimensional well-being (i.e., human flourishing), which extends beyond traditional physical and mental health outcomes and include other key domains of human well-being such as purpose in life and social well-being. In essence, Shiba’s objective for this line of research is to study health in its fullest sense, defined by the World Health Organization as “a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity”.

Research Interests:

• Social Epidemiology
• Health Disparities
• Epidemiologic Methods
• Causal Inference
• Machine Learning
• Effect Heterogeneity
• Traumatic Events/Disasters
• Positive Psychological Factors
• Well-being
• Healthy Aging
• Social Engagement
• Neighborhood/Built-Environment

Google Scholar