Koichiro Shiba

Koichiro Shiba

Assistant Professor of Epidemiology

Boston University School of Public Health



  • 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


  • PhD in Population Health Sciences, 2020

    Harvard University

  • Master of Public Health, 2016

    The University of Tokyo

  • BSc in Health Sciences, 2014

    The University of Tokyo

About me

My 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, my 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. I lead 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, I have worked on several key substantive areas that address urgent public health concerns. First, I study 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. Second, I investigate 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. I have also explored how internet-based social interactions can influence population health. Third, I study the impacts of positive psychological factors (for instance, purpose in life, Ikigai) on health. My 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, my 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”.

For the full list of publications, please visit my google scholar page.

Selected Publications

Quickly discover relevant content by filtering publications.
(2022). Associations of Online Religious Participation During the COVID-19 Lockdown with Subsequent Health and Well-being: A Longitudinal Study of the U.K. Population. . Psychologoical Medicine.


(2022). Global Trends of Mean and Inequality in Multidimensional Well-being From 2009 to 2019: Analysis of 1.2 Million Individuals From 162 Countries. Frontiers in Public Health.


(2022). Ikigai and subsequent health and wellbeing among Japanese older adults: Longitudinal outcome-wide analysis. The Lancet Regional Health - Western Pacific.


(2021). Heterogeneity in cognitive disability after a major disaster: A natural experiment study. Science Advances.


(2021). Estimating the impact of sustained social participation on depressive symptoms in older adults. Epidemiology.



Measurement Error and Misclassification for Epidemiologists (Role: Teaching Fellow)

Overview of the implications of and methods to deal with measurement error and misclassification in epidemiologic studies. Theories and assumptions for valid use of the correction methods were discussed.

Epidemiologic Methods III: Models for Causal Inference (Role: Teaching Fellow)

Intermediate course on epidemiologic methods for causal inference from observational data. The methods covered include stratification, regression model, propensity score, g-formula, inverse probability weighting and marginal structural model, g-estimation and structural nested mean model, and instrumental variable estimation.

Principles of Social and Behavioral Research (Role: Teaching Fellow)

Introductory course on methods for social research in public health. Topics covered include measurement, study design, survey research methods, questionnaire development, sampling, and data collection.

Advanced Epidemiologic Methods (Role: Teaching Fellow)

Advanced course on epidemiologic methods for causal inference to estimate causal effect of time-varying treatment. Topics covered include Directed Acyclic Graphs and Single World Intervention Graphs, g-formula, inverse probability weighting, dynamic regimes, structural nested models, instrumental variable estimation, and doubly robust methods.

Explaining Health Behavior: Insights from Behavioral Economics (Role: Teaching Fellow)

Review of the application of theories and constructs from behavioral sciences (particularly behavioral economics and social psychology) to the field of health behavior.

Society and Health (Role: Head Teaching Fellow)

Introductory course on social epidemiology. Reviewed key evidence of social determinants of health and their implication for population health and health disparities.