Joshua Epstein
Professor of Epidemiology
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Professional overview
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Joshua Epstein is Professor of Epidemiology in the NYU School of Global Public Health, and founding Director of the NYU Agent-Based Modeling Laboratory, with affiliated appointments at The Courant Institute of Mathematical Sciences, and the College of Arts & Sciences. Prior to joining NYU, he was Professor of Emergency Medicine at Johns Hopkins, and Director of the Center for Advanced Modeling in the Social, Behavior, and Health Sciences, with Joint appointments in Economics, Applied Mathematics, International Health, and Biostatistics. Before that, he was Senior Fellow in Economic Studies at the Brookings Institution and Director of the Center on Social and Economic Dynamics. His research interest has been modeling complex social dynamics using mathematical and computational methods, notably the method of Agent-Based Modeling in which he is a recognized pioneer. For this transformative innovation, he was awarded the NIH Director’s Pioneer Award in 2008, an Honorary Doctorate of Science from Amherst College in 2010, and was elected to the Society of Sigma XI in 2018. He has applied this method to the study of infectious diseases (e.g., Ebola, pandemic influenza, and smallpox), vector-borne diseases (e.g., zika), urban disaster preparedness, contagious violence, the evolution of norms, economic dynamics, computational archaeology, and the emergence of social classes, among many other topics. His books include Nonlinear Dynamics, Mathematical Biology, and Social Science (Wiley 1997), Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton, 2006), Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science (Princeton, 2013), and with Robert Axtell, Growing Artificial Societies: Social Science from the Bottom Up (MIT, 1996). Dr. Epstein earned his BA from Amherst College and his Ph.D. from The Massachusetts Institute of Technology.
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Education
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BA, Independent Scholar with Thesis in Political Economy, Amherst College, Amherst, MAPhD, Political Science (Specialization: Security Studies, Communist Studies, and Economics), Massachusetts Institute of Technology, Cambridge, MA
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Honors and awards
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Honorary Doctorate of Science, Amherst College (2010)Director’s Pioneer Award, National Institutes of Health (2008)Rockefeller Foundation International Relations Fellowship (1984)Council on Foreign Relations International Affairs Fellowship (1983)Ford Foundation Dual Expertise Fellowship in Soviet/East European Area Studies and International Security/Arms Control (1981)Institute for the Study of World Politics Fellowship (1981)
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Areas of research and study
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Agent-Based ModelingApplied EconomicsCost AnalysisDisaster HealthEpidemiologyHealth EconomicsInfectious DiseasesMathematical and Computational ModelingModeling Social and Behavioral DynamicsNew York Department of Health and Mental HygienePublic Health SystemsUrban HealthUrban InformaticsUrban Science
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Presentations
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Publications
Publications
Can Social Norms Explain Long-Term Trends in Alcohol Use? Insights from Inverse Generative Social Science
Generating Mixed Patterns of Residential Segregation: An Evolutionary Approach
Inverse Generative Social Science: Backward to the Future
Special Section on "Inverse Generative Social Science": Guest Editors’ Statement
AbstractEpstein, J. M., Garibay, I., Hatna, E., Koehler, M., & Rand, W. (n.d.).Publication year
2023Journal title
JASSSVolume
26Issue
2AbstractThis is a guest editors’ statement accompanying the publication of a special issue on "Inverse Generative Social Science", published in volume 26, issue 2, 2023 of JASSS-Journal of Artificial Societies and Social Simulation".Privacy and contact tracing efficacy
A review and agenda for integrated disease models including social and behavioural factors
Triple contagion: A two-fears epidemic model
AbstractEpstein, J. M., Hatna, E., & Crodelle, J. (n.d.).Publication year
2021Journal title
Journal of the Royal Society InterfaceVolume
18Issue
181AbstractWe present a differential equations model in which contagious disease transmission is affected by contagious fear of the disease and contagious fear of the control, in this case vaccine. The three contagions are coupled. The two fears evolve and interact in ways that shape distancing behaviour, vaccine uptake, and their relaxation. These behavioural dynamics in turn can amplify or suppress disease transmission, which feeds back to affect behaviour. The model reveals several coupled contagion mechanisms for multiple epidemic waves. Methodologically, the paper advances infectious disease modelling by including human behavioural adaptation, drawing on the neuroscience of fear learning, extinction and transmission.Data analysis and modeling pipelines for controlled networked social science experiments
Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework
The Normative Underpinnings of Population-Level Alcohol Use: An Individual-Level Simulation Model
Panel discussion
Nonlinear dynamics, mathematical biology, and social science
Advancing Agent_Zero
Social conformity despite individual preferences for distinctiveness
Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science
Modeling the regional spread and control of vancomycin-resistant enterococci
Agent-based computational models and generative social science
Coordination in transient social networks
Generative social science: Studies in agent-based computational modeling
Growing adaptive organizations
Learning to be thoughtless
Modeling civil violence
Non-explanatory equilibria
Population growth and collapse in a multiagent model of the kayenta anasazi in long house valley
Axtell, R. L., Epstein, J. M., Dean, J. S., Gumerman, G. J., Swedlund, A. C., Harburger, J., Chakravarty, S., Hammond, R., Parker, J., & Parker, M. (n.d.). In Generative Social Science (1–).Publication year
2012Page(s)
117-129Remarks on the foundations of agent-based generative social science