Joshua Epstein

Professor of Epidemiology

Professional overview

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.

Education

BA, Independent Scholar with Thesis in Political Economy, Amherst College, Amherst, MA

PhD, Political Science (Specialization: Security Studies, Communist Studies, and Economics), Massachusetts Institute of Technology, Cambridge, MA

Honors and awards

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)

Areas of research and study

Agent-Based Modeling

Applied Economics

Cost Analysis

Disaster Health

Epidemiology

Health Economics

Infectious Diseases

Mathematical and Computational Modeling

Modeling Social and Behavioral Dynamics

New York Department of Health and Mental Hygiene

Public Health Systems

Urban Health

Urban Informatics

Urban Science

Presentations

Agent Zero and Generative Social Science

Agent Zero and Integrative Economics

Publications

Publications

A distributed platform for global-scale agent-based models of disease transmission

Parker, J., & Epstein, J. (n.d.).

Publication year

2011

Journal title

ACM Transactions on Modeling and Computer Simulation

Volume

22

Issue

1

10.1145/2043635.2043637

Abstract

Abstract

The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM's speed and scalability.

A hybrid epidemic model : Combining the advantages of agent-based and equation-based approaches

Bobashev, G. V., Goedecke, D. M., Yu, F., & Epstein, J. (n.d.).

Publication year

2007

Page(s)

1532-1537

10.1109/WSC.2007.4419767

Abstract

Abstract

Agent-based models (ABMs) are powerful in describing structured epidemiological processes involving human behavior and local interaction. The joint behavior of the agents can be very complex and tracking the behavior requires a disciplined approach. At the same time, equation-based models (EBMs) can be more tractable and allow for at least partial analytical insight. However, inadequate representation of the detailed population structure can lead to spurious results, especially when the epidemic process is beginning and individual variation is critical. In this paper, we demonstrate an approach that combines the two modeling paradigms and introduces a hybrid model that starts as agent-based and switches to equation-based after the number of infected individuals is large enough to support a population-averaged approach. This hybrid model can dramatically save computational times and, more fundamentally, allows for the mathematical analysis of emerging structures generated by the ABM.

A review and agenda for integrated disease models including social and behavioural factors

Bedson, J., Skrip, L. A., Pedi, D., Abramowitz, S., Carter, S., Jalloh, M. F., Funk, S., Gobat, N., Giles-Vernick, T., Chowell, G., de Almeida, J. R., Elessawi, R., Scarpino, S. V., Hammond, R. A., Briand, S., Epstein, J., Hébert-Dufresne, L., & Althouse, B. M. (n.d.).

Publication year

2021

Journal title

Nature human behaviour

Volume

5

Issue

7

Page(s)

834-846

10.1038/s41562-021-01136-2

Abstract

Abstract

Social and behavioural factors are critical to the emergence, spread and containment of human disease, and are key determinants of the course, duration and outcomes of disease outbreaks. Recent epidemics of Ebola in West Africa and coronavirus disease 2019 (COVID-19) globally have reinforced the importance of developing infectious disease models that better integrate social and behavioural dynamics and theories. Meanwhile, the growth in capacity, coordination and prioritization of social science research and of risk communication and community engagement (RCCE) practice within the current pandemic response provides an opportunity for collaboration among epidemiological modellers, social scientists and RCCE practitioners towards a mutually beneficial research and practice agenda. Here, we provide a review of the current modelling methodologies and describe the challenges and opportunities for integrating them with social science research and RCCE practice. Finally, we set out an agenda for advancing transdisciplinary collaboration for integrated disease modelling and for more robust policy and practice for reducing disease transmission.

Advancing Agent_Zero

Epstein, J., & Chelen, J. (n.d.). (A. Kirman & D. S. Wilson, Eds.).

Publication year

2016

Abstract

Abstract

~

Agent-based computational models and generative social science

Epstein, J. (n.d.).

Publication year

2012

Page(s)

4-46

Abstract

Abstract

~

Agent-based computational models and generative social science

Epstein, J. (n.d.).

Publication year

1999

Journal title

Complexity

Volume

4

Issue

5

Page(s)

41-60

10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F

Abstract

Abstract

This article argues that the agent-based computational model permits a distinctive approach to social science for which the term “generative” is suitable. In defending this terminology, features distinguishing the approach from both “inductive” and “deductive” science are given. Then, the following specific contributions to social science are discussed: The agent-based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agent-based modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent-based (“bottom up”) models. The agent-based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent-based modeling offers powerful new forms of hybrid theoretical-computational work; these are particularly relevant to the study of non-equilibrium systems. The agent-based approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agent-based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible.

Agent-Based Computational Models and Generative Social Science

Epstein, J. (n.d.).

Publication year

1999

Journal title

Complexity

Volume

4

Issue

5

Page(s)

41-60

Abstract

Abstract

~

Agent-Based Modeling: Understanding Our Creations

Axtell, R., & Epstein, J. (n.d.).

Publication year

1994

Journal title

The Bulletin of the Santa Fe Institute

Volume

9

Issue

4

Page(s)

28-32

Abstract

Abstract

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Agent_Zero : Toward Neurocognitive Foundations for Generative Social Science

Epstein, J. (n.d.).

Publication year

2014

Volume

9781400848256

Abstract

Abstract

The Final Volume of the Groundbreaking Trilogy on Agent-Based Modeling. In this pioneering synthesis, Joshua Epstein introduces a new theoretical entity: Agent_Zero. This software individual, or "agent," is endowed with distinct emotional/affective, cognitive/deliberative, and social modules. Grounded in contemporary neuroscience, these internal components interact to generate observed, often far-from-rational, individual behavior. When multiple agents of this new type move and interact spatially, they collectively generate an astonishing range of dynamics spanning the fields of social conflict, psychology, public health, law, network science, and economics. Epstein weaves a computational tapestry with threads from Plato, Hume, Darwin, Pavlov, Smith, Tolstoy, Marx, James, and Dostoevsky, among others. This transformative synthesis of social philosophy, cognitive neuroscience, and agent-based modeling will fascinate scholars and students of every stripe. Epstein's computer programs are provided in the book or on its Princeton University Press website, along with movies of his "computational parables." Agent_Zero is a signal departure in what it includes (e.g., a new synthesis of neurally grounded internal modules), what it eschews (e.g., standard behavioral imitation), the phenomena it generates (from genocide to financial panic), and the modeling arsenal it offers the scientific community. For generative social science, Agent_Zero presents a groundbreaking vision and the tools to realize it.

Agent_Zero and Evolutionary Economics

Epstein, J. (n.d.). (P. G. Dosi, Ed.).

Publication year

2025

Abstract

Abstract

~

Agent_Zero and the Social, Behavioral, and hHealth Sciences.

Epstein, J. (n.d.).

Journal title

Systemi Intelligenti

Abstract

Abstract

~

Agent_Zero InternationalConference onEvolutionaryEconomicsInvitedLecturerPisa, Italy Nov 6,2023

Epstein, J. (n.d.).

Publication year

2023

Abstract

Abstract

~

Agent_Zero InternationalConference onEvolutionaryEconomicsInvitedLecturerPisa, Italy Nov 6,2023

Epstein, J. (n.d.).

Publication year

2023

Abstract

Abstract

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Aligning Simulation Models: A Case Study and Results

Axtell, R., Axelrod, R., Cohen, M., & Epstein, J. (n.d.).

Publication year

1996

Journal title

Computational and Mathematical Organization Theory

Volume

1

Issue

2

Page(s)

123-141

Abstract

Abstract

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Artificial Societies and Generative Social Science

Axtell, R., & Epstein, J. (n.d.). (1st ed.).

Publication year

1996

Volume

1

Page(s)

33-34

Abstract

Abstract

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Assessing the Military Balance: Defense Analysis and the Defense Debate

Epstein, J. (n.d.).

Publication year

1985

Journal title

The Brookings Review

Volume

3

Issue

3

Page(s)

16-20

Abstract

Abstract

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At the Boundary of Law and Software : Toward Regulatory Design with Agent-Based Modeling

Benthall, S., Tschantz, M. C., Hatna, E., Epstein, J., & Strandburg, K. J. (n.d.).

Publication year

2022

Journal title

CEUR Workshop Proceedings

Volume

3182

Abstract

Abstract

Computer systems that automate the making of decisions about people must be accountable to regulators. Such accountability requires looking at the operation of the software within an environment populated with people. We propose to use agent-based modeling (ABM) to model such environments for auditing and testing purposes. We explore our proposal by considering the use of ABM for the regulation of ad targeting to prevent housing discrimination.

Can Social Norms Explain Long-Term Trends in Alcohol Use? Insights from Inverse Generative Social Science

Vu, T. M., Buckley, C., Duro, J. A., Brennan, A., Epstein, J., & Purshouse, R. C. (n.d.).

Publication year

2023

Journal title

JASSS

Volume

26

Issue

2

10.18564/jasss.5077

Abstract

Abstract

Social psychological theory posits entities and mechanisms that attempt to explain observable differences in behavior. For example, dual process theory suggests that an agent’s behavior is influenced by intentional (arising from reasoning involving attitudes and perceived norms) and unintentional (i.e., habitual) processes. In order to pass the generative sufficiency test as an explanation of alcohol use, we argue that the theory should be able to explain notable patterns in alcohol use that exist in the population, e.g., the distinct differences in drinking prevalence and average quantities consumed by males and females. In this study, we further develop and apply inverse generative social science (iGSS) methods to an existing agent-based model of dual process theory of alcohol use. Using iGSS, implemented within a multi-objective grammar-based genetic program, we search through the space of model structures to identify whether a single parsimonious model can best explain both male and female drinking, or whether separate and more complex models are needed. Focusing on alcohol use trends in New York State, we identify an interpretable model structure that achieves high goodness-of-fit for both male and female drinking patterns simultaneously, and which also validates success-fully against reserved trend data. This structure offers a novel interpretation of the role of norms in formulating drinking intentions, but the structure’s theoretical validity is questioned by its suggestion that individuals with low autonomy would act against perceived descriptive norms. Improved evidence on the distribution of autonomy in the population is needed to understand whether this finding is substantive or is a modeling artefact.

Chapter 34 Remarks on the Foundations of Agent-Based Generative Social Science

Epstein, J. (n.d.). (L. Tesfatsion & K. Judd, Eds.).

Publication year

2006

Page(s)

1585-1604

10.1016/S1574-0021(05)02034-4

Abstract

Abstract

This chapter treats a variety of epistemological issues surrounding generative explanation in the social sciences, and discusses the role of agent-based computational models in generative social science.

Civil Violence and EndogenousInequalityInstitut desSystemesComplexes,InvitedLecturerParis October2023

Epstein, J. (n.d.).

Publication year

2023

Abstract

Abstract

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Combining computational fluid dynamics and agent-based modeling : A new approach to evacuation planning

Epstein, J., Pankajakshan, R., & Hammond, R. A. (n.d.).

Publication year

2011

Journal title

PloS one

Volume

6

Issue

5

10.1371/journal.pone.0020139

Abstract

Abstract

We introduce a novel hybrid of two fields-Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)-as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool.

Containing a large bioterrorist smallpox attack : a computer simulation approach

Longini, I. M., Elizabeth Halloran, M., Nizam, A., Yang, Y., Xu, S., Burke, D. S., Cummings, D. A., & Epstein, J. (n.d.).

Publication year

2007

Journal title

International Journal of Infectious Diseases

Volume

11

Issue

2

Page(s)

98-108

10.1016/j.ijid.2006.03.002

Abstract

Abstract

Background: A bioterrorist release of smallpox is a constant threat to the population of the USA and other countries. Design: A stochastic simulation model of the spread of smallpox due to a large bioterrorist attack in a structured population was constructed. Disease natural history parameter estimates, time lines of behavioral activities, and control scenarios were based on the literature and on the consensus opinion of a panel of smallpox experts. Results: The authors found that surveillance and containment, i.e., isolation of known cases and vaccination of their close contacts, would be sufficient to effectively contain a large intentional smallpox release. Given that surveillance and containment measures are in place, preemptive vaccination of hospital workers would further reduce the number of smallpox cases and deaths but would require large numbers of prevaccinations. High levels of reactive mass vaccination after the outbreak begins would further reduce smallpox cases and deaths to a minimum, but would require even larger numbers of vaccinations. Reactive closure of schools would have a minimal effect. Conclusion: A rapid and well-organized response to a bioterrorist attack would be necessary for effective surveillance and containment to control spread. Preemptive vaccination of hospital workers and reactive vaccination of the target population would further limit spread, but at a cost of many more vaccinated. This cost in resources and potential harm due to vaccination will have to be weighed against the potential benefits should an attack occur. Prevaccination of the general population is not necessary.

Controlling pandemic flu : The value of international air travel restrictions

Epstein, J., Goedecke, D. M., Yu, F., Morris, R. J., Wagener, D. K., & Bobashev, G. V. (n.d.).

Publication year

2007

Journal title

PloS one

Volume

2

Issue

5

10.1371/journal.pone.0000401

Abstract

Abstract

Background. Planning for a possible influenza pandemic is an extremely high priority, as social and economic effects of an unmitigated pandemic would be devastating. Mathematical models can be used to explore different scenarios and provide insight into potential costs, benefits, and effectiveness of prevention and control strategies under consideration. Methods and Findings. A stochastic, equation-based epidemic model is used to study global transmission of pandemic flu, including the effects of travel restrictions and vaccination. Economic costs of intervention are also considered. The distribution of First Passage Times (FPT) to the United States and the numbers of infected persons in metropolitan areas worldwide are studied assuming various times and locations of the initial outbreak. International air travel restrictions alone provide a small delay in FPT to the U.S. When other containment measures are applied at the source in conjunction with travel restrictions, delays could be much longer. If in addition, control measures are instituted worldwide, there is a significant reduction in cases worldwide and specifically in the U.S. However, if travel restrictions are not combined with other measures, local epidemic severity may increase, because restriction-induced delays can push local outbreaks into high epidemic season. The per annum cost to the U.S. economy of international and major domestic air passenger travel restrictions is minimal: on the order of 0.8% of Gross National Product. Conclusions. International air travel restrictions may provide a small but important delay in the spread of a pandemic, especially if other disease control measures are implemented during the afforded time. However, if other measures are not instituted, delays may worsen regional epidemics by pushing the outbreak into high epidemic season. This important interaction between policy and seasonality is only evident with a global-scale model. Since the benefit of travel restrictions can be substantial while their costs are minimal, dismissal of travel restrictions as an aid in dealing with a global pandemic seems premature.

Controlling the Greenhouse Effect: Five Global Regimes Compared

Epstein, J., & Gupta, R. (n.d.).

Publication year

1990

Abstract

Abstract

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Conventional Force Reductions: A Dynamic Assessment

Epstein, J. (n.d.).

Publication year

1990

Abstract

Abstract

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