Assessing the Use of Agent-Based Models for Tobacco Regulation (2015)

Assessing the Use of
AGENT-BASED MODELS
for TOBACCO REGULATION

Committee on the Assessment of Agent-Based Models to Inform
Tobacco Product Regulation

Board on Population Health and Public Health Practice

Robert Wallace, Amy Geller, and V. Ayano Ogawa, Editors

INSTITUTE OF MEDICINE
               OF THE NATIONAL ACADEMIES

THE NATIONAL ACADEMIES PRESS

Washington, D.C.

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NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance.

This study was supported by Contract/Grant No. HHSF22301031T between the National Academy of Sciences and the Department of Health and Human Services: Food and Drug Administration. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the organizations or agencies that provided support for the project.

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Suggested citation: IOM (Institute of Medicine). 2015. Assessing the use of agent-based models for tobacco regulation. Washington, DC: The National Academies Press.

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INSTITUTE OF MEDICINE
              OF THE NATIONAL ACADEMIES

Advising the Nation. Improving Health.

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COMMITTEE ON THE ASSESSMENT OF AGENT-BASED
MODELS TO INFORM TOBACCO PRODUCT REGULATION

ROBERT WALLACE (Chair), Irene Ensminger Stecher Professor of Epidemiology and Internal Medicine, Department of Epidemiology, University of Iowa

ELIZABETH BRUCH, Assistant Professor of Sociology and Complex Systems, Assistant Research Scientist, Population Studies Center, Department of Sociology, University of Michigan

KAREN GLANZ, George A. Weiss University Professor (Penn Integrates Knowledge [PIK] Professor), Professor of Epidemiology and Nursing, Perelman School of Medicine and School of Nursing, University of Pennsylvania

CARLOS ROBERTO JAÉN, Dr. and Mrs. James L. Holly Distinguished Professor and Chairman of Family and Community Medicine, and Professor of Epidemiology and Biostatistics, University of Texas Health Science Center, San Antonio

SCOTT J. LEISCHOW, Professor of Health Sciences Research, Mayo Clinic

DOUGLAS LUKE, Professor and Director, Center for Public Health Systems Science, George Warren Brown School of Social Work, Washington University in St. Louis

CHARLES F. MANSKI, Board of Trustees Professor in Economics, Department of Economics, Northwestern University

DAVID MENDEZ, Associate Professor, Health Management and Policy, School of Public Health, University of Michigan

NANCY A. RIGOTTI, Professor of Medicine, Harvard Medical School, Director of Tobacco Research and Treatment Center, Associate Chief, General Medicine Division, Massachusetts General Hospital

DAVID SHOHAM, Associate Professor, Department of Public Health, Loyola University Chicago

JODY SINDELAR, Professor of Public Health (Policy) and Economics, Department of Health Policy and Management, School of Public Health, Yale University

MELISSA STIGLER, Associate Professor, Division of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas

Consultants

LAWRENCE E. BLUME, Goldwin Smith Professor of Economics, Cornell University

ROSS A. HAMMOND, Senior Fellow in Economic Studies, Brookings Institution

ALAN H. SANSTAD, Staff Scientist, Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory

IOM Staff

AMY GELLER, Study Director

V. AYANO OGAWA, Research Associate

BETTINA RITTER, Research Assistant

ANNA MARTIN, Senior Program Assistant

DORIS ROMERO, Financial Associate

ROSE MARIE MARTINEZ, Senior Board Director, Board on Population Health and Public Health Practice

Reviewers

This report has been reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise, in accordance with procedures approved by the National Research Council’s Report Review Committee. The purpose of this independent review is to provide candid and critical comments that will assist the institution in making its published report as sound as possible and to ensure that the report meets institutional standards for objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We wish to thank the following individuals for their review of this report:

DAMON M. CENTOLA, University of Pennsylvania

SEYMOUR S. COHEN, Marine Biological Laboratory

ANA V. DIEZ ROUX, Drexel University

STEVEN N. DURLAUF, University of Wisconsin–Madison

STEPHEN EUBANK, Virginia Polytechnic Institute and State University

SANTO FORTUNATO, Aalto University

DOROTHY HATSUKAMI, University of Minnesota, Minneapolis

LEE D. HOFFER, Case Western Reserve University

ELENA G. IRWIN, Ohio State University

PAULA M. LANTZ, George Washington University

DAVID LEVY, Georgetown University

SIDNEY REDNER, Boston University

Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations, nor did they see the final draft of the report before its release. The review of this report was overseen by RONALD S. BROOKMEYER, University of California, Los Angeles, and ALFRED O. BERG, University of Washington. Appointed by the National Research Council and the Institute of Medicine, they were responsible for making certain that an independent examination of this report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of this report rests entirely with the authoring committee and the institution.

Contents

ACRONYMS AND ABBREVIATIONS

PREFACE

SUMMARY

1 INTRODUCTION

Addressing the Statement of Task

Background

Computational Modeling of Tobacco Use

References

2 TOBACCO CONTROL LANDSCAPE

Tobacco Environment

Regulatory Authority for Tobacco Products

Tobacco Use Behavior

Why Use Agent-Based Models to Explore Tobacco Use?

Concluding Comments

References

3 BUILDING EFFECTIVE MODELS TO GUIDE POLICY DECISION MAKING

The Challenge of Anticipating and Understanding Policy Effects

Mechanisms That Generate Feedback Between Behavior and Social Environments

Overview of Types of Structural Models for Informing Policy Decisions

Specifying Individual Behavior in Agent-Based Models

Model Uncertainty and Policy Decision Making

Conclusion

References

4 AN EVALUATION FRAMEWORK FOR POLICY-RELEVANT AGENT-BASED MODELS

Model Description

Evaluation Framework

Case Examples

Annex

Example of Applying Grammar to Describe Agent-Based Models

Evaluation Questions Derived from the Evaluation Framework for Policy Relevant Agent-Based Models

References

5 REVIEW OF THE SOCIAL NETWORK ANALYSIS FOR POLICY ON DIRECTED GRAPH NETWORKS MODEL

Background

SnapDragon Model Evaluation

Implications for the SnapDragon Model

References

6 DATA AND IMPLEMENTATION NEEDS FOR COMPUTATIONAL MODELING FOR TOBACCO CONTROL

Existing Tobacco Use Data Sources

Data Needs for Future Modeling Efforts

Data Collection and Model Development at the Center for Tobacco Products

Conclusion

References

APPENDIXES

A Considerations and Best Practices in Agent-Based Modeling to Inform Policy, Ross A. Hammond

B Agent-Based Models for Policy Analysis, Lawrence Blume

Annex

C Assessing Agent-Based Models for Regulatory Applications: Lessons from Energy Analysis, Alan H. Sanstad

Annex

D Committee Meeting Agendas

E Committee Biographical Sketches

INDEX

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Acronyms and Abbreviations

Preface

Models are often used to represent complex systems. As such, they can be used to provide a framework for thinking through difficult problems, to help researchers understand factors within the complex system and their relations to specific events, to guide data collection efforts, and to identify research needs. Models are also useful for exploring policy and regulatory questions.

There is a long history of using models as one tool to guide policy making in a range of disciplines, including transportation, environmental health, energy, and health. One public health topic in which various modeling approaches have been used to address policy questions is tobacco control. Tobacco control models have been used to look at the impact of cigarette taxes, smoke-free ordinances, and smoking cessation programs. The Center for Tobacco Products (CTP) at the U.S. Food and Drug Administration (FDA) uses modeling to inform its regulatory decisions. In fact, two population models—SimSmoke and the Cancer Intervention and Surveillance Modeling Network, or CISNET, model—were used in a recent CTP-sponsored Institute of Medicine (IOM) report to study the impact of changing the minimum purchase age of tobacco products.¹ Those models, along with insights gleaned from traditional statistical and epidemiological studies, helped inform that committee’s conclusions.

Although these models continue to be important in informing policy decisions by making it possible to project the impact of tobacco policies

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¹IOM (Institute of Medicine). 2015. Public health implications of raising the minimum age of legal access to tobacco products. Washington, DC: The National Academies Press.

and interventions at the population level (aggregate models), the majority of these models do not consider interactions at the individual level or the heterogeneity of individuals, which can be important when examining some tobacco regulatory policies. One modeling approach that CTP is exploring to address such individual interactions is the use of agent-based models (ABMs). ABMs can elucidate interactions at the individual level and thus complement population models. Existing population-level tobacco control models have provided great insight into the effects of various tobacco policies, and multiple modeling approaches are needed—and will continue to be needed—for complex problems such as understanding the impact of tobacco regulation. The results of ABMs can also be used as inputs for population models. With that in mind, it should be noted that the recommendations in this report have no relevance for the type of modeling used in the recent 2015 IOM report noted above, which focused on projections based on population models.

Through an interagency agreement, CTP commissioned Sandia National Laboratories (SNL) to develop an ABM to explore certain tobacco policies under the jurisdiction of CTP. To that end, SNL is developing a model entitled Social Network Analysis for Policy on Directed Graph Networks (SnapDragon). Thus far, the model has been developed through an iterative process and as of July 2014 was in an intermediate stage of development. CTP asked IOM to evaluate SnapDragon in its current stage of development. The Committee on the Assessment of Agent-Based Models to Inform Tobacco Product Regulation was created to conduct that review, which is presented in this report. CTP also asked for advice on using ABMs in the future, which the committee addresses in this report. The developers of SnapDragon provided updates on the model up until July 31, 2014. In July 2014 and January 2015, draft descriptions of the committee’s technical understanding of the model² were sent to SNL for technical review. In the lab’s January 2015 response, SNL described some updates that had been made to the model since the July 31, 2014, cutoff date and also provided information on some changes to the model that might be made in the future. However, the committee did not have an opportunity to examine any revisions to the model made after July 2014.

In addition to evaluating SnapDragon, the report offers guidance to CTP on developing and evaluating ABMs. It was beyond the scope of this report to develop specific guidance on exactly what policies or questions could be addressed using policy-relevant tobacco control ABMs. Furthermore, developing a core set of essential domains or attributes for policy-relevant

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²The correspondence and excerpts between the committee and SNL are available in the project public access file: https://www8.nationalacademies.org/cp/ManageRequest.aspx?key=49612.

tobacco control models is a challenging venture that would vary depending on the intended purpose of the model; the time frame of this study did not allow the committee to fully explore this. In Chapter 2 the committee outlines the complex tobacco regulatory environment and the variables that need to be considered in the current regulatory environment. Each policy question to be addressed by FDA will require input from subject-matter experts as well as modeling experts to ensure that the relevant dynamics are captured in the model. This report also offers a number of issues for ABM modelers and model users to consider during model development, some important data considerations, and an evaluation framework that CTP can use in its future development of ABMs.

Acknowledgments

The committee wishes to thank the colleagues, organizations, and agencies that shared their expertise in the development of this report. Their contributions informed the committee and enhanced the quality of the report.

First, the committee thanks the Center for Tobacco Products of FDA for sponsoring the report and for bringing attention to the importance of developing models that can inform tobacco control policy. The committee expresses its deep appreciation for the SnapDragon model developers at SNL for their willingness to present the model, respond to the committee’s questions, and share their experience and thoughts on the model.

The committee thanks Lawrence Blume, Ross Hammond, and Alan Sanstad for writing commissioned papers that informed the committee on the varying views concerning ABM, the practice of and pitfalls associated with ABM, and lessons learned regarding the application of ABMs. These papers were critical to the committee’s deliberations.

The committee also thanks those individuals who volunteered their time and shared a wealth of information with the committee during our public meetings. Their perspectives provided valuable insights which informed the deliberations of the committee and, ultimately, the report. The meeting agendas provided in Appendix D include the names of all speakers. The committee would especially like to thank Margaret (Maggie) Eppstein of the University of Vermont and Allison Ritter and Pascal Perez of the Drug Policy Modelling Program based at the University of New South Wales in Australia for taking the time to describe the ABMs they had developed, and to answer questions from the committee and staff.

Finally, the committee expresses its gratitude to the IOM staff members who contributed to the production of this report, including study director Amy Geller, research associate V. Ayano Ogawa, research assistant Bettina Ritter, senior program assistant Anna Martin, and board director Rose Marie Martinez. Other staff members of the Board on Population Health

and Public Health Practice, including Hope Hare, Doris Romero, and Kathleen Stratton, provided important support as well. The committee is also thankful for Norman Grossblatt and Robert Pool for their editorial support as well as for the National Academies Research Center.

On a personal note, I thank the members of the IOM Committee on the Assessment of Agent-Based Models to Inform Tobacco Product Regulation, who volunteered their time from their very busy professional lives to participate on the committee. I deeply appreciated their dedication and commitment to help guide FDA and the nation on this critical topic.

Robert Wallace, Chair
Committee on the Assessment of Agent-Based Models to Inform Tobacco Product Regulation