New Horizons in Modeling and Simulation for Social Epidemiology and Public Health

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Daniel Kim. New Horizons in Modeling and Simulation for Social Epidemiology and Public Health

Table of Contents

List of Tables

List of Illustrations

Guide

Pages

Modeling and Simulation

New Horizons in Modeling and Simulation for Social Epidemiology and Public Health

List of Contributors

Foreword

References

Acknowledgements

List of Figures

List of Tables

1 A Primer on the Social Determinants of Health

1.1 Introduction

1.2 The Health Olympics: Winners and Losers

1.3 What are the Social Determinants of Health?

1.4 The 3 P's (people, places, and policies) Population Health Triad

1.5 Conventional Approaches to Studying the Social Determinants of Health

1.6 Novel Approaches to Strengthen Causal Inference in Studying the Social Determinants of Health

1.7 What Do We Know About the Social Determinants of Health?

1.8 How Addressing the Social Determinants of Health Could Change Lives

References

2 Rationale for New Modeling and Simulation Tools : Agent‐Based Modeling and Microsimulation

2.1 Advantages of Systems Science Approaches over Conventional Approaches

2.2 Specific Advantages of Agent‐Based Modeling and Microsimulation Modeling. Agent‐Based Modeling

Microsimulation Models

Other Complex Systems Modeling Tools

2.3 Comparison of Agent‐Based and Microsimulation Models

2.4 Why ABM and MSM are Useful for Studying the Social Determinants of Health

2.5 Structure of this Book

References

3 Overview of Current Concepts and Process for Agent‐Based Modeling

3.1 The Components of an Agent‐Based Model: Key Terms

3.2 Steps in Designing and Deploying an Agent‐Based Model

3.3 History of ABM Application and Categories of ABM Usage

References

4 Agent‐Based Modeling in the Social Sciences

4.1 Introduction

4.2 Segregation

4.3 Power Laws

4.4 The Anasazi

4.5 Conclusions

References

Notes

5 Agent‐Based Modeling in Public Health

5.1 Introduction

5.2 Scale of ABM Usage in Public Health

5.3 Example Models: Infectious Disease

Geography

Behavior

5.4 Example Models: Obesity

5.5 Example Models: Tobacco Control

5.6 Conclusions

References

Note

6 Section Summary

6.1 Past Use of ABM for Public Policy Translation

6.2 Bridging Gaps to Advance Agent‐Based Modeling of Social Determinants of Health

Data and Data Usage

Theories of Individual Behavior

Training

References

Note

7 Concepts and Methods for Microsimulation Modeling in the Social Sciences

7.1 Introduction

7.2 Methodological Choices

Static Models

Incorporating the Behavioral Dimension

Incorporating the Time Dimension

Incorporating the Spatial Dimension

Incorporating the Macrodimension

7.3 Population Scope

7.4 Policy Scope

7.5 Building a Microsimulation Model

Input Data Collection and Preparation

Including the Policy Rules

Changing the Population Structure

Integrating Macroaggregates and Spatial Breakdowns

Deriving Output Data

Validation and Calibration

7.6 Applications for Policy Making: Illustrations in the Domain of Health

Microsimulation Models in the Domain of Health

Examples of Applications

7.7 Conclusions

References

8 Empirical Evidence Using Microsimulation Models in the Social Sciences

8.1 Introduction

8.2 Microsimulation and Economics

The Social Impact of Tax and Benefit Policies

First Round Effects on Income Distribution, Public Budget, and Work Incentives

Redistributive Effects of Tax–Benefit Policies

The Importance of the Tax–Benefit Design

The Economic Downturn: An Opportunity for New Analysis

Beyond Disposable Income: Modeling In‐kind Benefits and Indirect Taxes

8.3 Microsimulation and the Prediction of Behavioral Changes

Labor Supply Models

8.4 Beyond Economics: Microsimulation and Other Social Sciences. Microsimulation and Demography

Applications

8.5 Microsimulation and Geography. Spatial Models

Micro Data Generation: Synthetic Reconstruction Versus Reweighting

Applications

8.6 Microsimulation and Transports. Characterization of Space, Mode and Time

Travel Demand, Route Choice and Network Performance

Applications

8.7 Microsimulation and Environmental Sciences. Scope and Spatial Disaggregation

Modeling Pollution and Natural Resources

The Valuation of Nonmarket Public Goods and Benefit Transfers

Socioeconomic and Environmental Interactions

Applications

8.8 Conclusions

References

Note

9 Applications of Microsimulation Models to the Social Determinants of Health and Public Health: A Systematic Review of the Literature

9.1 Overview

9.2 Direct Empirical Applications to the Study of the Social Determinants of Health

9.3 Other Empirical Applications of Microsimulation Models to Medicine and Public Health. Health Care Policy Models

Disease Microsimulation Models

Health Behavior‐Related Policy

9.4 Chapter Summary

References

10 Section Summary

10.1 Summary of Previous Chapters

10.2 Direct Public Policy Relevance of Microsimulation

10.3 Bridging Gaps to Advance Microsimulation Modeling of the Social Determinants of Health

References

11 Future Directions

11.1 Avenues for Future Research

11.2 Conceptual Model and Empirical Examples of Integration of ABM and MSM

11.3 Facilitators and Constraints in the Continued Emergence of Modeling and Simulation of the Social Determinants of Health

11.4 Implications for Public Health

References

Index. a

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The HiAP approach has been increasingly adopted in jurisdictions around the world. For example, the Department of Housing and Urban Development (HUD) in the United States has embraced a HiAP approach and is collaborating with the U.S. Department of Health and Human Services (HHS) to ensure the integration of the elderly and disabled into the community via housing and human service agencies to enable them to live as long and as healthily as possible (Bostic et al. 2012). HUD further encourages applicants to regional planning and neighborhood initiative grants to incorporate health metrics into their baseline assessments of neighborhoods and asks them to indicate how they will support regional planning efforts that consider public health impacts (Bostic et al. 2012). Moreover, to attain objectives on the social determinants of health, the HiAP approach has been encouraged by Healthy People 2020 (2010), the U.S. Centers for Disease Control and Prevention initiative that establishes national goals and objectives for policy, programs, and activities to address the major health challenges facing our country today. The Secretary's Advisory Committee on Healthy People Objectives for 2020 (Office of Disease Prevention and Health Promotion 2010) has further advised that all federal agencies (e.g. the Departments of Education, Transportation, and HUD) should be required to include Healthy People in their strategic plans.

In 2010, the US state of California created a HiAP Task Force, with representation of 19 state agencies, offices, and departments. Employing a HiAP framework, this statewide effort brought policymakers together to identify and recommend programs, policies, and strategies to improve health, including multiagency initiatives addressing transportation, housing, affordable healthy foods, safe neighborhoods, and green spaces. Additional recommendations included the development of health criteria in the discretionary funding review process and incorporating health issues into statewide data collection and survey efforts (Health in All Policies Task Force 2010).

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