Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Rensselaer, New York 12144, USA; email:
Department of Emergency Medicine, University of California, Davis, Sacramento, California 95616, USA; email:
Annu Rev Public Health. 2018 Apr 1;39:77-94. doi: 10.1146/annurev-publhealth-040617-014317. Epub 2018 Jan 12.
Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.
基于代理的建模是一种计算方法,其中具有特定特征集的代理根据预定义的规则相互作用并与环境相互作用。我们回顾了基于代理的建模在公共卫生领域的关键应用领域,包括传染病和非传染性疾病、健康行为和社会流行病学。我们还描述了这种方法对于具有公共卫生相关性的问题的主要优势和局限性。最后,我们描述了我们认为将增强基于代理的建模在公共卫生方面的价值的方法学和实质性的未来方向。特别是,模型验证方面的进展、与其他因果建模过程的比较以及扩展模型以更系统地考虑合并症和共同影响,将提高这种方法在为公共卫生研究、实践和政策提供信息方面的实用性。