Agent-Based Modeling in Public Health: Current Applications and Future Directions.

Agent-Based Modeling in Public Health: Current Applications and Future Directions.
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DOI:
10.1146/annurev-publhealth-040617-014317
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发表时间:
2018-04-01
影响因子:
20.8
通讯作者:
Keyes KM
Keyes KM
中科院分区:
医学1区
文献类型:
--
作者:
Tracy M;Cerdá M;Keyes KM

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基于Agent的建模是一种计算方法,其中具有指定特征集的Agent根据预定义的规则彼此交互并与其环境交互。我们回顾了公共卫生中采用基于代理的建模的关键领域,包括传染性和非传染性疾病,健康行为和社会流行病学。我们还描述了这种方法的主要优势和局限性的问题与公共卫生相关性。最后,我们描述了方法和实质性的未来方向,我们相信这将提高基于代理的公共卫生建模的价值。特别是,模型验证的进步,与其他因果建模程序的比较,以及模型的扩展,以更系统地考虑共病和联合影响,将提高这种方法的效用,为公共卫生研究,实践和政策提供信息。
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.
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