Developing agent-based models of complex health behaviour.

Developing agent-based models of complex health behaviour.
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DOI:
10.1016/j.healthplace.2018.08.022
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发表时间:
2018-11
期刊:
影响因子:
4.8
通讯作者:
Hunter RF
Hunter RF
中科院分区:
医学2区
文献类型:
--
作者:
Badham J;Chattoe-Brown E;Gilbert N;Chalabi Z;Kee F;Hunter RF

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管理非传染性疾病要求决策者采取一种全系统的观点,充分反映人类行为的复杂因果结构。基于主体的建模是一种计算方法,通过模拟系统内实体的行为来理解复杂系统的行为,包括这些个体影响和受其物理和社会环境影响的方式。这种方法的潜在好处已经导致一些呼吁在公共卫生研究中更多地使用。我们讨论了潜在的建模者面临的三个挑战:模型规范,获得所需的数据,并制定良好的做法。我们还提出了步骤,以帮助研究人员,以满足这些挑战,并实现他们的基于代理的模型。ABM是有效的建模嵌入环境中的健康行为。关键挑战是:制定规则,获取过程数据和获得技能。其他学科的经验可用于公共卫生研究。反弹道导弹的潜在好处需要作出必要的努力。
Managing non-communicable diseases requires policy makers to adopt a whole systems perspective that adequately represents the complex causal architecture of human behaviour. Agent-based modelling is a computational method to understand the behaviour of complex systems by simulating the actions of entities within the system, including the way these individuals influence and are influenced by their physical and social environment. The potential benefits of this method have led to several calls for greater use in public health research. We discuss three challenges facing potential modellers: model specification, obtaining required data, and developing good practices. We also present steps to assist researchers to meet these challenges and implement their agent-based model. ABM is effective for modelling health behaviour embedded within the environment. Key challenges are: formulating rules, obtaining process data, and acquiring skills. Experience from other disciplines may be adapted for public health research. The potential benefits of ABM warrant the effort required.
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