Promoting the adoption of agent-based modelling for synergistic interventions and decision-making during pandemic outbreaks

P. Kyriakidis, Dimitris Kavroudakis, Philip Fayad, Stylianos Hadjipetrou, G. Leventis, A. Papakonstantinou
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Abstract

Abstract. Geography has long sought to explain spatial relationships between social and physical processes, including the spread of infectious diseases, within the context of modelling human-environment interactions. The spread of the recent COVID-19 pandemic, and its devastating effects on human activity and welfare, represent but examples of such complex human-environment interactions. In this paper, we discuss the value of agent-based models for simulating the spread of the COVID-19 virus to support decision-making with regards to non-pharmaceutical interventions, e.g., lock-down. We also develop a prototype agent-based model using a minimal set of rules regarding patterns of human mobility within a hypothetical town, and couple that with an epidemiological model of infectious disease spread. The coupled model is used to: (a) create synthetic trajectories corresponding to daily and weekly activities postulated between a set of predefined points of interest (e.g., home, work), and (b) simulate new infections at contact points and their subsequent effects on the spread of the disease. We finally use the model simulations as a means of evaluating decisions regarding the number and type of activities to be limited during a planned lockdown in a COVID-19 pandemic context.
促进采用基于主体的模型,以便在大流行病爆发期间进行协同干预和决策
摘要地理学长期以来一直试图在模拟人与环境相互作用的背景下解释社会过程和物理过程之间的空间关系,包括传染病的传播。最近COVID-19大流行的传播及其对人类活动和福祉的破坏性影响就是这种复杂的人与环境相互作用的例子。在本文中,我们讨论了基于智能体的模型在模拟COVID-19病毒传播方面的价值,以支持有关非药物干预措施(例如封锁)的决策。我们还开发了一个基于主体的原型模型,该模型使用了关于假设城镇内人类流动模式的最小规则集,并将其与传染病传播的流行病学模型相结合。耦合模型用于:(a)创建与一组预定义的兴趣点(例如,家庭、工作)之间假定的每日和每周活动相对应的合成轨迹,以及(b)模拟接触点的新感染及其对疾病传播的后续影响。最后,我们使用模型模拟作为评估在COVID-19大流行背景下计划封锁期间要限制的活动数量和类型的决策的手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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