The increase in readily available computational power raises the possibility that direct agent-based modeling can play a key role in the analysis of epidemiological population dynamics. Specifically, the objective of this work is to develop a robust agent-based computational framework to investigate the emergent structure of Susceptible-Infected-Removed/Recovered (SIR)-type populations and variants thereof, on a global planetary scale. To accomplish this objective, we develop a planet-wide model based on interaction between discrete entities (agents), where each agent on the surface of the planet is initially uninfected. Infections are then seeded on the planet in localized regions. Contracting an infection depends on the characteristics of each agent—i.e. their susceptibility and contact with the seeded, infected agents. Agent mobility on the planet is dictated by social policies, for example such as “shelter in place”, “complete lockdown”, etc. The global population is then allowed to evolve according to infected states of agents, over many time periods, leading to an SIR population. The work illustrates the construction of the computational framework and the relatively straightforward application with direct, non-phenomenological, input data. Numerical examples are provided to illustrate the model construction and the results of such an approach.

中文翻译：

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基于代理的计算框架，用于模拟 X 星球上的全球流行病和社会反应

随时可用的计算能力的增加提高了基于代理的直接建模在流行病学人口动态分析中发挥关键作用的可能性。具体来说，这项工作的目的是开发一个强大的基于代理的计算框架，以在全球行星范围内研究易感感染移除/恢复 (SIR) 型种群及其变体的紧急结构。为了实现这一目标，我们开发了一个基于离散实体（代理）之间相互作用的全球模型，其中行星表面上的每个代理最初都没有受到感染。然后感染在地球上的局部区域播种。感染感染取决于每种病原体的特性——即它们的易感性以及与播种、受感染病原体的接触。地球上的特工流动性由社会政策决定，例如“就地避难”、“完全封锁”等。然后允许全球人口根据特工的感染状态在多个时间段内进化，从而导致一个 SIR 人口。这项工作说明了计算框架的构建以及直接的、非现象学的输入数据的相对简单的应用。提供了数值示例来说明模型构建和这种方法的结果。这项工作说明了计算框架的构建以及直接的、非现象学的输入数据的相对简单的应用。提供了数值示例来说明模型构建和这种方法的结果。这项工作说明了计算框架的构建以及直接的、非现象学的输入数据的相对简单的应用。提供了数值示例来说明模型构建和这种方法的结果。