基于agent的sir微分方程的推导

M. Bicher, N. Popper
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引用次数: 6

摘要

由于计算资源呈指数级增长,基于个体的模型在流行病学家中越来越受欢迎。受SIR(易感-感染-恢复)流行病的启发,可以创建非常复杂和灵活的疾病模型和疫苗策略,接受风险,也许无法解释和不可预测的混乱群体行为可能会扭曲结果。对这些微观模型进行预防性理论分析仍然非常困难。基于扩散近似的思想,提出了一种计算简单的预定义的基于agent的SIR模型的均值的方法,使其渐近地满足Kermack和McKendrick的经典SIR微分方程。这种技术可以推广到基于智能体的模型的分析,并有助于开发混合模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agent-Based Derivation of the SIR-Differential Equations
Due to exponentially increasing computational resources, individual-based models are getting more and more popular among epidemiologists. Inspired by SIR (Susceptible-Infected-Recovered) epidemics very complex and flexible models for diseases and vaccine strategies can be created accepting the risk, that maybe unexplained and unpredictable chaotic group-behavior could distort the results. Preventive theoretical analysis of these microscopic models is still very difficult. Based on the idea of diffusion approximation a technique is presented, how the mean value of a simple predefined agent-based SIR model can be calculated to asymptotically satisfy the classic SIR differential equations by Kermack and McKendrick. This technique can be generalized to contribute to the analysis of agent-based models and can help developing hybrid models.
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