Dept. ESPM, UC Berkeley, CA 94720-3114, USA; School of Mathematical Sciences, University of KwaZulu-Natal, Private Bag X54001, Durban 4000, South Africa; Numerus, 850 Iron Point Rd., Folsom, CA 95630, USA.
Numerus, 850 Iron Point Rd., Folsom, CA 95630, USA; Computer Science Dept., Oberlin College, Oberlin, OH 44074, USA.
Epidemics. 2018 Dec;25:9-19. doi: 10.1016/j.epidem.2018.06.001. Epub 2018 Jul 13.
Epidemiological models are dominated by compartmental models, of which SIR formulations are the most commonly used. These formulations can be continuous or discrete (in either the state-variable values or time), deterministic or stochastic, or spatially homogeneous or heterogeneous, the latter often embracing a network formulation. Here we review the continuous and discrete deterministic and discrete stochastic formulations of the SIR dynamical systems models, and we outline how they can be easily and rapidly constructed using Numerus Model Builder, a graphically-driven coding platform. We also demonstrate how to extend these models to a metapopulation setting using NMB network and mapping tools.
流行病学模型主要由房室模型主导，其中 SIR 公式是最常用的。这些公式可以是连续的或离散的（无论是状态变量值还是时间）、确定性的或随机的，或者空间均匀的或不均匀的，后者通常包含网络公式。在这里，我们回顾了 SIR 动力系统模型的连续和离散确定性和离散随机公式，并概述了如何使用 Numerus Model Builder（一个图形驱动的编码平台）轻松快速地构建它们。我们还演示了如何使用 NMB 网络和映射工具将这些模型扩展到集合种群设置。
