Miller Joel C
Harvard School of Public Health, Boston, MA 02215, USA.
J Math Biol. 2011 Mar;62(3):349-58. doi: 10.1007/s00285-010-0337-9. Epub 2010 Mar 23.
Recent work by Volz (J Math Biol 56:293-310, 2008) has shown how to calculate the growth and eventual decay of an SIR epidemic on a static random network, assuming infection and recovery each happen at constant rates. This calculation allows us to account for effects due to heterogeneity and finiteness of degree that are neglected in the standard mass-action SIR equations. In this note we offer an alternate derivation which arrives at a simpler-though equivalent-system of governing equations to that of Volz. This new derivation is more closely connected to the underlying physical processes, and the resulting equations are of comparable complexity to the mass-action SIR equations. We further show that earlier derivations of the final size of epidemics on networks can be reproduced using the same approach, thereby providing a common framework for calculating both the dynamics and the final size of an epidemic spreading on a random network. Under appropriate assumptions these equations reduce to the standard SIR equations, and we are able to estimate the magnitude of the error introduced by assuming the SIR equations.
沃尔兹最近的研究(《数学生物学杂志》56:293 - 310,2008年)表明,在假设感染和恢复均以恒定速率发生的情况下,如何计算静态随机网络上SIR传染病的增长及最终衰减情况。这种计算使我们能够考虑到标准质量作用SIR方程中被忽略的度的异质性和有限性所带来的影响。在本笔记中,我们给出了一种替代推导方法,得出了一个与沃尔兹的方程组虽等价但更简单的控制方程组。这种新的推导与潜在的物理过程联系更为紧密,所得方程的复杂性与质量作用SIR方程相当。我们进一步表明,使用相同的方法可以重现早期关于网络上传染病最终规模的推导,从而为计算随机网络上传染病的动态变化和最终规模提供了一个通用框架。在适当的假设下,这些方程可简化为标准的SIR方程,并且我们能够估计因假设SIR方程而引入的误差大小。