Computing the extinction path for epidemic models

IF 1.8 4区 数学 Q2 BIOLOGY
Damian Clancy, John J.H. Stewart
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引用次数: 0

Abstract

In infectious disease modelling, the expected time from endemicity to extinction (of infection) may be analysed via WKB approximation, a method with origins in mathematical physics. The method is very general, but its uptake to date may have been limited by the practical difficulties of implementation. It is necessary to compute a trajectory of a (high dimensional) dynamical system, the ‘extinction path’, and this trajectory is maximally sensitive to small perturbations, making numerical computation challenging. The purpose of this paper is to make this methodology more accessible. Our method to achieve this is to present four computational algorithms, with associated Matlab code, together with discussion of various ways in which the algorithms may be tuned to achieve satisfactory convergence. One of the four algorithms is standard in this context, although we are able to somewhat enhance previously available code; the use of the three other algorithms in this context is novel. We illustrate our methods using three standard infectious disease models. Our results demonstrate that for each such model, our algorithms are able to improve upon previously available results.
计算流行病模型的灭绝路径。
在传染病建模中,从流行到(感染)灭绝的预期时间可以通过WKB近似来分析,这是一种起源于数学物理的方法。该方法是非常普遍的,但迄今为止,它的采用可能由于执行的实际困难而受到限制。有必要计算(高维)动力系统的轨迹,即“消光路径”,并且该轨迹对小扰动最敏感,这使得数值计算具有挑战性。本文的目的是使这种方法更容易理解。我们实现这一目标的方法是提出四种计算算法,以及相关的Matlab代码,并讨论了算法可以调整以实现令人满意的收敛的各种方法。在这种情况下,四种算法中的一种是标准的,尽管我们能够在一定程度上增强以前可用的代码;在这种情况下使用其他三种算法是新颖的。我们用三个标准传染病模型来说明我们的方法。我们的结果表明,对于每个这样的模型,我们的算法都能够改进先前可用的结果。
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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来源期刊
Mathematical Biosciences
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
审稿时长
18 days
期刊介绍: Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
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