Predicting population extinction or disease outbreaks with stochastic models

Q3 Mathematics Letters in Biomathematics Pub Date : 2017-01-01 DOI:10.1080/23737867.2016.1264870
L. Allen, S. Jang, L. Roeger
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引用次数: 7

Abstract

Models of exponential growth, logistic growth and epidemics are common applications in undergraduate differential equation courses. The corresponding stochastic models are not part of these courses, although when population sizes are small their behaviour is often more realistic and distinctly different from deterministic models. For example, the randomness associated with births and deaths may lead to population extinction even in an exponentially growing population. Some background in continuous-time Markov chains and applications to populations, epidemics and cancer are presented with a goal to introduce this topic into the undergraduate mathematics curriculum that will encourage further investigation into problems on conservation, infectious diseases and cancer therapy. MATLAB programs for graphing sample paths of stochastic models are provided in the Appendix.
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用随机模型预测种群灭绝或疾病爆发
指数增长模型、逻辑增长模型和流行病模型是本科微分方程课程中常见的应用。相应的随机模型不是这些课程的一部分,尽管当人口规模较小时,它们的行为通常更现实,与确定性模型明显不同。例如,即使在指数增长的人口中,与出生和死亡相关的随机性也可能导致人口灭绝。本文介绍了连续时间马尔可夫链的一些背景知识以及在人口、流行病和癌症方面的应用,目的是将这一主题引入本科数学课程,从而鼓励对守恒、传染病和癌症治疗问题的进一步研究。在附录中提供了绘制随机模型样本路径的MATLAB程序。
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
Letters in Biomathematics
Letters in Biomathematics Mathematics-Statistics and Probability
CiteScore
2.00
自引率
0.00%
发文量
0
审稿时长
14 weeks
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