{"title":"Equivalence of mass action and Poisson network SIR epidemic models","authors":"Grzegorz A. Rempala","doi":"10.55630/j.biomath.2023.11.237","DOIUrl":null,"url":null,"abstract":"This brief note highlights a largely overlooked similarity between the SIR ordinary differential equations used for epidemics on the configuration model of a Poisson network and the classical mass-action SIR equations introduced nearly a century ago by Kermack and McKendrick. We demonstrate that the decline pattern in susceptibles is identical for both models. This equivalence carries practical implications: the susceptibles decay curve, often referred to as the epidemic or incidence curve, is frequently used in empirical studies to forecast epidemic dynamics. Although the curves for susceptibles align perfectly, those for infections do differ. Yet, the infection curves tend to converge and become almost indistinguishable in high-degree networks. In summary, our analysis suggests that under many practical scenarios, it's acceptable to use the classical SIR model as a close approximation to the Poisson SIR network model.","PeriodicalId":52247,"journal":{"name":"Biomath","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomath","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55630/j.biomath.2023.11.237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
This brief note highlights a largely overlooked similarity between the SIR ordinary differential equations used for epidemics on the configuration model of a Poisson network and the classical mass-action SIR equations introduced nearly a century ago by Kermack and McKendrick. We demonstrate that the decline pattern in susceptibles is identical for both models. This equivalence carries practical implications: the susceptibles decay curve, often referred to as the epidemic or incidence curve, is frequently used in empirical studies to forecast epidemic dynamics. Although the curves for susceptibles align perfectly, those for infections do differ. Yet, the infection curves tend to converge and become almost indistinguishable in high-degree networks. In summary, our analysis suggests that under many practical scenarios, it's acceptable to use the classical SIR model as a close approximation to the Poisson SIR network model.
这篇简短的文章强调了在泊松网络配置模型上用于流行病的 SIR 常微分方程与近一个世纪前由 Kermack 和 McKendrick 引入的经典质量作用 SIR 方程之间一个被忽视的相似性。我们证明,两种模型的易感人群下降模式是相同的。这种等效性具有实际意义:易感者衰减曲线通常被称为流行病或发病率曲线,在实证研究中经常被用来预测流行病的动态。虽然易感者的曲线完全一致,但感染者的曲线确实不同。然而,感染曲线趋于收敛,在高阶网络中几乎无法区分。总之,我们的分析表明,在许多实际情况下,使用经典 SIR 模型作为泊松 SIR 网络模型的近似值是可以接受的。