传染病系统中从宿主内尺度到种群尺度的数学方法

IF 3 3区医学 Q2 INFECTIOUS DISEASES

Epidemics Pub Date : 2023-10-30 DOI:10.1016/j.epidem.2023.100724

James W.G. Doran , Robin N. Thompson , Christian A. Yates , Ruth Bowness

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引用次数: 0

摘要

数学建模者在不同尺度上对传染病动力学进行建模。宿主内模型代表病原体在个体内的传播，而宿主间模型则追踪个体之间的传播。然而，一个尺度上的病原体动态会影响另一个尺度上的病原体动态。这导致了连接宿主内部和宿主之间动态的多尺度模型的发展。在本文中，我们根据PRISMA指南系统地回顾了关于多尺度传染病建模的文献，将先前发表的模型分为五类，管理其方法方法(Garira(2017))，并解释了它们的优点和局限性。我们提供了开发传染病的多尺度模型的入门。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Mathematical methods for scaling from within-host to population-scale in infectious disease systems

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Mathematical methods for scaling from within-host to population-scale in infectious disease systems

Mathematical modellers model infectious disease dynamics at different scales. Within-host models represent the spread of pathogens inside an individual, whilst between-host models track transmission between individuals. However, pathogen dynamics at one scale affect those at another. This has led to the development of multiscale models that connect within-host and between-host dynamics. In this article, we systematically review the literature on multiscale infectious disease modelling according to PRISMA guidelines, dividing previously published models into five categories governing their methodological approaches (Garira (2017)), explaining their benefits and limitations. We provide a primer on developing multiscale models of infectious diseases.

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来源期刊

Epidemics INFECTIOUS DISEASES-

CiteScore

6.00

自引率

7.90%

发文量

审稿时长

140 days

期刊介绍： Epidemics publishes papers on infectious disease dynamics in the broadest sense. Its scope covers both within-host dynamics of infectious agents and dynamics at the population level, particularly the interaction between the two. Areas of emphasis include: spread, transmission, persistence, implications and population dynamics of infectious diseases; population and public health as well as policy aspects of control and prevention; dynamics at the individual level; interaction with the environment, ecology and evolution of infectious diseases, as well as population genetics of infectious agents.