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Quantitative Biology > Quantitative Methods

arXiv:2503.03131 (q-bio)
[Submitted on 5 Mar 2025 (v1) , last revised 4 Jul 2025 (this version, v2)]

Title: Spatially-Structured Models of Viral Dynamics: A Scoping Review

Title: 空间结构化的病毒动力学模型:范围综述

Authors:Thomas Williams, James M. McCaw, James M. Osborne
Abstract: There is growing recognition in both the experimental and modelling literature of the importance of spatial structure to the dynamics of viral infections in tissues. Aided by the evolution of computing power and motivated by recent biological insights, there has been an explosion of new, spatially-explicit models for within-host viral dynamics in recent years. This development has only been accelerated in the wake of the COVID-19 pandemic. Spatially-structured models offer improved biological realism and can account for dynamics which cannot be well-described by conventional, mean-field approaches. However, despite their growing popularity, spatially-structured models of viral dynamics are underused in biological applications. One major obstacle to the wider application of such models is the huge variety in approaches taken, with little consensus as to which features should be included and how they should be implemented for a given biological context. Previous reviews of the field have focused on specific modelling frameworks or on models for particular viral species. Here, we instead apply a scoping review approach to the literature of spatially-structured viral dynamics models as a whole to provide an exhaustive update of the state of the field. Our analysis is structured along two axes, methodology and viral species, in order to examine the breadth of techniques used and the requirements of different biological applications. We then discuss the contributions of mathematical and computational modelling to our understanding of key spatially-structured aspects of viral dynamics, and suggest key themes for future model development to improve robustness and biological utility.
Abstract: 在实验和建模文献中,人们对空间结构在组织中病毒感染动力学中的重要性有了越来越多的认识。 在计算能力不断进步的推动下,并受到近期生物学见解的启发,近年来出现了大量新的、空间明确的宿主内病毒动力学模型。 在新冠疫情爆发后,这一发展速度进一步加快。 空间结构模型提供了更好的生物学现实性,并可以解释传统平均场方法难以描述的动力学。 然而,尽管这些模型日益流行,它们在生物学应用中仍使用不足。 这类模型更广泛应用的主要障碍在于方法的多样性,对于哪些特征应被包含以及如何为特定的生物学背景实施这些特征,尚缺乏共识。 该领域的以往综述主要集中在特定的建模框架或特定病毒种类的模型上。 在此,我们采用范围审查的方法对整个空间结构病毒动力学模型文献进行综述,以全面更新该领域的发展状况。 我们的分析沿着两个轴线展开:方法学和病毒种类,以考察所使用技术的广度以及不同生物学应用的要求。 然后,我们讨论数学和计算建模在理解病毒动力学的关键空间结构方面所做的贡献,并提出未来模型开发的关键主题,以提高模型的稳健性和生物学实用性。
Subjects: Quantitative Methods (q-bio.QM)
Cite as: arXiv:2503.03131 [q-bio.QM]
  (or arXiv:2503.03131v2 [q-bio.QM] for this version)
  https://doi.org/10.48550/arXiv.2503.03131
arXiv-issued DOI via DataCite

Submission history

From: Thomas Williams [view email]
[v1] Wed, 5 Mar 2025 03:01:00 UTC (2,118 KB)
[v2] Fri, 4 Jul 2025 02:24:07 UTC (3,885 KB)
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