On the use of reactive multiparticle collision dynamics to gather particulate level information from simulations of epidemic models

IF 1.4 4区 物理与天体物理 Q4 MATERIALS SCIENCE, MULTIDISCIPLINARY
AIP Advances Pub Date : 2024-09-09 DOI:10.1063/5.0223361
Zaib Un Nisa Memon, Katrin Rohlf
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Abstract

This paper discusses the application of reactive multiparticle collision (RMPC) dynamics, a particle-based method, to epidemic models. First, we consider a susceptible-infectious-recovered framework to obtain data on contacts of susceptibles with infectious people in a population. It is found that the number of contacts increases and the contact duration decreases with increases in the disease transmission rate and average population speed. Next, we obtain reinfection statistics for a general infectious disease from RMPC simulations of a susceptible-infectious-recovered-susceptible model. Finally, we simulate a susceptible-exposed-infectious-recovered model and gather the exposure, infection, and recovery time for the individuals in the population under consideration. It is worth mentioning that we can collect data in the form of average contact duration, average initial infection time, etc., from RMPC simulations of these models, which is not possible with population-based stochastic models, or deterministic systems. This study provides quantitative insights on the potential of RMPC to simulate epidemic models and motivates future efforts for its application in the field of mathematical epidemiology.
利用反应多粒子碰撞动力学从流行病模型模拟中收集粒子水平信息
本文讨论了反应多粒子碰撞动力学(RMPC)这一基于粒子的方法在流行病模型中的应用。首先,我们考虑了易感-感染-恢复框架,以获取人群中易感者与感染者的接触数据。研究发现,随着疾病传播率和人口平均速度的增加,接触人数会增加,接触持续时间会缩短。接着,我们从易感-感染-康复-易感模型的 RMPC 模拟中获得了一般传染病的再感染统计数据。最后,我们模拟易感-暴露-感染-恢复模型,收集所考虑人群中个体的暴露、感染和恢复时间。值得一提的是,我们可以从这些模型的 RMPC 模拟中收集平均接触时间、平均初始感染时间等数据,而基于种群的随机模型或确定性系统则无法做到这一点。这项研究从数量上揭示了 RMPC 模拟流行病模型的潜力,并激励我们今后在数学流行病学领域应用 RMPC。
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
AIP Advances
AIP Advances NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
2.80
自引率
6.20%
发文量
1233
审稿时长
2-4 weeks
期刊介绍: AIP Advances is an open access journal publishing in all areas of physical sciences—applied, theoretical, and experimental. All published articles are freely available to read, download, and share. The journal prides itself on the belief that all good science is important and relevant. Our inclusive scope and publication standards make it an essential outlet for scientists in the physical sciences. AIP Advances is a community-based journal, with a fast production cycle. The quick publication process and open-access model allows us to quickly distribute new scientific concepts. Our Editors, assisted by peer review, determine whether a manuscript is technically correct and original. After publication, the readership evaluates whether a manuscript is timely, relevant, or significant.
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