A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile.

IF 1.8 4区 数学 Q3 ECOLOGY Journal of Biological Dynamics Pub Date : 2023-12-01 DOI:10.1080/17513758.2023.2256774
Raimund Bürger, Gerardo Chowell, Ilja Kröker, Leidy Yissedt Lara-Díaz
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Abstract

A computational approach is adapted to analyze the parameter identifiability of a compartmental model. The model is intended to describe the progression of the COVID-19 pandemic in Chile during the initial phase in early 2020 when government declared quarantine measures. The computational approach to analyze the structural and practical identifiability is applied in two parts, one for synthetic data and another for some Chilean regional data. The first part defines the identifiable parameter sets when these recover the true parameters used to create the synthetic data. The second part compares the results derived from synthetic data, estimating the identifiable parameter sets from regional Chilean epidemic data. Experiments provide evidence of the loss of identifiability if some initial conditions are estimated, the period of time used to fit is before the peak, and if a significant proportion of the population is involved in quarantine periods.

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新冠肺炎在智利传播和控制模型的可识别性分析的计算方法。
计算方法适用于分析隔室模型的参数可识别性。该模型旨在描述2020年初新冠肺炎疫情在智利的发展,当时政府宣布了隔离措施。分析结构和实际可识别性的计算方法分为两部分,一部分用于合成数据,另一部分用于智利的一些区域数据。第一部分定义了可识别的参数集,当这些参数集恢复用于创建合成数据的真实参数时。第二部分比较了合成数据的结果,估计了智利地区疫情数据中的可识别参数集。如果估计了一些初始条件,用于拟合的时间段在峰值之前,并且如果很大一部分人群参与了隔离期,则实验提供了可识别性丧失的证据。
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来源期刊
Journal of Biological Dynamics
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
审稿时长
33 weeks
期刊介绍: Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.
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