A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile
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 t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Journal of Biological Dynamics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17513758.2023.2256774 |
| _version_ | 1797331589805375488 |
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| author | Raimund Bürger Gerardo Chowell Ilja Kröker Leidy Yissedt Lara-Díaz |
| author_facet | Raimund Bürger Gerardo Chowell Ilja Kröker Leidy Yissedt Lara-Díaz |
| author_sort | Raimund Bürger |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T07:36:40Z |
| format | Article |
| id | doaj.art-e90dedabeb044c94b6c4b7309fb1c8d7 |
| institution | Directory Open Access Journal |
| issn | 1751-3758 1751-3766 |
| language | English |
| last_indexed | 2024-03-08T07:36:40Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Biological Dynamics |
| spelling | doaj.art-e90dedabeb044c94b6c4b7309fb1c8d72024-02-02T18:51:34ZengTaylor & Francis GroupJournal of Biological Dynamics1751-37581751-37662023-12-0117110.1080/17513758.2023.2256774A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in ChileRaimund Bürger0Gerardo Chowell1Ilja Kröker2Leidy Yissedt Lara-Díaz3CIMA and Departamento de Ingeniería Matemática, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Concepción, ChileSchool of Public Health, Georgia State University, Atlanta, GA, USAStochastic Simulation & Safety Research for Hydrosystems (LS3), Institute for Modelling Hydraulic and Environmental Systems (IWS), Universität Stuttgart, Stuttgart, GermanyDepartamento de Matemática, Física y Estadística, Facultad de Ciencias Básicas, Universidad Católica del Maule, Talca, ChileA 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.https://www.tandfonline.com/doi/10.1080/17513758.2023.2256774COVID-19 modeldynamical quarantinesparameter estimationidentifiability of parametersbasic reproduction numbersimulated annealing |
| spellingShingle | Raimund Bürger Gerardo Chowell Ilja Kröker Leidy Yissedt Lara-Díaz A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile Journal of Biological Dynamics COVID-19 model dynamical quarantines parameter estimation identifiability of parameters basic reproduction number simulated annealing |
| title | A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile |
| title_full | A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile |
| title_fullStr | A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile |
| title_full_unstemmed | A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile |
| title_short | A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile |
| title_sort | computational approach to identifiability analysis for a model of the propagation and control of covid 19 in chile |
| topic | COVID-19 model dynamical quarantines parameter estimation identifiability of parameters basic reproduction number simulated annealing |
| url | https://www.tandfonline.com/doi/10.1080/17513758.2023.2256774 |
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