On an interval prediction of COVID-19 development based on a SEIR epidemic model
© 2021 Elsevier Ltd. All rights reserved.
| Veröffentlicht in: | Annual reviews in control. - 1998. - 51(2021) vom: 15., Seite 477-487 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2021
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| Zugriff auf das übergeordnete Werk: | Annual reviews in control |
| Schlagworte: | Journal Article COVID-19 Epidemic model Interval predictor Parameter Identification |
| Zusammenfassung: | © 2021 Elsevier Ltd. All rights reserved. In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model's improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identified model is then applied to predict the SARS-CoV-2 virus propagation under various conditions of confinement. For this purpose, an interval predictor is designed, allowing variations and uncertainties in the model parameters to be taken into account. The code and the utilized data are available on Github |
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| Beschreibung: | Date Revised 08.09.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1367-5788 |
| DOI: | 10.1016/j.arcontrol.2021.01.006 |