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Non-Markovian SIR epidemic spreading model of COVID-19
- We introduce non-Markovian SIR epidemic spreading model inspired by the characteristics of the COVID-19, by considering discrete-and continuous-time versions. The distributions of infection intensity and recovery period may take an arbitrary form. By taking corresponding choice of these functions, it is shown that the model reduces to the classical Markovian case. The epidemic threshold is analytically determined for arbitrary functions of infectivity and recovery and verified numerically. The relevance of the model is shown by modeling the first wave of the epidemic in Italy, Spain and the UK, in the spring, 2020.
Author details: | Lasko BasnarkovORCiD, Igor TomovskiORCiD, Trifce SandevORCiDGND, Ljupčo KocarevGND |
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DOI: | https://doi.org/10.1016/j.chaos.2022.112286 |
ISSN: | 0960-0779 |
ISSN: | 1873-2887 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/35694643 |
Title of parent work (English): | Chaos, solitons & fractals : applications in science and engineering ; an interdisciplinary journal of nonlinear science |
Publisher: | Elsevier |
Place of publishing: | Oxford [u.a.] |
Publication type: | Article |
Language: | English |
Date of first publication: | 2022/07/01 |
Publication year: | 2022 |
Release date: | 2024/01/12 |
Tag: | COVID-19; Epidemic spreading models; Non-Markovian processes; SIR model |
Volume: | 160 |
Article number: | 112286 |
Number of pages: | 8 |
Funding institution: | German Research Foundation (DFG) [ME 1535/12-1]; Faculty of Computer; Science and Engineering, at the Ss. Cyril and Methodius University in; Skopje, Macedonia; German Research Foundation (DFG) |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |
Peer review: | Referiert |