Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/14687
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Basnarkov, Lasko | en_US |
dc.contributor.author | Igor Tomovski | en_US |
dc.contributor.author | Trifce Sandev | en_US |
dc.contributor.author | Kocarev, LJupcho | en_US |
dc.date.accessioned | 2021-09-14T11:43:50Z | - |
dc.date.available | 2021-09-14T11:43:50Z | - |
dc.date.issued | 2021-07-15 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/14687 | - |
dc.description.abstract | We introduce non-Markovian SIR epidemic spreading model inspired by the characteristics of the COVID-19, by considering discrete- and continuous-time versions. The incubation period, delayed infectiousness and the distribution of the recovery period are modeled with general functions. 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, in the spring, 2020. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Arxiv repository | en_US |
dc.subject | Epidemic sreading | en_US |
dc.subject | Non-Markovian models | en_US |
dc.subject | SIR model | en_US |
dc.title | Non-Markovian SIR epidemic spreading model | en_US |
dc.type | Preprint | en_US |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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File | Description | Size | Format | |
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Non_Markovian_SIR_epidemic_spreading_model.pdf | 198.46 kB | Adobe PDF | View/Open |
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