Key Epidemic Parameters of the SIRV-Model Determined from Past COVID-19 Mutant Waves
Monitored infection and vaccination rates during past past Corona waves are used to infer a posteriori two key parameter of the SIRV-epidemic model, namely the real time variation of the (i) ratio of recovery to infection rate and (ii) ratio of vaccination to infection rate. We demonstrate that using the classical SIR model the ratio between recovery and infection rates tends to overestimate the true ratio, that is of relevance in predicting the dynamics of an epidemics in the presence of vaccinations..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Preprints.org - (2023) vom: 06. Mai Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Schlickeiser, Reinhard [VerfasserIn] |
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| doi: |
10.20944/preprints202303.0515.v1 |
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| PPN (Katalog-ID): |
preprintsorg039111725 |
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| 245 | 1 | 0 | |a Key Epidemic Parameters of the SIRV-Model Determined from Past COVID-19 Mutant Waves |
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| 520 | |a Monitored infection and vaccination rates during past past Corona waves are used to infer a posteriori two key parameter of the SIRV-epidemic model, namely the real time variation of the (i) ratio of recovery to infection rate and (ii) ratio of vaccination to infection rate. We demonstrate that using the classical SIR model the ratio between recovery and infection rates tends to overestimate the true ratio, that is of relevance in predicting the dynamics of an epidemics in the presence of vaccinations. | ||
| 700 | 1 | |a Kröger, Martin |0 (orcid)0000-0003-1402-6714 |4 aut | |
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