Schlickeiser, R.; Kröger, M. Key Epidemic Parameters of the SIRV Model Determined from Past COVID-19 Mutant Waves. COVID 2023, 3, 592–600, doi:10.3390/covid3040042.
Schlickeiser, R.; Kröger, M. Key Epidemic Parameters of the SIRV Model Determined from Past COVID-19 Mutant Waves. COVID 2023, 3, 592–600, doi:10.3390/covid3040042.
Cite as:
Schlickeiser, R.; Kröger, M. Key Epidemic Parameters of the SIRV Model Determined from Past COVID-19 Mutant Waves. COVID 2023, 3, 592–600, doi:10.3390/covid3040042.
Schlickeiser, R.; Kröger, M. Key Epidemic Parameters of the SIRV Model Determined from Past COVID-19 Mutant Waves. COVID 2023, 3, 592–600, doi:10.3390/covid3040042.
Abstract
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.
Medicine and Pharmacology, Pulmonary and Respiratory Medicine
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
