Author:
Marinov Tchavdar T.,Marinova Rossitza S.
Abstract
AbstractAn Adaptive Susceptible-Infected-Removed-Vaccinated (A-SIRV) epidemic model with time-dependent transmission and removal rates is constructed for investigating the dynamics of an epidemic disease such as the COVID-19 pandemic. Real data of COVID-19 spread is used for the simultaneous identification of the unknown time-dependent rates and functions participating in the A-SIRV system. The inverse problem is formulated and solved numerically using the Method of Variational Imbedding, which reduces the inverse problem to a problem for minimizing a properly constructed functional for obtaining the sought values. To illustrate and validate the proposed solution approach, the present study used available public data for several countries with diverse population and vaccination dynamics—the World, Israel, The United States of America, and Japan.
Publisher
Springer Science and Business Media LLC
Reference39 articles.
1. WHO. World Health Organization, Novel Coronavirus (2019-nCoV) situation reports. https://www.who.int/ (2020).
2. Callaway, E. The race for coronavirus vaccines: a graphical guide. Nature 580, 576–577. https://doi.org/10.1038/d41586-020-01221-y (2020).
3. Ritchie, H. et al. Coronavirus Pandemic (COVID-19). https://ourworldindata.org/coronavirus (2020).
4. Kermack, W. & McKendrick, A. A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. Ser. A 115, 700–721. https://doi.org/10.1098/rspa.1927.0118 (1927).
5. Ajbar, A., Alqahtani, R. & Boumaza, M. Dynamics of an SIR-based COVID-19 model with linear incidence rate, nonlinear removal rate, and public awareness. Front. Phys. 9, 634251. https://doi.org/10.3389/fphy.2021.634251 (2021).
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献