Analysing an epidemic–economic model in the presence of novel corona virus infection: capital stabilization, media effect, and the role of vaccine

Abstract

The pandemic being a health issue at its core is a multifaceted crisis encompassing both economic and epidemic factors in a twisted tale of challenges. In counteraction, we have proposed a combined epidemic–economic model that analyses system dynamics arising in the presence of an infectious disease (SARS-2-COVID-19 in our case). Dynamical analysis of the system has been performed in context to the equilibria along with local and global stability analysis of the system simultaneously visualizing the effect on capital stabilization. The global stability analysis has been performed using graph-theoretic method. Curve-Fit has been performed for the system using optimization algorithm. The relation between all the parameters and variables involved in the model has been explored by calculating sensitivity indices which gives us the proportion that a relative change in a parameter brings to the relative change in a variable. Our findings reveal that (1) Vaccination instigates economic growth (with evidence of data obtained for 24 countries). (2) Complete vaccination leads to a considerable reduction in all infections (reduction up to 90%, as per current CDC study). (3) Excessive exposure to media can facilitate spike in infections. (4) Parameter sensitivity analysis can be of immense help in policy formation.

Dynamics of the COVID-19 pandemic: nonlinear approaches on the modelling, prediction and control

“…The dynamics of the spread of an infectious disease together with the economic challenges faced by the country are examined through a combined epidemic-economic model proposed by Karim et al [1].…”

“…This special issue is a compilation of original research articles that address the dynamics and applications of COVID-19 through nonlinear dynamics. The articles are organized in five sections, comprising mathematical modeling and epidemics [1][2][3][4][5][6][7], the dynamics of several waves and transmission [8][9][10][11][12][13][14][15][16][17], neural network and deep learning related to COVID-19 [18][19][20][21][22][23][24], predictions and estimations related to COVID-19 [25][26][27][28][29][30], and detailed analysis on the pandemic and its applications [31][32][33][34][35].…”

Stability analysis of a non-singular fractional-order covid-19 model with nonlinear incidence and treatment rate

“…Mathematical models in epidemiology are great tools that can help us to understand the transmission dynamics of COVID-19 Ahmad et al (2022), Allegretti et al (2021), Biswas et al (2020), Erturk and Kumar (2020), Gao et al (2020), Kumar et al (2020), Naik et al (2020aNaik et al ( , 2020b, Rajagopal et al (2020), Sene (2020), Kumar and Erturk (2021), Naik et al (2021), Safare et al (2021), Sitthiwirattham et al (2021), Özköse et al (2022), , Karim et al (2022), Kurmi and Chouhan (2022), Pandey et al (2022), Guo and Li (2022), Haq et al (2022), Guo (2022a, 2022b), Pérez and Oluyori (2022), Swati (2022), Joshi et al (2023). It captures all the scenarios in a very compact form and by proper analysis of these models show, for example, (I) how the disease spreads worldwide, (II) how much population is affected, (III) how to constrain COVID-19.…”

Consenso colombiano sobre vacunación en pacientes con enfermedad renal crónica

“…La pandemia de COVID-19 demostró que la vacunación no solo es un pilar de la salud pública, sino que es un eje de la sostenibilidad económica global [5]. La disponibilidad de vacunas es crítica para las poblaciones más vulnerables como lo son los niños, las personas de edad avanzada y las personas con condiciones de enfermedad [6].…”