Growth Recovery and COVID-19 Pandemic Model: Comparative Analysis for Selected Emerging Economies

Mathematics. 2022. Vol. 10. No. 19. Article 3654.

Akaev A., Zvyagintsev A., Sarygulov A., Devezas T., Tick A., Yuri Ichkitidze

The outburst of the COVID-19 pandemic and its rapid spread throughout the world in
2020 shed a new light on mathematic models describing the nature of epidemics. However, as
the pandemic shocked economies to a much greater extent than earlier epidemics, the recovery
potential of economies was emphasized and its inclusion in epidemic models is becoming more
important. The present paper deals with the issues of modeling the recovery of economic systems
that have undergone severe medical shocks, such as COVID-19. The proposed mathematical model
considers the close relationship between the dynamics of pandemics and economic development.
This distinguishes it from purely “medical” models, which are used exclusively to study the
dynamics of the spread of the COVID-19 pandemic. Unlike standard SIR models, the present
approach involves the introduction of the “vaccine” equation to the SIR model and introduces
correction components that include the possibility of re-infection and other nuances such as the
number of people at risk of infection (not sick with COVID but not vaccinated); sick with COVID;
recovered; fully vaccinated (two doses) citizens; the rate of COVID infection; the rate of recovery
of infected individuals; the vaccination coefficients, respectively, for those who have not been ill
and recovered from COVID; the coefficient of revaccination; the COVID re-infection rate; and the
population fluctuation coefficient, which takes into account the effect of population change as a
result of births and deaths and due to the departure and return of citizens. The present model
contains governance so that it not only generates scenario projections but also models specific
governance measures as well to include the pandemic and restore economic growth. The model
also adds management issues, so that it not only generates scenario forecasts but simultaneously
models specific management measures as well, aiming to suppress the pandemic and restoring
economic growth. The model was implemented on specific data on the dynamics of the spread of
the COVID-19 pandemic in selected developing economies.

Keywords: economic systems, SIR model, economic recovery, COVID-19, governance models, Sanderson model