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

Abstract

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.

Mathematical Models for Forecasting Unstable Economic Processes in the Eurozone

“…The COVID-19 pandemic, due to its scale and rapid spread, practically paralyzed the entire global economy in 2020, but this shock was overcome relatively quickly. A possible economic growth recovery model for emerging economics for the period after the COVID-19 pandemic was proposed in the work by Akaev et al [1]. The events around Ukraine that followed after February 2022 led the EU countries to the highest inflation in its history, and it is obvious that its curbing will take more than one year.…”

“…Having solved the extreme problem (4) based on the actual quarterly statistical data for the period from 2015 to 2022, we have ρ = 0.28316; q Y = 0.00223 Since the equilibrium level of quarterly GDP growth rates turned out to be 0.22% (q Y = 0.00223), the annual equilibrium level of the GDP growth rates is 0.89% ( 4 * q Y , and it is quite low (this is partly due to the coronavirus pandemic), which is not enough for the effective development of the European economy. It can be seen from formula (1) that, for GDP growth, it is necessary to increase the monetary base, as well as to reduce the interest rate and the state budget deficit. These measures will increase the purchasing power of the population and consumer demand, allow enterprises to actively lend, and facilitate the inflow of investments into the economy.…”

New Challenges in the Mathematical Modelling and Control of COVID-19 Epidemics: Analysis of Non-Pharmaceutical Actions and Vaccination Strategies

“…To understand the recovery from such shocks, ref. [57] proposes a mathematical model that accounts for the interplay between pandemic dynamics and economic development, including management considerations. This model's effectiveness was validated by applying it to five emerging economies: India, Brazil, Indonesia, South Africa, and Kazakhstan.…”