Aeronautics and COVID-19: a Reciprocal Cause-and-Effect Phenomenon

Devezas, Tessaleno C.

doi:10.5028/jatm.v12.1183

Cited by 1 publication

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“…A similar nature of the impact of a medical disease on the economy that consists of stimulating productive managerial decisions by the epidemic has not yet been seen in modern history. Devezas [15,16] characterizes COVID-19 as a "provocative" innovation that has the potential to trigger a profound global transformation, causing a sharp surge in digitalization, accelerated development of artificial intelligence, the dominance of remote forms of work, and an e-commerce boom. Furthermore, Stiglitz [17] draws conclusions about the inefficiency of traditional market mechanisms in the context of the global COVID-19 pandemic and points to the dependence of further economic growth on the active participation of governments in overcoming the pandemic and its consequences.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Introductionmentioning

confidence: 99%