Attitudes Toward Vaccination and Its Impact on Economy

Rapid rollouts of the vaccine are imperative for economic recovery;however, vaccine hesitancy could draw out not only the pandemic but also social distancing and lockdown requirements. The main purpose of this paper is to empirically investigate whether the vaccination rate affects government budget constraints as well as whether vaccine hesitancy matters in controlling the dynamics of the Covid-19 epidemic in Uzbekistan. We integrated a Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model with a macroeconomic model to explore the impact of the vaccination. Our results show that vaccine hesitancy substantially influences excess COVID-19-related deaths, such that governments that are able to sustain quick vaccine rollout rates would have a 20-times lower excess death rate. A slow-paced vaccine rollout has compounded effects over time, producing much heavier consequences for the population than a rapid rollout rate. In Uzbekistan, a counterfactual exercise that intensified vaccine hesitancy between April and November 2021 likely increased the death toll by approximately thousand deaths. Therefore, the policy gains of accelerating the vaccination rate are significant, given that it would minimize both cumulative mortality and the risk of new virus variants while achieving herd immunity. Concurrently, efforts to mitigate hesitancy are crucial, particularly if the percentage of the population that is against the vaccination is greater than the percentage needed for herd immunity. To this end, our empirical study helps shed light on the challenging dynamics between health and the economy during the pandemic as well as the mechanisms through which these effects take place. JEL Classification: I15, I18, D58, E17 © International Journal of Economics and Management. ISSN 1823-836X. e-ISSN 2600-9390.

Purely Data-driven Exploration of COVID-19 Pandemic After Three Months of the Outbreak

Many research studies have been carried out to understand the epidemiological characteristics of the COVID-19 pandemic in its early phase. The current study is yet another contribution to better understand the disease properties by parameter estimation based on mathematical SIR epidemic modeling. The authors used Johns Hopkins University's dataset to estimate the basic reproduction number of COVID-19 for five representative countries (Japan, Germany, Italy, France, and the Netherlands) that were selected using cluster analysis. As by products, the authors estimated the transmission, recovery, and death rates for each selected country and carried out statistical tests to see if there were any significant differences.