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Assessing the global impact of COVID-19 vaccination

Author

Listed:
  • Rayhan

    (Department of Computer Science and Engineering, Brac University, 66 Mohakhali, Dhaka-1212, Dhaka, Bangladesh.)

  • M. Abdullah-Al-Wadud

    (Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.)

  • M. Helal Uddin Ahmed

    (B. Sc (Hons.), M.Sc (Dhaka), MBA (Dundee, UK), Ph.D. in Computer Engineering (South Korea), Professor, Department of Management Information Systems (MIS), University of Dhaka, Dhaka-1000, Bangladesh)

Abstract

This study aims to statistically assess the effectiveness of vaccination against SARS-CoV-2. It is indispensable to investigate the association between COVID-19 deadliness and vaccination in order to study the impact of vaccine in real-world. The COVID-19 database ‘Our World in Data’ was analyzed on every three weeks interval. We studied rates of infection and death due to COVID-19 in different countries with respect to their level of vaccination. The estimation of risk of death was investigated using Case Fatality Ratio (CFR). People who received the required dose of vaccination were considered as fully vaccinated in this study. Based on the percentage of fully vaccinated population, countries were categorized into several groups. For the percentage of fully vaccinated population and COVID-19 CFR level, the coefficient of a linear trend line was calculated. During the investigation period, the countries were categorized into various bins of vaccination level and the average CFR of each bin was calculated in order to compare the change of COVID-19 CFR w.r.t vaccination levels.

Suggested Citation

  • Rayhan & M. Abdullah-Al-Wadud & M. Helal Uddin Ahmed, 2023. "Assessing the global impact of COVID-19 vaccination," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(1), pages 478-484, January.
    • Handle: RePEc:bcp:journl:v:7:y:2023:i:1:p:478-484
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    References listed on IDEAS

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    1. Manski, Charles F. & Molinari, Francesca, 2021. "Estimating the COVID-19 infection rate: Anatomy of an inference problem," Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
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