IDEAS home Printed from https://ideas.repec.org/a/bcp/journl/v7y2023i1p478-484.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijriss/Digital-Library/volume-7-issue-1/478-484.pdf
    Download Restriction: no
    File URL: https://www.rsisinternational.org/journals/ijriss/articles/assessing-the-global-impact-of-covid-19-vaccination/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Superchi, Francesco & Mati, Alessandro & Carcasci, Carlo & Bianchini, Alessandro, 2023. "Techno-economic analysis of wind-powered green hydrogen production to facilitate the decarbonization of hard-to-abate sectors: A case study on steelmaking," Applied Energy, Elsevier, vol. 342(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ichino, Andrea & Favero, Carlo A. & Rustichini, Aldo, 2020. "Restarting the economy while saving lives under Covid-19," CEPR Discussion Papers 14664, C.E.P.R. Discussion Papers.
    2. Difang Huang & Ying Liang & Boyao Wu & Yanyi Ye, 2025. "Estimating the impact of social distance policy in mitigating COVID-19 spread with factor-based imputation approach," Empirical Economics, Springer, vol. 68(2), pages 585-601, February.
    3. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
    4. La Torre, Davide & Liuzzi, Danilo & Marsiglio, Simone, 2021. "Epidemics and macroeconomic outcomes: Social distancing intensity and duration," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    5. Badi H. Baltagi & Ying Deng & Jing Li & Zhenlin Yang, 2023. "Cities in a pandemic: Evidence from China," Journal of Regional Science, Wiley Blackwell, vol. 63(2), pages 379-408, March.
    6. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    7. Nicholas W. Papageorge & Matthew V. Zahn & Michèle Belot & Eline Broek-Altenburg & Syngjoo Choi & Julian C. Jamison & Egon Tripodi, 2021. "Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(2), pages 691-738, April.
    8. Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
    9. Walter Distaso & Rustam Ibragimov & Alexander Semenov & Anton Skrobotov, 2020. "COVID-19: Tail Risk and Predictive Regressions," Papers 2009.02486, arXiv.org, revised Oct 2021.
    10. Chen, Xi & Qiu, Yun & Shi, Wei & Yu, Pei, 2022. "Key links in network interactions: Assessing route-specific travel restrictions in China during the Covid-19 pandemic," China Economic Review, Elsevier, vol. 73(C).
    11. Mauro Caselli & Andrea Fracasso & Sergio Scicchitano, 2022. "From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(4), pages 1517-1550, October.
    12. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    13. Garriga, Carlos & Manuelli, Rody & Sanghi, Siddhartha, 2022. "Optimal management of an epidemic: Lockdown, vaccine and value of life," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    14. Zakharov, Nikita, 2020. "The protective effect of smoking against COVID-19: A population-based study using instrumental variables," MPRA Paper 101267, University Library of Munich, Germany.
    15. Jung, Juergen & Manley, James & Shrestha, Vinish, 2021. "Coronavirus infections and deaths by poverty status: The effects of social distancing," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 311-330.
    16. Michael Barnett & Greg Buchak & Constantine Yannelis, 2023. "Epidemic responses under uncertainty," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(2), pages 2208111120-, January.
    17. Franco Peracchi & Daniele Terlizzese, 2020. "Estimating the prevalence of the COVID-19 infection, with an application to Italy," EIEF Working Papers Series 2013, Einaudi Institute for Economics and Finance (EIEF), revised May 2020.
    18. Huberts, Nick F.D. & Thijssen, Jacco J.J., 2023. "Optimal timing of non-pharmaceutical interventions during an epidemic," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1366-1389.
    19. Daniel W. Sacks & Nir Menachemi & Peter Embi & Coady Wing, 2020. "What can we learn about SARS-CoV-2 prevalence from testing and hospital data?," Papers 2008.00298, arXiv.org, revised Mar 2021.
    20. Shin KINOSHITA & Masayuki SATO & Takanori IDA, 2022. "Bayesian Probability Revision and Infection Prevention Behavior in Japan : A Quantitative Analysis of the First Wave of COVID-19," Discussion papers e-22-004, Graduate School of Economics , Kyoto University.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bcp:journl:v:7:y:2023:i:1:p:478-484. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Pawan Verma (email available below). General contact details of provider: https://rsisinternational.org/journals/ijriss/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.