IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0290974.html
   My bibliography  Save this article

Optimal age-specific vaccination control for COVID-19: An Irish case study

Author

Listed:
  • Eleni Zavrakli
  • Andrew Parnell
  • David Malone
  • Ken Duffy
  • Subhrakanti Dey

Abstract

The outbreak of a novel coronavirus causing severe acute respiratory syndrome in December 2019 has escalated into a worldwide pandemic. In this work, we propose a compartmental model to describe the dynamics of transmission of infection and use it to obtain the optimal vaccination control. The model accounts for the various stages of the vaccination, and the optimisation is focused on minimising the infections to protect the population and relieve the healthcare system. As a case study, we selected the Republic of Ireland. We use data provided by Ireland’s COVID-19 Data-Hub and simulate the evolution of the pandemic with and without the vaccination in place for two different scenarios, one representative of a national lockdown situation and the other indicating looser restrictions in place. One of the main findings of our work is that the optimal approach would involve a vaccination programme where the older population is vaccinated in larger numbers earlier while simultaneously part of the younger population also gets vaccinated to lower the risk of transmission between groups. We compare our simulated results with those of the vaccination policy taken by the Irish government to explore the advantages of our optimisation method. Our comparison suggests that a similar reduction in cases may have been possible even with a reduced set of vaccinations available for use.

Suggested Citation

  • Eleni Zavrakli & Andrew Parnell & David Malone & Ken Duffy & Subhrakanti Dey, 2023. "Optimal age-specific vaccination control for COVID-19: An Irish case study," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-38, September.
  • Handle: RePEc:plo:pone00:0290974
    DOI: 10.1371/journal.pone.0290974
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0290974
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0290974&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0290974?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ding, Chunxiao & Liu, Wenjian & Sun, Yun & Zhu, Yuanguo, 2019. "A delayed Schistosomiasis transmission model and its dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 18-34.
    2. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
    3. Li, Tingting & Guo, Youming, 2022. "Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    4. Phenyo E. Lekone & Bärbel F. Finkenstädt, 2006. "Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study," Biometrics, The International Biometric Society, vol. 62(4), pages 1170-1177, December.
    5. Alberto Godio & Francesca Pace & Andrea Vergnano, 2020. "SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence," IJERPH, MDPI, vol. 17(10), pages 1-19, May.
    6. Li, Li & Zhang, Jie & Liu, Chen & Zhang, Hong-Tao & Wang, Yi & Wang, Zhen, 2019. "Analysis of transmission dynamics for Zika virus on networks," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 566-577.
    Full references (including those not matched with items on IDEAS)

    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. Tagliazucchi, E. & Balenzuela, P. & Travizano, M. & Mindlin, G.B. & Mininni, P.D., 2020. "Lessons from being challenged by COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    2. Lu Tang & Yiwang Zhou & Lili Wang & Soumik Purkayastha & Leyao Zhang & Jie He & Fei Wang & Peter X.‐K. Song, 2020. "A Review of Multi‐Compartment Infectious Disease Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 462-513, August.
    3. Catalina Amuedo-Dorantes & Neeraj Kaushal & Ashley N. Muchow, 2021. "Timing of social distancing policies and COVID-19 mortality: county-level evidence from the U.S," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1445-1472, October.
    4. Kamara, Abdul A. & Wang, Xiangjun & Mouanguissa, Lagès Nadège, 2020. "Analytical solution for post-death transmission model of Ebola epidemics," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    5. Susan M. Rogers & James Rineer & Matthew D. Scruggs & William D. Wheaton & Phillip C. Cooley & Douglas J. Roberts & Diane K. Wagener, 2014. "A Geospatial Dynamic Microsimulation Model for Household Population Projections," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 119-146.
    6. Talal Daghriri & Michael Proctor & Sarah Matthews, 2022. "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    7. Andrew G. Atkeson & Karen A. Kopecky & Tao Zha, 2024. "Four Stylized Facts About Covid‐19," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(1), pages 3-42, February.
    8. Victor W. Chu & Raymond K. Wong & Chi-Hung Chi & Wei Zhou & Ivan Ho, 2017. "The design of a cloud-based tracker platform based on system-of-systems service architecture," Information Systems Frontiers, Springer, vol. 19(6), pages 1283-1299, December.
    9. Khan, Hasib & Ibrahim, Muhammad & Abdel-Aty, Abdel-Haleem & Khashan, M. Motawi & Khan, Farhat Ali & Khan, Aziz, 2021. "A fractional order Covid-19 epidemic model with Mittag-Leffler kernel," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    10. Wouter Vermeer & Otto Koppius & Peter Vervest, 2018. "The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-21, December.
    11. Phillip Stroud & Sara Del Valle & Stephen Sydoriak & Jane Riese & Susan Mniszewski, 2007. "Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-9.
    12. Caixia Wang & Huijie Li, 2022. "Public Compliance Matters in Evidence-Based Public Health Policy: Evidence from Evaluating Social Distancing in the First Wave of COVID-19," IJERPH, MDPI, vol. 19(7), pages 1-13, March.
    13. Shen, Lucas, 2025. "Illegal immigration and infections: Evidence from two modern pandemics," Economic Modelling, Elsevier, vol. 145(C).
    14. Robin N Thompson & Christopher A Gilligan & Nik J Cunniffe, 2016. "Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-18, April.
    15. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    16. Krista Ruffini & Aaron Sojourner & Abigail Wozniak, 2021. "Who'S In And Who'S Out Under Workplace Covid Symptom Screening?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(2), pages 614-641, March.
    17. Lin Ma & Gil Shapira & Damien de Walque & Quy‐Toan Do & Jed Friedman & Andrei A. Levchenko, 2022. "The Intergenerational Mortality Trade‐Off Of Covid‐19 Lockdown Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1427-1468, August.
    18. Philipp Ager & Katherine Eriksson & Ezra Karger & Peter Nencka & Melissa A. Thomasson, 2024. "School Closures during the 1918 Flu Pandemic," The Review of Economics and Statistics, MIT Press, vol. 106(1), pages 266-276, January.
    19. repec:plo:pone00:0243699 is not listed on IDEAS
    20. repec:plo:pone00:0128070 is not listed on IDEAS
    21. Jérôme Adda, 2016. "Economic Activity and the Spread of Viral Diseases: Evidence from High Frequency Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 891-941.
    22. Peter Caley & Niels G Becker & David J Philp, 2007. "The Waiting Time for Inter-Country Spread of Pandemic Influenza," PLOS ONE, Public Library of Science, vol. 2(1), pages 1-8, January.

    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:plo:pone00:0290974. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.