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Rates of SARS-COV-2 transmission and vaccination impact the fate of vaccine-resistant strains

Author

Listed:
  • Simón A. Rella

    (Institute of Science and Technology Austria)

  • Yuliya A. Kulikova

    (Banco de España)

  • Emmanouil T. Dermitzakis

    (University of Geneva Medical School)

  • Fyodor A. Kondrashov

    (Institute of Science and Technology Austria)

Abstract

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. These results, therefore, suggest the convenience of maintaining non-pharmaceutical interventions and prevention protocols throughout the entire vaccination period.

Suggested Citation

  • Simón A. Rella & Yuliya A. Kulikova & Emmanouil T. Dermitzakis & Fyodor A. Kondrashov, 2021. "Rates of SARS-COV-2 transmission and vaccination impact the fate of vaccine-resistant strains," Working Papers 2129, Banco de España.
  • Handle: RePEc:bde:wpaper:2129
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    References listed on IDEAS

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

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    Cited by:

    1. S. A. Trigger & A. M. Ignatov, 2022. "Strain-stream model of epidemic spread in application to COVID-19," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(11), pages 1-8, November.
    2. Abolfazl Mollalo & Alireza Mohammadi & Sara Mavaddati & Behzad Kiani, 2021. "Spatial Analysis of COVID-19 Vaccination: A Scoping Review," IJERPH, MDPI, vol. 18(22), pages 1-14, November.
    3. Patrick Mellacher, 2022. "Endogenous viral mutations, evolutionary selection, and containment policy design," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(3), pages 801-825, July.
    4. Shnip, A.I. & Trigger, S.A., 2024. "On the repeated epidemic waves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    5. Ioannis Alexandros Charitos & Andrea Ballini & Roberto Lovero & Francesca Castellaneta & Marica Colella & Salvatore Scacco & Stefania Cantore & Roberto Arrigoni & Filiberto Mastrangelo & Mario Dioguar, 2022. "Update on COVID-19 and Effectiveness of a Vaccination Campaign in a Global Context," IJERPH, MDPI, vol. 19(17), pages 1-20, August.
    6. Gopal Krishna Roy, 2022. "An Economic Case for Waiving Intellectual Property Rights on Covid Vaccines," India Quarterly: A Journal of International Affairs, , vol. 78(1), pages 143-147, March.
    7. Yen-Chang Chang & Ching-Ti Liu, 2022. "A Stochastic Multi-Strain SIR Model with Two-Dose Vaccination Rate," Mathematics, MDPI, vol. 10(11), pages 1-22, May.
    8. Marlon Fritz & Thomas Gries & Margarete Redlin, 2023. "The effectiveness of vaccination, testing, and lockdown strategies against COVID-19," International Journal of Health Economics and Management, Springer, vol. 23(4), pages 585-607, December.
    9. Gabriela Lobinska & Ady Pauzner & Arne Traulsen & Yitzhak Pilpel & Martin A. Nowak, 2022. "Evolution of resistance to COVID-19 vaccination with dynamic social distancing," Nature Human Behaviour, Nature, vol. 6(2), pages 193-206, February.
    10. Saba Wajeeh & Abhishek Lal & Naseer Ahmed & Md. Ibrahim Khalil & Afsheen Maqsood & Akram Mojidea M Alshammari & Abdulelah Zaid Alshammari & Meshari Musallam Mohammed Alsharari & Abdulelah Hamdan Alrus, 2021. "Operational Implications and Risk Assessment of COVID-19 in Dental Practices," IJERPH, MDPI, vol. 18(22), pages 1-13, November.
    11. Grass, D. & Wrzaczek, S. & Caulkins, J.P. & Feichtinger, G. & Hartl, R.F. & Kort, P.M. & Kuhn, M. & Prskawetz, A. & Sanchez-Romero, M. & Seidl, A., 2024. "Riding the waves from epidemic to endemic: Viral mutations, immunological change and policy responses," Theoretical Population Biology, Elsevier, vol. 156(C), pages 46-65.
    12. Xiyun Zhang & Zhongyuan Ruan & Muhua Zheng & Jie Zhou & Stefano Boccaletti & Baruch Barzel, 2022. "Epidemic spreading under mutually independent intra- and inter-host pathogen evolution," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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    More about this item

    Keywords

    SARS-COV-2 transmission; vaccination; vaccine-resistant strains; SIR model; stochastic dynamics;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    NEP fields

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