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Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence

Author

Listed:
  • Rastko Jovanović

    (“VINČA” Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovica Alasa 12-14, P.O. Box 522, 11351 Vinca, Belgrade, Serbia)

  • Miloš Davidović

    (“VINČA” Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovica Alasa 12-14, P.O. Box 522, 11351 Vinca, Belgrade, Serbia)

  • Ivan Lazović

    (“VINČA” Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovica Alasa 12-14, P.O. Box 522, 11351 Vinca, Belgrade, Serbia)

  • Maja Jovanović

    (“VINČA” Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovica Alasa 12-14, P.O. Box 522, 11351 Vinca, Belgrade, Serbia)

  • Milena Jovašević-Stojanović

    (“VINČA” Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovica Alasa 12-14, P.O. Box 522, 11351 Vinca, Belgrade, Serbia)

Abstract

A novel statistical model based on a two-layer, contact and information, graph is suggested in order to study the influence of disease prevalence on voluntary general population vaccination during the COVID-19 outbreak. Details about the structure and number of susceptible, infectious, and recovered/vaccinated individuals from the contact layer are simultaneously transferred to the information layer. The ever-growing wealth of information that is becoming available about the COVID virus was modelled at each individual level by a simplified proxy predictor of the amount of disease spread. Each informed individual, a node in a heterogeneous graph, makes a decision about vaccination “motivated” by their benefit. The obtained results showed that disease information type, global or local, has a significant impact on an individual vaccination decision. A number of different scenarios were investigated. The scenarios showed that in the case of the stronger impact of globally broadcasted disease information, individuals tend to vaccinate in larger numbers at the same time when the infection has already spread within the population. If individuals make vaccination decisions based on locally available information, the vaccination rate is uniformly spread during infection outbreak duration. Prioritising elderly population vaccination leads to an increased number of infected cases and a higher reduction in mortality. The developed model accuracy allows the precise targeting of vaccination order depending on the individuals’ number of social contacts. Precisely targeted vaccination, combined with pre-existing immunity, and public health measures can limit the infection to isolated hotspots inside the population, as well as significantly delay and lower the infection peak.

Suggested Citation

  • Rastko Jovanović & Miloš Davidović & Ivan Lazović & Maja Jovanović & Milena Jovašević-Stojanović, 2021. "Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:12:p:6217-:d:571184
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    References listed on IDEAS

    as
    1. Sibel Eker, 2020. "Validity and usefulness of COVID-19 models," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-5, December.
    2. Ali Eshragh & Saed Alizamir & Peter Howley & Elizabeth Stojanovski, 2020. "Modeling the dynamics of the COVID-19 population in Australia: A probabilistic analysis," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-19, October.
    3. Munazza Fatima & Kara J. O’Keefe & Wenjia Wei & Sana Arshad & Oliver Gruebner, 2021. "Geospatial Analysis of COVID-19: A Scoping Review," IJERPH, MDPI, vol. 18(5), pages 1-14, February.
    4. Atangana, Abdon, 2020. "Modelling the spread of COVID-19 with new fractal-fractional operators: Can the lockdown save mankind before vaccination?," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    5. Bader S. Al-Anzi & Mohammad Alenizi & Jehad Al Dallal & Frage Lhadi Abookleesh & Aman Ullah, 2020. "An Overview of the World Current and Future Assessment of Novel COVID-19 Trajectory, Impact, and Potential Preventive Strategies at Healthcare Settings," IJERPH, MDPI, vol. 17(19), pages 1-19, September.
    6. Yu Chen & Mengke Zhu & Qian Zhou & Yurong Qiao, 2021. "Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model," IJERPH, MDPI, vol. 18(3), pages 1-26, January.
    7. Nikola Anđelić & Sandi Baressi Šegota & Ivan Lorencin & Zdravko Jurilj & Tijana Šušteršič & Anđela Blagojević & Alen Protić & Tomislav Ćabov & Nenad Filipović & Zlatan Car, 2021. "Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm," IJERPH, MDPI, vol. 18(3), pages 1-26, January.
    8. Anupama Sharma & Shakti N Menon & V Sasidevan & Sitabhra Sinha, 2019. "Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-18, May.
    9. Timokleia Kousi & Lefkothea-Christina Mitsi & Jean Simos, 2021. "The Early Stage of COVID-19 Outbreak in Greece: A Review of the National Response and the Socioeconomic Impact," IJERPH, MDPI, vol. 18(1), pages 1-17, January.
    10. Kristoffer Rypdal & Filippo Maria Bianchi & Martin Rypdal, 2020. "Intervention Fatigue is the Primary Cause of Strong Secondary Waves in the COVID-19 Pandemic," IJERPH, MDPI, vol. 17(24), pages 1-17, December.
    11. Amanda M. Y. Chu & Thomas W. C. Chan & Mike K. P. So & Wing-Keung Wong, 2021. "Dynamic Network Analysis of COVID-19 with a Latent Pandemic Space Model," IJERPH, MDPI, vol. 18(6), pages 1-22, March.
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