IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v92y2024ics0038012124000466.html
   My bibliography  Save this article

Planning for the optimal vaccination sequence in the context of a population-stratified model

Author

Listed:
  • Zhang, Jingwen
  • Wang, Xinwei
  • Rong, Lili
  • Pan, Qiuwei
  • Bao, Chunbing
  • Zheng, Qinyue

Abstract

We explore strategies for optimally controlling the pandemic through practical vaccination planning across different subpopulations, with the aiming of striking a balance between minimizing mortalities and conserving vaccines. To achieve this objective, the total population is categorized into four subpopulations: health workers, young individuals, middle-aged individuals, and the elderly, based on immunity and exposure risk. We assume a heterogeneous pattern of social contacts among these subpopulations. Accordingly, we formulate a population-stratified SPMILHRD model with 32 compartments that accounts for different statuses of detection and symptoms to define the epidemic dynamics. Numerical simulations demonstrate a staged optimization-based, population-stratified vaccination approach, where health workers, the middle-aged, the elderly, and the young receive priority in succession. The analysis reveals that our optimal vaccination control strategy can significantly reduce the number of infections, including fatalities, compared to scenarios involving proportional policies or no control in the numerical experiment. It has demonstrated that well-designed vaccination planning could substantially curb dissemination and reduce mortality. The findings of this study are instructive for the potential implementation of future vaccine administration.

Suggested Citation

  • Zhang, Jingwen & Wang, Xinwei & Rong, Lili & Pan, Qiuwei & Bao, Chunbing & Zheng, Qinyue, 2024. "Planning for the optimal vaccination sequence in the context of a population-stratified model," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    • Handle: RePEc:eee:soceps:v:92:y:2024:i:c:s0038012124000466
    DOI: 10.1016/j.seps.2024.101847
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012124000466
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2024.101847?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yousefpour, Amin & Jahanshahi, Hadi & Bekiros, Stelios, 2020. "Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    2. van Ackere, Ann & Schulz, Peter J., 2020. "Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    3. Na Jia & Lawrence Tsui, 2005. "Epidemic Modelling using Sars as a Case Study," North American Actuarial Journal, Taylor & Francis Journals, vol. 9(4), pages 28-42.
    4. Ochoa-Barragán, Rogelio & Munguía-López, Aurora del Carmen & Ponce-Ortega, José María, 2023. "Strategic planning for the optimal distribution of COVID-19 vaccines," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    5. Oluwaseun Sharomi & Tufail Malik, 2017. "Optimal control in epidemiology," Annals of Operations Research, Springer, vol. 251(1), pages 55-71, April.
    6. Gong, Jiangyue & Gujjula, Krishna Reddy & Ntaimo, Lewis, 2023. "An integrated chance constraints approach for optimal vaccination strategies under uncertainty for COVID-19," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    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. Asamoah, Joshua Kiddy K. & Owusu, Mark A. & Jin, Zhen & Oduro, F. T. & Abidemi, Afeez & Gyasi, Esther Opoku, 2020. "Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment: using data from Ghana," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Tu, Yunbo & Meng, Xinzhu & Alzahrani, Abdullah Khames & Zhang, Tonghua, 2023. "Multi-objective optimization and nonlinear dynamics for sub-healthy COVID-19 epidemic model subject to self-diffusion and cross-diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    3. Chu, Yu-Ming & Bekiros, Stelios & Zambrano-Serrano, Ernesto & Orozco-López, Onofre & Lahmiri, Salim & Jahanshahi, Hadi & Aly, Ayman A., 2021. "Artificial macro-economics: A chaotic discrete-time fractional-order laboratory model," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    4. Charu Arora & Poras Khetarpal & Saket Gupta & Nuzhat Fatema & Hasmat Malik & Asyraf Afthanorhan, 2023. "Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management," Mathematics, MDPI, vol. 11(4), pages 1-15, February.
    5. Njud S. Alharbi & Hadi Jahanshahi & Qijia Yao & Stelios Bekiros & Irene Moroz, 2023. "Enhanced Classification of Heartbeat Electrocardiogram Signals Using a Long Short-Term Memory–Convolutional Neural Network Ensemble: Paving the Way for Preventive Healthcare," Mathematics, MDPI, vol. 11(18), pages 1-17, September.
    6. Michela Baccini & Giulia Cereda & Cecilia Viscardi, 2021. "The first wave of the SARS-CoV-2 epidemic in Tuscany (Italy): A SI2R2D compartmental model with uncertainty evaluation," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-23, April.
    7. Maleki, Abolfazl & Hemmati, Vahid & Reza Abazari, Seyed & Aghsami, Amir & Rabbani, Masoud, 2024. "Optimal distribution and waste management of Covid-19 vaccines from vaccination centers’ satisfaction perspective – A fuzzy time window-based VRP," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    8. Kumar Das, Dhiraj & Khatua, Anupam & Kar, T.K. & Jana, Soovoojeet, 2021. "The effectiveness of contact tracing in mitigating COVID-19 outbreak: A model-based analysis in the context of India," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    9. Xin Jing & Jin Seo Cho, 2023. "Forecasting the Confirmed COVID-19 Cases Using Modal Regression," Working papers 2023rwp-217, Yonsei University, Yonsei Economics Research Institute.
    10. Imane Abouelkheir & Fadwa El Kihal & Mostafa Rachik & Ilias Elmouki, 2019. "Optimal Impulse Vaccination Approach for an SIR Control Model with Short-Term Immunity," Mathematics, MDPI, vol. 7(5), pages 1-21, May.
    11. Ozgur M. Araz & Mayteé Cruz-Aponte & Fernando A. Wilson & Brock W. Hanisch & Ruth S. Margalit, 2022. "An Analytic Framework for Effective Public Health Program Design Using Correctional Facilities," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 113-128, January.
    12. Kazancoglu, Yigit & Ekinci, Esra & Mangla, Sachin Kumar & Sezer, Muruvvet Deniz & Ozbiltekin-Pala, Melisa, 2023. "Impact of epidemic outbreaks (COVID-19) on global supply chains: A case of trade between Turkey and China," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    13. Kılıç, Hakan & Güneş, Evrim Didem, 2024. "Patient adherence in healthcare operations: A narrative review," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    14. Nenchev, Vladislav, 2020. "Optimal quarantine control of an infectious outbreak," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    15. Hainaut, Donatien, 2020. "An actuarial approach for modeling pandemic risk," LIDAM Discussion Papers ISBA 2020025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Mustafa Akan, 2019. "Optimal Control Theoretic Approach To Investment In Doctors," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 8(4), pages 91-111.
    17. Donatien Hainaut, 2020. "An Actuarial Approach for Modeling Pandemic Risk," Risks, MDPI, vol. 9(1), pages 1-28, December.
    18. Arshad, Sadia & Siddique, Imran & Nawaz, Fariha & Shaheen, Aqila & Khurshid, Hina, 2023. "Dynamics of a fractional order mathematical model for COVID-19 epidemic transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    19. de Souza, Silvio L.T. & Batista, Antonio M. & Caldas, Iberê L. & Iarosz, Kelly C. & Szezech Jr, José D., 2021. "Dynamics of epidemics: Impact of easing restrictions and control of infection spread," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    20. Sharbayta, Sileshi Sintayehu & Buonomo, Bruno & d'Onofrio, Alberto & Abdi, Tadesse, 2022. "‘Period doubling’ induced by optimal control in a behavioral SIR epidemic model," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).

    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:eee:soceps:v:92:y:2024:i:c:s0038012124000466. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.