IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v168y2023ics0960077923001005.html
   My bibliography  Save this article

Optimal strategies of the age-specific vaccination and antiviral treatment against influenza

Author

Listed:
  • Yang, Junyuan
  • Yang, Li
  • Jin, Zhen

Abstract

Influenza, caused by any of several human influenza viruses, is a highly contagious respiratory disease and it produces millions of cases worldwide. Vaccination and antiviral treatment are two main biomedical interventions for curtailing influenza spread. In this paper, an age-structured SVIR influenza model is used to take account for the efficacy of vaccination and antiviral treatment. Next, the stability of the disease-free equilibrium is captured by analyzing the root distributions of the characteristic equation and the existence of the endemic equilibrium is established by employing a generalized fixed point theorem. Moreover, the consideration of the availability of medical resources is settled as an optimal control problem to investigate the cost-effective interventions for the guidelines of optimal policy selection. Numerical simulations show that the outcomes of optimal control are characterized by the cost of control strategies, age structured of hosts and the different measures of influenza intervention. As a result of consequences, we recommend projecting vaccination at the early period and the implement of therapy at the entire infectious course, to slow down or eradicate influenza transmission.

Suggested Citation

  • Yang, Junyuan & Yang, Li & Jin, Zhen, 2023. "Optimal strategies of the age-specific vaccination and antiviral treatment against influenza," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:chsofr:v:168:y:2023:i:c:s0960077923001005
    DOI: 10.1016/j.chaos.2023.113199
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923001005
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113199?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. Kang, Ting & Zhang, Qimin & Rong, Libin, 2019. "A delayed avian influenza model with avian slaughter: Stability analysis and optimal control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 529(C).
    2. Cassandra Willyard, 2019. "Flu on the farm," Nature, Nature, vol. 573(7774), pages 62-63, September.
    3. Steven Riley & Joseph T Wu & Gabriel M Leung, 2007. "Optimizing the Dose of Pre-Pandemic Influenza Vaccines to Reduce the Infection Attack Rate," PLOS Medicine, Public Library of Science, vol. 4(6), pages 1-9, June.
    4. Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
    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. Zhou, Qi & Li, Xining & Hu, Jing & Zhang, Qimin, 2024. "Dynamics and optimal control for a spatial heterogeneity model describing respiratory infectious diseases affected by air pollution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 220(C), pages 276-295.

    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. M. Hashem Pesaran & Cynthia Fan Yang, 2022. "Matching theory and evidence on Covid‐19 using a stochastic network SIR model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1204-1229, September.
    3. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    4. S. M. Niaz Arifin & Christoph Zimmer & Caroline Trotter & Anaïs Colombini & Fati Sidikou & F. Marc LaForce & Ted Cohen & Reza Yaesoubi, 2019. "Cost-Effectiveness of Alternative Uses of Polyvalent Meningococcal Vaccines in Niger: An Agent-Based Transmission Modeling Study," Medical Decision Making, , vol. 39(5), pages 553-567, July.
    5. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    6. Mirjam Kretzschmar & Rafael T Mikolajczyk, 2009. "Contact Profiles in Eight European Countries and Implications for Modelling the Spread of Airborne Infectious Diseases," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-8, June.
    7. Andrei I. Vlad & Alexei A. Romanyukha & Tatiana E. Sannikova, 2024. "Parameter Tuning of Agent-Based Models: Metaheuristic Algorithms," Mathematics, MDPI, vol. 12(14), pages 1-21, July.
    8. Gillis, Melissa & Urban, Ryley & Saif, Ahmed & Kamal, Noreen & Murphy, Matthew, 2021. "A simulation–optimization framework for optimizing response strategies to epidemics," Operations Research Perspectives, Elsevier, vol. 8(C).
    9. Valentina Marziano & Giorgio Guzzetta & Alessia Mammone & Flavia Riccardo & Piero Poletti & Filippo Trentini & Mattia Manica & Andrea Siddu & Antonino Bella & Paola Stefanelli & Patrizio Pezzotti & Ma, 2021. "The effect of COVID-19 vaccination in Italy and perspectives for living with the virus," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    10. Nikolaos P. Rachaniotis & Thomas K. Dasaklis & Filippos Fotopoulos & Platon Tinios, 2021. "A Two-Phase Stochastic Dynamic Model for COVID-19 Mid-Term Policy Recommendations in Greece: A Pathway towards Mass Vaccination," IJERPH, MDPI, vol. 18(5), pages 1-21, March.
    11. Thomas Ash & Antonio M. Bento & Daniel Kaffine & Akhil Rao & Ana I. Bento, 2022. "Disease-economy trade-offs under alternative epidemic control strategies," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    12. Lewandowski, Piotr, 2020. "Occupational Exposure to Contagion and the Spread of COVID-19 in Europe," IZA Discussion Papers 13227, Institute of Labor Economics (IZA).
    13. Ruenzi, Stefan & Maeckle, Kai, 2023. "Friends with Drugs: The Role of Social Networks in the Opioid Epidemic," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277574, Verein für Socialpolitik / German Economic Association.
    14. Laura Ozella & Francesco Gesualdo & Michele Tizzoni & Caterina Rizzo & Elisabetta Pandolfi & Ilaria Campagna & Alberto Eugenio Tozzi & Ciro Cattuto, 2018. "Close encounters between infants and household members measured through wearable proximity sensors," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-16, June.
    15. Mohamed Ismail, 2023. "The Effect of Social Contacts on the Uptake of Health Innovations among Older Ethnic Minorities in the UK: A Mixed Methods Study," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    16. Christopher Bronk Ramsey, 2020. "Human agency and infection rates: Implications for social distancing during epidemics," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-17, December.
    17. Charles Stoecker & Nicholas J. Sanders & Alan Barreca, 2016. "Success Is Something to Sneeze At: Influenza Mortality in Cities that Participate in the Super Bowl," American Journal of Health Economics, MIT Press, vol. 2(1), pages 125-143, January.
    18. Étienne Dagorn & Martina Dattilo & Matthieu Pourieux, 2022. "Preferences matter! Political Responses to the COVID-19 and Population’s Preferences," Economics Working Paper Archive (University of Rennes & University of Caen) 2022-01, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    19. Batabyal, Saikat, 2021. "COVID-19: Perturbation dynamics resulting chaos to stable with seasonality transmission," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    20. Anna Houstecka & Dongya Koh & Raül Santaeulàlia-Llopis, 2020. "Contagion at Work," Working Papers 1225, Barcelona School of Economics.

    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:chsofr:v:168:y:2023:i:c:s0960077923001005. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.