IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i23p3817-d1535183.html
   My bibliography  Save this article

Synergistic Impact of Active Case Detection and Early Hospitalization for Controlling the Spread of Yellow Fever Outbreak in Nigeria: An Epidemiological Modeling and Optimal Control Analysis

Author

Listed:
  • Nawaf L. Alsowait

    (Department of Mathematics, College of Science, Northern Border University, Arar 91431, Saudi Arabia)

  • Mohammed M. Al-Shomrani

    (Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Ismail Abdulrashid

    (School of Finance and Operations Management, The University of Tulsa, Tulsa, OK 74104, USA)

  • Salihu S. Musa

    (Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
    Department of Mathematics, Aliko Dangote University of Science and Technology, Wudil 713101, Kano, Nigeria
    Department of Mathematics, University of Maryland, College Park, MD 20742, USA
    Institute for Health Computing, University of Maryland, North Bethesda, MD 20852, USA)

Abstract

Capturing the factors influencing yellow fever (YF) outbreaks is essential for effective public health interventions, especially in regions like Nigeria, where the disease poses significant health risks. This study explores the synergistic effects of active case detection (ACD) and early hospitalization on controlling YF transmission dynamics. We develop a dynamic model that integrates vaccination, active case detection, and hospitalization to enhance our understanding of disease spread and inform prevention strategies. Our methodology encompasses mechanistic dynamic modeling, optimal control analysis, parameter estimation, model fitting, and sensitivity analyses to study YF transmission dynamics, ensuring the robustness of control measures. We employ advanced mathematical techniques, including next-generation matrix methods, to accurately compute the reproduction number and assess outbreak transmissibility. Rigorous qualitative analysis of the model reveals two equilibria: disease-free and endemic, demonstrating global asymptotic stability and its impact on overall YF transmission dynamics, significantly affecting control and prevention mechanisms. Furthermore, through sensitivity analysis, we identify crucial parameters of the model that require urgent attention for more effective YF control. Moreover, our results highlight the critical roles of ACD and early hospitalization in reducing YF transmission. These insights provide a foundation for informed decision making and resource allocation in epidemic control efforts, ultimately contributing to the enhancement of public health strategies aimed at mitigating the impact of YF outbreaks.

Suggested Citation

  • Nawaf L. Alsowait & Mohammed M. Al-Shomrani & Ismail Abdulrashid & Salihu S. Musa, 2024. "Synergistic Impact of Active Case Detection and Early Hospitalization for Controlling the Spread of Yellow Fever Outbreak in Nigeria: An Epidemiological Modeling and Optimal Control Analysis," Mathematics, MDPI, vol. 12(23), pages 1-30, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3817-:d:1535183
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/23/3817/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/23/3817/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robbins, Matthew J. & Lunday, Brian J., 2016. "A bilevel formulation of the pediatric vaccine pricing problem," European Journal of Operational Research, Elsevier, vol. 248(2), pages 634-645.
    2. Mohammed M. Al-Shomrani & Salihu S. Musa & Abdullahi Yusuf, 2023. "Unfolding the Transmission Dynamics of Monkeypox Virus: An Epidemiological Modelling Analysis," Mathematics, MDPI, vol. 11(5), pages 1-21, February.
    3. Duijzer, Lotty Evertje & van Jaarsveld, Willem & Dekker, Rommert, 2018. "Literature review: The vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 268(1), pages 174-192.
    4. Jovic Aaron S. Caasi & Brian M. Joseph & Heera J. Kodiyamplakkal & Jaelene Renae U. Manibusan & Leslie J. Camacho Aquino & Hyunju Oh & Jan Rychtář & Dewey Taylor, 2022. "A Game-Theoretic Model of Voluntary Yellow Fever Vaccination to Prevent Urban Outbreaks," Games, MDPI, vol. 13(4), pages 1-14, August.
    5. Molnar, S. & Szidarovszky, F., 1996. "Some notes on the time-variant Lyapunov theory," European Journal of Operational Research, Elsevier, vol. 89(3), pages 668-670, March.
    6. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    7. Tadic, Vladislav, 1997. "Stochastic gradient algorithm with random truncations," European Journal of Operational Research, Elsevier, vol. 101(2), pages 261-284, September.
    8. Katy A M Gaythorpe & Kévin Jean & Laurence Cibrelus & Tini Garske, 2019. "Quantifying model evidence for yellow fever transmission routes in Africa," PLOS Computational Biology, Public Library of Science, vol. 15(9), pages 1-18, September.
    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. Wang, Fan & Xu, Danni & Zhuo, Xiaopo & Zhang, Chao & Liu, Yaoqi, 2022. "Improving consumer welfare in vaccine market: Pricing, government subsidies and consumer awareness," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    2. Muckstadt, John A. & Klein, Michael G. & Jackson, Peter L. & Gougelet, Robert M. & Hupert, Nathaniel, 2023. "Efficient and effective large-scale vaccine distribution," International Journal of Production Economics, Elsevier, vol. 262(C).
    3. Pirayesh, Amir & Asadaraghi, Alireza & Mohammadi, Mehrdad & Siadat, Ali & Battaïa, Olga, 2025. "A dynamic optimization model for vaccine allocation with age considerations: A study inspired by the COVID-19 pandemic," International Journal of Production Economics, Elsevier, vol. 280(C).
    4. Chen, Shi-Shun & Li, Xiao-Yang, 2025. "Comparison of global sensitivity analysis methods for a fire spread model with a segmented characteristic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 229(C), pages 304-318.
    5. Sinha, Priyank & Kumar, Sameer & Chandra, Charu, 2023. "Strategies for ensuring required service level for COVID-19 herd immunity in Indian vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 304(1), pages 339-352.
    6. Laura Calvet & Rocio de la Torre & Anita Goyal & Mage Marmol & Angel A. Juan, 2020. "Modern Optimization and Simulation Methods in Managerial and Business Economics: A Review," Administrative Sciences, MDPI, vol. 10(3), pages 1-23, July.
    7. Chiara F. Del Bo, 2023. "Institutional quality and COVID-19 vaccination: does decentralization matter?," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-24, December.
    8. Rebecca M Johnson & Isaac J Stopard & Helen M Byrne & Philip M Armstrong & Douglas E Brackney & Ben Lambert, 2024. "Investigating the dose-dependency of the midgut escape barrier using a mechanistic model of within-mosquito dengue virus population dynamics," PLOS Pathogens, Public Library of Science, vol. 20(4), pages 1-28, April.
    9. Mo, Wenyu & Yu, Beichen & Jiang, Long & Xu, Kai & Xu, Jun & Wang, Yi & Su, Sheng & Hu, Song & Xiang, Jun, 2024. "Process simulation, thermodynamic and system optimization for the low-carbon alcohols production via gasification of second-generation biomass," Energy, Elsevier, vol. 313(C).
    10. Lin, Qi & Zhao, Qiuhong & Lev, Benjamin, 2022. "Influenza vaccine supply chain coordination under uncertain supply and demand," European Journal of Operational Research, Elsevier, vol. 297(3), pages 930-948.
    11. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    12. Zéphirin Nganmeni & Roland Pongou & Bertrand Tchantcho & Jean‐Baptiste Tondji, 2022. "Vaccine and inclusion," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 1101-1123, October.
      • Zéphirin Nganmeni & Roland Pongou & Bertrand Tchantcho & Jean-Baptiste Tondji, 2022. "Vaccine and Inclusion," Working Papers 2202E Classification-C62,, University of Ottawa, Department of Economics.
      • Zéphirin Nganmeni & Roland Pongou & Bertrand Tchantcho & Jean‐baptiste Tondji, 2022. "Vaccine and inclusion," Post-Print hal-04257703, HAL.
    13. Lotty E. Westerink‐Duijzer & Loe P. J. Schlicher & Marieke Musegaas, 2020. "Core Allocations for Cooperation Problems in Vaccination," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1720-1737, July.
    14. De Boeck, Kim & Decouttere, Catherine & Vandaele, Nico, 2020. "Vaccine distribution chains in low- and middle-income countries: A literature review," Omega, Elsevier, vol. 97(C).
    15. Yadav, Amit Kumar & Shweta, & Kumar, Dinesh, 2023. "Blockchain technology and vaccine supply chain: Exploration and analysis of the adoption barriers in the Indian context," International Journal of Production Economics, Elsevier, vol. 255(C).
    16. Lunday, Brian J. & Robbins, Matthew J., 2019. "Collaboratively-developed vaccine pricing and stable profit sharing mechanisms," Omega, Elsevier, vol. 84(C), pages 102-113.
    17. 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).
    18. Xie, Lei & Hou, Pengwen & Han, Hongshuai, 2021. "Implications of government subsidy on the vaccine product R&D when the buyer is risk averse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    19. Leonelli, Manuele & Varando, Gherardo, 2024. "Robust learning of staged tree models: A case study in evaluating transport services," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    20. Fadaki, Masih & Abareshi, Ahmad & Far, Shaghayegh Maleki & Lee, Paul Tae-Woo, 2022. "Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia," Transportation Research Part E: Logistics and Transportation Review, 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:gam:jmathe:v:12:y:2024:i:23:p:3817-:d:1535183. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.