IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1011931.html
   My bibliography  Save this article

Mathematical models of Plasmodium vivax transmission: A scoping review

Author

Listed:
  • Md Nurul Anwar
  • Lauren Smith
  • Angela Devine
  • Somya Mehra
  • Camelia R Walker
  • Elizabeth Ivory
  • Eamon Conway
  • Ivo Mueller
  • James M McCaw
  • Jennifer A Flegg
  • Roslyn I Hickson

Abstract

Plasmodium vivax is one of the most geographically widespread malaria parasites in the world, primarily found across South-East Asia, Latin America, and parts of Africa. One of the significant characteristics of the P. vivax parasite is its ability to remain dormant in the human liver as hypnozoites and subsequently reactivate after the initial infection (i.e. relapse infections). Mathematical modelling approaches have been widely applied to understand P. vivax dynamics and predict the impact of intervention outcomes. Models that capture P. vivax dynamics differ from those that capture P. falciparum dynamics, as they must account for relapses caused by the activation of hypnozoites. In this article, we provide a scoping review of mathematical models that capture P. vivax transmission dynamics published between January 1988 and May 2023. The primary objective of this work is to provide a comprehensive summary of the mathematical models and techniques used to model P. vivax dynamics. In doing so, we aim to assist researchers working on mathematical epidemiology, disease transmission, and other aspects of P. vivax malaria by highlighting best practices in currently published models and highlighting where further model development is required. We categorise P. vivax models according to whether a deterministic or agent-based approach was used. We provide an overview of the different strategies used to incorporate the parasite’s biology, use of multiple scales (within-host and population-level), superinfection, immunity, and treatment interventions. In most of the published literature, the rationale for different modelling approaches was driven by the research question at hand. Some models focus on the parasites’ complicated biology, while others incorporate simplified assumptions to avoid model complexity. Overall, the existing literature on mathematical models for P. vivax encompasses various aspects of the parasite’s dynamics. We recommend that future research should focus on refining how key aspects of P. vivax dynamics are modelled, including spatial heterogeneity in exposure risk and heterogeneity in susceptibility to infection, the accumulation of hypnozoite variation, the interaction between P. falciparum and P. vivax, acquisition of immunity, and recovery under superinfection.Author summary: Malaria is a mosquito-borne disease and causes significant morbidity and mortality. P. vivax is one of the five species that cause malaria and the parasites can stay hidden within the human liver after an infection from an infected mosquito bite. These hidden parasites are known as hypnozoites and can activate later, causing further infections. Mathematical modelling techniques have been used since the 19th century to understand how P. vivax malaria spreads through a population. In this study, we provide a review of all the mathematical models that have been developed until May 2023 to capture P. vivax transmission. We discuss some key aspects that are crucial when developing P. vivax transmission models and highlight the models that capture these aspects. We aim to assist researchers in the field of P. vivax malaria by providing this summary and identifying the areas where further focus is needed.

Suggested Citation

  • Md Nurul Anwar & Lauren Smith & Angela Devine & Somya Mehra & Camelia R Walker & Elizabeth Ivory & Eamon Conway & Ivo Mueller & James M McCaw & Jennifer A Flegg & Roslyn I Hickson, 2024. "Mathematical models of Plasmodium vivax transmission: A scoping review," PLOS Computational Biology, Public Library of Science, vol. 20(3), pages 1-26, March.
  • Handle: RePEc:plo:pcbi00:1011931
    DOI: 10.1371/journal.pcbi.1011931
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011931
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011931&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1011931?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
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:plo:pcbi00:1011931. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    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.