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Transmission dynamics of mumps epidemic model through stochastic analysis with delay effect

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10258599" target="_blank" >RIV/61989100:27740/25:10258599 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.nature.com/articles/s41598-025-11869-z" target="_blank" >https://www.nature.com/articles/s41598-025-11869-z</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1038/s41598-025-11869-z" target="_blank" >10.1038/s41598-025-11869-z</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Transmission dynamics of mumps epidemic model through stochastic analysis with delay effect

  • Original language description

    Stochastic delayed modeling (stochastic differential equations (SDEs) with delay parameters) has a significant non-pharmaceutical intervention to control transmission dynamics of infectious diseases and its results are close to the reality of nature. Mumps is a viral disease specified with swollen jaws and inflated cheeks. Direct contact with saliva or respiratory drop less from the mouth is the major causes of its outbreak. According to the World Health Organization (WHO), still, 20% of young adult males develop mumps worldwide. No doubt, the vaccination of Mumps exists. The main cause is to study the transmission dynamics of Mumps through stochastic with delay approaches. How is the stochastic delay the best strategy to study the dynamics of disease in a population? For this, we consider the existing deterministic model in literature, with the whole population, divided as susceptible human population S(t), exposed human population E(t), symptomatic infectious I(t), asymptomatic infectious A(t), isolated and treated symptomatic Q(t), recovered humans R(t). After that, we extend the deterministic model into a stochastic delay model (Stochastic delay differential equations (SDDEs) by using the transition probabilities and non-parametric perturbation ways. The positivity, boundedness, extinction, and persistence of disease study with essential properties of reproduction number rigorously. The mump-free equilibrium (MFE) and mumps existing equilibrium (MEE) are two states, local, and global stability of second order and sensitivity analysis of parameters analyzed to verify the model validations. Due to the highly nonlinear stochastic delay differential equations of the model, we used both standard and nonstandard methods such as Euler Maryama, stochastic Euler, stochastic Runge-Kutta, and stochastic nonstandard finite difference with a delayed sense to visualization of results. In the end, the comparison of the methods is presented to support the efficiency of non-standard methods in the sense of stochastic with delay parameters.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    21100 - Other engineering and technologies

Result continuities

  • Project

    <a href="/en/project/EH23_021%2F0008759" target="_blank" >EH23_021/0008759: Increasing the resilience of power grids in the context of decarbonisation, decentralisation and sustainable socio-economic development</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Scientific Reports

  • ISSN

    2045-2322

  • e-ISSN

  • Volume of the periodical

    15

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    19

  • Pages from-to

    35257

  • UT code for WoS article

    001591494800033

  • EID of the result in the Scopus database

    2-s2.0-105018268141