<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-interdisciplinary-mathematics</journal-id>
      <journal-title-group>
        <journal-title>Journal of Interdisciplinary Mathematics</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-012X</issn>
      <issn publication-format="print">0972-0502</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JIM-2834</article-id>
      <title-group>
        <article-title>Dynamical systems modeling for epidemic spread and control</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Datkhile</surname>
            <given-names>Kailas</given-names>
          </name>
          <aff>Department of Molecular Biology and Genetics Laboratory, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, Maharashtra, 415539, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jani</surname>
            <given-names>Mrudul Y.</given-names>
          </name>
          <aff>Department of Applied Sciences and Humanities, Faculty of Engineering and Technology, Parul University, Vadodara, Gujarat, 391760, India</aff>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Deepthi</surname>
            <given-names>S.</given-names>
          </name>
          <aff>Presidency School of Computer Science and Engineering, Presidency University, Bangalore, Karnataka, 560119, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jayapalan</surname>
            <given-names>Senthil</given-names>
          </name>
          <aff>Department of Mechanical Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation (Deemed to be University), Chennai, Tamil Nadu, 603104, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Anandhi</surname>
            <given-names>D.</given-names>
          </name>
          <aff>Department of Biochemistry, Meenakshi Ammal Dental College &amp; Hospital, Meenakshi Academy of Higher Education &amp; Research, Chennai, Tamil Nadu, 600087, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Dewangan</surname>
            <given-names>Deo Narayan</given-names>
          </name>
          <aff>Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Rungta International Skills University, Bhilai, Chhattisgarh, 490024, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Selvamalar</surname>
            <given-names>N.</given-names>
          </name>
          <aff>Department of Mathematics, Aditya University, Surampalem, Andhra Pradesh, 533437, India</aff>
        </contrib>
      </contrib-group>
      <volume>29</volume>
      <issue>10</issue>
      <fpage>3245</fpage>
      <lpage>3256</lpage>
      <pub-date date-type="pub">
        <day>27</day>
        <month>10</month>
        <year>2026</year>
      </pub-date>
      <abstract>
        <p>Epidemic outbreaks are characterized by complex nonlinear dynamics, with the effects of transmission, recovery, population interactions and interventions. This study introduces a framework for the modelling of epidemics and its assessment of disease control mechanisms based on dynamical systems. The susceptible, exposed, infected and recovered populations are modeled using coupled nonlinear differential equations. A time-varying transmission and recovery rates are indicative of changes in the contact patterns, health care response and control measures. To determine the long-term epidemic behavior, disease-free and endemic equilibrium points are determined. Stability analysis offers insight into about conditions necessary for the elimination of a disease or for its persistence. The framework facilitates assessment of transmission reduction, recovery enhancement, and epidemic stability and offers a flexible mathematical basis to learn about outbreaks and to devise effective public health control measures and policies.</p>
      </abstract>
      <kwd-group>
        <kwd>Epidemic modeling</kwd>
        <kwd>Dynamical systems</kwd>
        <kwd>Nonlinear differential equations</kwd>
        <kwd>SEIR model</kwd>
        <kwd>Stability analysis</kwd>
        <kwd>Disease control</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
