Dynamical systems modeling for epidemic spread and control
Kailas Datkhilekddatkhile@gmail.comDepartment of Molecular Biology and Genetics LaboratoryKrishna Vishwa Vidyapeeth (Deemed to be University)Karad, Maharashtra, 415539, IndiaView full profile → , Mrudul Y. Janimrudul.jani@paruluniversity.ac.inDepartment of Applied Sciences and HumanitiesFaculty of Engineering and TechnologyParul UniversityVadodara, Gujarat, 391760, IndiaView full profile → , *S. DeepthiCorresponding authorId-deepthi.s@presidencyuniversity.inPresidency School of Computer Science and EngineeringPresidency UniversityBangalore, Karnataka, 560119, IndiaView full profile → , Senthil Jayapalansenthiljayapalan@gmail.comDepartment of Mechanical EngineeringAarupadai Veedu Institute of TechnologyVinayaka Mission’s Research Foundation (Deemed to be University)Chennai, Tamil Nadu, 603104, IndiaView full profile → , D. Anandhianandhid@maher.ac.inDepartment of BiochemistryMeenakshi Ammal Dental College & HospitalMeenakshi Academy of Higher Education & ResearchChennai, Tamil Nadu, 600087, IndiaView full profile → , Deo Narayan Dewangandnd@rungta.orgDepartment of Computer Science and EngineeringRungta College of Engineering and TechnologyRungta International Skills UniversityBhilai, Chhattisgarh, 490024, IndiaView full profile → , N. Selvamalarn.selvamalar@adityauniversity.inDepartment of MathematicsAditya UniversitySurampalem, Andhra Pradesh, 533437, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2026
- Published Online:
- 27 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIM-2834
- Pages:
- 3245–3256
Abstract
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.
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References
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