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Mathematical models to optimize pandemic spread and control strategies in public health management

Uma BhardwajDepartment of Biotechnology and Microbiology, Noida International University, Greater Noida, Uttar Pradesh, 203201, IndiaShirish Jaysing NavaleDepartment of Mechanical Engineering, AISSMS College of Engineering, Pune, Maharashtra, 411001, IndiaAkshita ChanchlaniDepartment of Computer Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, 411038, IndiaS. D. MurtuzaDepartment of Computer Engineering, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, 411038, IndiaDebarshita DeySymbiosis Law School Pune (SLS-P), Symbiosis Centre for Advanced Legal Studies and Research (SCALSAR), Symbiosis International (Deemed University), Pune, Maharashtra, 411014, IndiaEgambergan XudaynazarovDepartment of General Professional Sciences, Mamun University, Khiva, 220900, UzbekistanNavneet JoshiDepartment of Mathematics, Bhimtal Campus, Graphic Era Hill University, Nainital, Uttarakhand, 263136, India

2026en

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ABI

Annotatsiya

This paper presents mathematical models that may be applied to enhance the management of the health of the population and prevent pandemics. It is based on compartmental models such as SEIR and control variables such as the vaccine, quarantine, and social isolation to model disease spread and the effectiveness of interventions. Dynamic programming and optimal control theory are optimisation techniques that are applied to identify the optimal reaction plans. The outcomes of the simulation indicate that there are significant decreases in the rate of reduction of the number of infections and consumption of resources. The proposed models provide the lawmakers with practical information that can be applied to them in times of outbreak and pandemic scenarios to make timely and data-driven decisions.

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DOI: 10.47974/jim-2494

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