Sustainable COVID-19 control measures: a mathematical modelling study

Salman, Amer M. and Mohd Hafiz Mohd, . (2024) Sustainable COVID-19 control measures: a mathematical modelling study. Journal of Sustainability Science and Management (Malaysia), 19 (6). pp. 25-35. ISSN 2672-7226

Mathematical modelling techniques have become essential in predicting the consequences of viral disease outbreaks and in planning sustainable preventative measures to curb their transmission dynamics. To better understand the sustainable evolution of the control measures’ impacts on the COVID-19 transmissions, a reaction-diffusion system is employed to describe the epidemiological phenomenon through two processes: (i) a reaction process of SEIRS-type (Susceptible, Exposed, Infected, Recovered, and Susceptible) kinetics; (ii) a diffusion process that models local dispersal of individuals through the incorporation of spatial dimension. Optimal control theory and numerical simulation studies are performed to examine the combined effects of reinfection, spatial dispersal process, and distinct control measures on the severity of the outbreaks. The results indicate the effectiveness of implementing adequate control measures vaccination and treatments to prevent further disease outbreaks and minimise the number of infected cases. The insights from these modelling studies benefit different stakeholders, e.g., public health practitioners and policymakers in devising sustainable COVID-19 management plans to prepare for endemicity and deal with large-scale disease outbreaks in the future.

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Abstract

Mathematical modelling techniques have become essential in predicting the consequences of viral disease outbreaks and in planning sustainable preventative measures to curb their transmission dynamics. To better understand the sustainable evolution of the control measures’ impacts on the COVID-19 transmissions, a reaction-diffusion system is employed to describe the epidemiological phenomenon through two processes: (i) a reaction process of SEIRS-type (Susceptible, Exposed, Infected, Recovered, and Susceptible) kinetics; (ii) a diffusion process that models local dispersal of individuals through the incorporation of spatial dimension. Optimal control theory and numerical simulation studies are performed to examine the combined effects of reinfection, spatial dispersal process, and distinct control measures on the severity of the outbreaks. The results indicate the effectiveness of implementing adequate control measures vaccination and treatments to prevent further disease outbreaks and minimise the number of infected cases. The insights from these modelling studies benefit different stakeholders, e.g., public health practitioners and policymakers in devising sustainable COVID-19 management plans to prepare for endemicity and deal with large-scale disease outbreaks in the future.

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Item Type:	Article
AGROVOC Term:	COVID-19
AGROVOC Term:	pandemics
AGROVOC Term:	public health
AGROVOC Term:	mathematical models
AGROVOC Term:	disease surveillance
AGROVOC Term:	viruses
AGROVOC Term:	human population
AGROVOC Term:	disease control
AGROVOC Term:	risk management
Geographical Term:	Malaysia
Depositing User:	Mr. Khoirul Asrimi Md Nor
Date Deposited:	09 Apr 2025 01:14
Last Modified:	09 Apr 2025 01:14
URI:	http://webagris.upm.edu.my/id/eprint/2547

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