Predictive Modeling and Control Strategies for the Transmission of Middle East Respiratory Syndrome Coronavirus

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dc.contributor.authorFatima, Bibi
dc.contributor.authorYavuz, Mehmet
dc.contributor.authorRahman, Mati Ur
dc.contributor.authorAlthobaiti, Ali
dc.contributor.authorAlthobaiti, Saad
dc.date.accessioned2024-02-23T14:35:14Z
dc.date.available2024-02-23T14:35:14Z
dc.date.issued2023
dc.departmentNEÜen_US
dc.description.abstractThe Middle East respiratory syndrome coronavirus (MERS-CoV) is a highly infectious respiratory illness that poses a significant threat to public health. Understanding the transmission dynamics of MERS-CoV is crucial for effective control and prevention strategies. In this study, we develop a precise mathematical model to capture the transmission dynamics of MERS-CoV. We incorporate some novel parameters related to birth and mortality rates, which are essential factors influencing the spread of the virus. We obtain epidemiological data from reliable sources to estimate the model parameters. We compute its basic reproduction number (R0). Stability theory is employed to analyze the local and global properties of the model, providing insights into the system's equilibrium states and their stability. Sensitivity analysis is conducted to identify the most critical parameter affecting the transmission dynamics. Our findings revealed important insights into the transmission dynamics of MERS-CoV. The stability analysis demonstrated the existence of stable equilibrium points, indicating the long-term behavior of the epidemic. Through the evaluation of optimal control strategies, we identify effective intervention measures to mitigate the spread of MERS-CoV. Our simulations demonstrate the impact of time-dependent control variables, such as supportive care and treatment, in reducing the number of infected individuals and controlling the epidemic. The model can serve as a valuable tool for public health authorities in designing effective control and prevention strategies, ultimately reducing the burden of MERS-CoV on global health.en_US
dc.description.sponsorshipThe researchers would like to acknowledge Deanship of Scientific Research, Taif University for funding this work.; Deanship of Scientific Research, Taif Universityen_US
dc.description.sponsorshipThe researchers would like to acknowledge Deanship of Scientific Research, Taif University for funding this work.en_US
dc.identifier.doi10.3390/mca28050098
dc.identifier.issn1300-686X
dc.identifier.issn2297-8747
dc.identifier.issue5en_US
dc.identifier.urihttps://doi.org/10.3390/mca28050098
dc.identifier.urihttps://hdl.handle.net/20.500.12452/15940
dc.identifier.volume28en_US
dc.identifier.wosWOS:001089377300001en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofMathematical And Computational Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMers-Cov Modelen_US
dc.subjectBasic Reproductive Numberen_US
dc.subjectAnalysis Of Stabilityen_US
dc.subjectEquilibria Pointsen_US
dc.subjectOptimality Controlen_US
dc.subjectNumerical Analysisen_US
dc.titlePredictive Modeling and Control Strategies for the Transmission of Middle East Respiratory Syndrome Coronavirusen_US
dc.typeArticleen_US

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