Mathematical modelling of the transmission dynamics of Marburg virus disease with optimal control and cost-effectiveness analysis based on lessons from Ebola virus disease

Marburg virus, like Ebola, causes haemorrhagic disease with high fatality rates. We developed a deterministic SEIRDVT model incorporating vaccination and treatment to study the disease dynamics. Qualitative analysis revealed a backward bifurcation when $R_{0}=1$ , meaning $R_{0} <1$ is insufficient to eradicate the virus. Sensitivity analysis using Latin Hypercube Sampling showed that applying four control measures—screening, prevention, continuous vaccination, and treatment—significantly reduced transmission. The most cost-effective strategy combines prevention, vaccination, and treatment. These findings provide a framework for designing efficient interventions to combat Marburg virus.

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Publication Details

Journal
Advances in Continuous and Discrete Models
Published
2024-10-31
DOI
https://doi.org/10.1186/s13662-024-03833-4
Citations
4
Primary Topic
Viral Infections and Outbreaks Research
Type
article
Field-Weighted Citation Impact
1.56
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article

Mathematical modelling of the transmission dynamics of Marburg virus disease with optimal control and cost-effectiveness analysis based on lessons from Ebola virus disease

Kwame Bonsu, Reindorf Nartey Borkor, Nicholas Kwasi-Do Ohene Opoku, Francis Ohene Boateng et al.
4 citations
Advances in Continuous and Discrete Models
Viral Infections and Outbreaks Research
1.56
article

Mathematical modelling of the transmission dynamics of Marburg virus disease with optimal control and cost-effectiveness analysis based on lessons from Ebola virus disease

Kwame Bonsu, Reindorf Nartey Borkor, Nicholas Kwasi-Do Ohene Opoku, Francis Ohene Boateng, John Amoah-Mensah, Rhoda Afutu, Vida Afosaa
article en
4 citations

Abstract

Marburg virus, like Ebola, causes haemorrhagic disease with high fatality rates. We developed a deterministic SEIRDVT model incorporating vaccination and treatment to study the disease dynamics. Qualitative analysis revealed a backward bifurcation when $R_{0}=1$ , meaning $R_{0} <1$ is insufficient to eradicate the virus. Sensitivity analysis using Latin Hypercube Sampling showed that applying four control measures—screening, prevention, continuous vaccination, and treatment—significantly reduced transmission. The most cost-effective strategy combines prevention, vaccination, and treatment. These findings provide a framework for designing efficient interventions to combat Marburg virus.

Advances in Continuous and Discrete ModelsVol. 2024(1)
Kwame Nkrumah University of Science and Technology (GH), African Institute for Mathematical Sciences Ghana (GH), Sunyani Technical University (GH), Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (GH)
Openalex Percentile: Top 17%
Viral Infections and Outbreaks Research
1.56
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Mathematical modelling of the transmission dynamics of Marburg virus disease with optimal control and cost-effectiveness analysis based on lessons from Ebola virus disease — Kwame Bonsu, Reindorf Nartey Borkor, et al. · Advances in Continuous and Discrete Models (2024) | TGRS Research Map | TGRS