Computational Modelling and Optimal Control of Ebola Virus Disease with non-Linear Incidence Rate

The 2014 Ebola outbreak in West Africa has exposed the need to connect modellers and those with relevant data as pivotal to better understanding of how the disease spreads and quantifying the effects of possible interventions. In this paper, we model and analyse the Ebola virus disease with non-line...

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Bibliographic Details
Published in:Journal of physics. Conference series 2017-03, Vol.818 (1), p.12003
Main Authors: Takaidza, I., Makinde, O. D., Okosun, O. K.
Format: Article
Language:English
Subjects:
Disease control
Ebola virus
Epidemics
Optimal control
Parameter sensitivity
Physics
Sensitivity analysis
Uncertainty analysis
Viral diseases
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Summary:The 2014 Ebola outbreak in West Africa has exposed the need to connect modellers and those with relevant data as pivotal to better understanding of how the disease spreads and quantifying the effects of possible interventions. In this paper, we model and analyse the Ebola virus disease with non-linear incidence rate. The epidemic model created is used to describe how the Ebola virus could potentially evolve in a population. We perform an uncertainty analysis of the basic reproductive number R0 to quantify its sensitivity to other disease-related parameters. We also analyse the sensitivity of the final epidemic size to the time control interventions (education, vaccination, quarantine and safe handling) and provide the cost effective combination of the interventions.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/818/1/012003