American Journal of Applied Mathematics and Statistics
ISSN (Print): 2328-7306 ISSN (Online): 2328-7292 Website: Editor-in-chief: Mohamed Seddeek
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American Journal of Applied Mathematics and Statistics. 2018, 6(3), 96-106
DOI: 10.12691/ajams-6-3-2
Open AccessArticle

Queueing Based Compartmental Models for Ebola Virus Disease Analysis

Ikeme John Dike1, and Chinyere Ogochukwu Dike2

1Department of Statistics & Operations Research, Modibbo Adama University of Technology, P.M.B 2076, Yola, Adamawa State, Nigeria

2Federal College of Education P.M.B 2042, Yola, Adamawa State, Nigeria

Pub. Date: June 13, 2018

Cite this paper:
Ikeme John Dike and Chinyere Ogochukwu Dike. Queueing Based Compartmental Models for Ebola Virus Disease Analysis. American Journal of Applied Mathematics and Statistics. 2018; 6(3):96-106. doi: 10.12691/ajams-6-3-2


Ebola Virus Disease (EVD) is a complex and unprecedented epidemic killer disease. Recently, the disease has caused serious loss of life, waste of economic and material resources in West African nations. The most prevalent countries are Guinea, Liberia and Sierra Leone. Compartmental models are traditional epidemiological mdels that try to explain epidemic problems through the use of specific compartments that are subsets of a given population. Analysis using the developed queueing based compartmental models for Ebola Virus Disease (EVD) resulted in estimates of R0= (2.2550, 3.5264, 2.2325) for Guinea, Liberia and Sierra Leone. R0 > 1 for each of the countries, implying that the transmission and control of the epidemic was unstable and needed urgent intervention. The developed SEILICDR model outperformed the existing SEIR model by 13.10%, 91.76%, and 83.14%, respectively on the basis of their RMSE. Finally, analysis using queueing in SEILICDR compartmental models led to the discovery that, at a probability of 0.4 in each compartment, the transmission of EVD can be controlled.

Ebola Virus Disease epidemic comparmental model transmission control queueing

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