MATHEMATICAL ANALYSIS OF SENSITIVE PARAMETERS ON THE DYNAMICAL TRANSMISSION OF EBOLA HEMORRHAGIC FEVER

Authors

  • S .O Adewale Departmental of P/AMathematics, LadokeAkintola University of Technology, LAUTECH Ogbomoso. NIGERIA
  • G.A Adeniran Departmental of P/AMathematics, LadokeAkintola University of Technology, LAUTECH Ogbomoso. NIGERIA
  • I .A Olopade Departmental of Mathematics and Computer Science,Elizade University, Ilara-Mokin. NIGERIA
  • I.T Mohammed Department of Mathematics and Stastitics Osun State Polytechnic Iree, NIGERIA

DOI:

https://doi.org/10.29121/granthaalayah.v4.i10.2016.2484

Keywords:

Ebola, Reproduction Number, Stability, Critical Point, Sensitivity, Simulation

Abstract [English]

A four (4) compartmental model of (S, E, I , I ) were presented to have better understanding of parameters that influence the dynamical spread of Ebola in a population. The model is analyzed for all the parameters responsible for the dynamical spread of the disease in order to find the most sensitive parameters that need to be given attention. 


The stability of the model was analyzed for the existence of disease free and endemic equilibrium points. Basic Reproduction Number ( ) was obtained using next generation matrix method (NGM), and it is shown that the disease free equilibrium point is locally asymptotically stable whenever the basic reproduction number is less than unity i.e ( ) and unstable whenever the basic reproduction number is greater than unity ( ).The relative sensitivity indices of the model with respect to each parameter in the basic reproduction number is calculated in order to find the most sensitive parameter which the medical practitioners and policy health makers should work on in order to reduce the spread of Ebola in the population. The result shows that effective contact rate and fraction of individuals with low immunity are the most sensitive parameters in the reproduction number. Therefore, effort should be put in place so that the basic reproduction number should not be greater unity so as to prevent the endemic situation.

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References

Adewale S.O., Olopade I.A., Adeniran G.A., Mohammed I.T and Ajao S.O. (2015): Mathematical Analysis of effects of isolation on Ebola transmission Dynamics. Resarchjournalis. Journal of Mathematics Vol. 2|No 2 February|2015 ISSN2349-5375

Amira R. and Delfin F.M. (2015): Mathematical Modeling, Simulation and Optimal Control of the 2015 Ebola outbreak in West Africa. Discrete Dynamics in Nature and society volume 2015(2015), Article ID 842792, 9 pages. http://dx.doi.org/10.1155/2015/842792 DOI: https://doi.org/10.1155/2015/842792

Breman J.G., Johnson K.M., Van der Groen, G. (1999): A search for Ebola Virus in animals in the Democratic Replubicof thecongo and Cameroon: Ecologic, vivologic, and serologic surveys 1979-1980. J.Inf.Dis.179, S139-S147.

Biek R., Walsh P.D., Leroy E.M., and Real L.A. (2006): Recent Common ancesting of bola Outbreak killed 5000 gorillas. Science Pathogens 2:e90.

Chowell G. and Hengartner N.W. The basic reproduction number of Ebola and the effects of public health measures: the cases of Congo and Uganda J. of theoretical Biology ELSIVIER. Available www.sciencedirect.com.

Centers for Disease Control and Prevention (CDC) (2002): Ebola hermorrhagic fever information packet. Available: http://www.dcd.gov/ncidod/dvrd/spb/mnpages/fact sheets/Ebola_Fact_Booklet.pdf [accessed January 10, 2006]

Centers for Disease Control (CDC) (2003b): Ebola hemorrhagic fever: table showing known cases and outbreaks, in chronological order. (http://www.dcd.gov/ncidod/dvrd/spb/mnpages/dispages/ebotabl.html), accessed on August 24, 2003.

Center for Disease Control and Prevention (2016): Available at www.dcd.gov/vhf/ebola/about.html. [Accessed October 7, 2016

Driessche P. and Watmough J. (2002): Reproduction numbers and sub-threshold endemicequilibrium for compartmental models of disease transmission, Mathematical Bioscience 180, 29-48. DOI: https://doi.org/10.1016/S0025-5564(02)00108-6

Leroy E. M, Kumulungui B, Pourut X, Rouquet P, Hassanin A, and Yaba P. (2005):Fruit bats as reservoirs of Ebola Virus. Nature 438:575-576. DOI: https://doi.org/10.1038/438575a

Leirs H., Mills J.N. and Kerbs J.W. (1999): Search for the Ebola virus reservoir in Kikuit, Democratic Republic of the Congo: reflections on a vertebrate collection. J.Inf. Dis.179, S155-S163.

Lakshmkanthan V., Lela S. and Martynyut A.A. (1989): Stability analysis of Non-Linear System. Marcel Dekker, Inc., New York and Basel.

Rouquet P, Fromen J, Bermejo M, kilboure A, Karesh W, and Reed P, (2005): Wild animal mortality monitoring and human Ebola Outbreaks, Gabon and Republic of Congo, 2001-2003. Emerging Infectious Diseases 11:283-290. DOI: https://doi.org/10.3201/eid1102.040533

World Health Organization (WHO), 2003a. Ebola hemorrhagic fever: disease outbreaks. (http://www.who/int/disease-outbreak-news/disease/A98.4.html)[Accessed October 17, 2003]

World Health Organization (2016): Ebola virus disease Fact sheet. Available at www.who.int/mediacentre/factsheets/fs103/en/. [Accessed October 9, 2016]

World Health Organization (WHO), 2003b. Ebola hemorrhagic fever. (http://www.who.int/inf-fs/en/fact103.html), [Accessed August 24, 2003]

Zack Yarus (2012): A mathematical look at Ebola Virus. May 11, 2012.

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Published

2016-10-31

How to Cite

Adewale, Adeniran, Olopade, & Mohammed. (2016). MATHEMATICAL ANALYSIS OF SENSITIVE PARAMETERS ON THE DYNAMICAL TRANSMISSION OF EBOLA HEMORRHAGIC FEVER. International Journal of Research -GRANTHAALAYAH, 4(10), 21–33. https://doi.org/10.29121/granthaalayah.v4.i10.2016.2484