×

An Ebola model with hyper-susceptibility. (English) Zbl 1490.92115

Summary: The Ebola Virus Disease is a zoonosis whose reservoir is fruit bats among other primates. Once the virus enters a human population from its supposed zoonotic reservoir, it can then spread through contact with infected persons or their body fluids. The people that are most susceptible to infection are close relatives of infected persons, healthcare givers and those dealing with deceased persons. We classify these people as being hyper-Susceptible and develop a mathematical model to study the impact of hyper-Susceptibility on the dynamics of Ebola virus disease outbreak. The model is shown to have a globally stable disease-free equilibrium point whenever the basic reproduction number \(\mathcal{R}_0\) is less than unity. The model is also shown to exhibit forward bifurcation, which suggests the possibility of eradication through keeping \(\mathcal{R}_0\) below unity. Disease spread is also shown to be highly sensitive to contact rate, transmission probability, death rate and hyper-Susceptibility. Numerical simulation of the model is also done to confirm the analytical results established.

MSC:

92D30 Epidemiology
37N25 Dynamical systems in biology
Full Text: DOI

References:

[1] Organization WH. Frequently asked questions on Ebola virus disease. 2016. http://www.who.int/csr/disease/ebola/faq-ebola/en/.
[2] Bornaa, C. S.; Seidu, B.; Daabo, M. I., Mathematical analysis of rabies infection, J Appl Math, 2020, 1-17 (2020) · Zbl 1442.92156
[3] Asamoah, J. K.K.; Oduro, F. T.; Bonyah, E.; Seidu, B., Modelling of rabies transmission dynamics using optimal control analysis, J Appl Math, 2017, 1-23 (2017) · Zbl 1437.92109
[4] Baloba, E. B.; Seidu, B.; Bornaa, C. S., Mathematical analysis of the effects of controls on the transmission dynamics of anthrax in both animal and human populations, Comput Math Methods Med, 2020, 1-14 (2020) · Zbl 1507.92084
[5] Bornaa, C. S.; Seini, Y. I.; Seidu, B., Modelling zoonotic diseases with treatment in both human and animal populations, Commun Math Biol Neurosci, 2017, 1-21 (2017)
[6] Agusto, F. B.; Teboh-Ewungkem, M. I.; Gumel, A. B., Mathematical assessment of the effect of traditional beliefs and customs on the transmission dynamics of the 2014 Ebola outbreaks, BMC Med, 13, 1-17 (2015)
[7] Sule, A.; Lawal, J., Mathematical modeling and optimal control of Ebola virus disease (EVD), Ann Res Rev Biol, 22, 2, 1-11 (2018)
[8] Ivorra, B.; Ngom, D.; Ramos, A. M., A mathematical model to predict the risk of human diseases spread between countriesvalidation and application to the 20142015 Ebola virus disease epidemic, Bull Math Biol, 77, 1668-1704 (2015) · Zbl 1339.92085
[9] Chen, X. Y.L. C.J., Permanence and positive periodic solution for the single-species nonautonomous delay diffusive models, Comput Math Appl, 32, 109-116 (1996) · Zbl 0873.34061
[10] Hethcote, H. W., The mathematics of infectious diseases, SIAM Rev, 42, 4, 599-653 (2000) · Zbl 0993.92033
[11] Shuai, P.; van den Driessche, Z., Global stability of infectious disease models using Lyapunov functions, SIAM J Appl Math, 73, 1513-1532 (2013) · Zbl 1308.34072
[12] LaSalle, J., Stability theory for ordinary differential equations, J Differ Equ, 4, 57-65 (1968) · Zbl 0159.12002
[13] Marino, S.; Hogue, I. B.; Ray, C. J.; Kirschner, D. E., A methodology for performing global uncertainty and sensitivity analysis in systems biology, J Theor Biol, 254, 1, 178-196 (2008) · Zbl 1400.92013
[14] Castillo-Chavez, C.; Song, B., Dynamical models of tuberculosis and their applications, Math Biosci Eng, 1, 2, 361-404 (2004) · Zbl 1060.92041
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.