Modelling In uenza Dynamics with Drug Resistance Aspect

Journal Title: Journal of Advances in Mathematics and Computer Science - Year 2017, Vol 25, Issue 3

Abstract

Despite improvement in medical and public health standards, in uenza continues to plague humankind causing high morbidity,mortality and socio-economic cost. E orts to e ectively combat the spread of in uenza can be put in place if its dynamics are well understood. Numerous challenges have been faced in the event of controlling the spread and eradicating this contagious disease, a major impediment being the rise of drug resistance. In light of this, a deterministic model is formulated and used to analyze the transmission dynamics of in uenza having incorporated the aspect of drug resistance. A system of di erential equations that models the transmission dynamics of in uenza is developed. The e ective reproduction number (Re) and the basic reproduction number (R0) are calculated.For this model,there exists at least four equilibrium points. The stability of the disease free equilibrium point and endemic equilibrium point is analyzed. Results of the analysis show that there exists a locally stable disease free equilibrium point, E0 when Re < 1 and a unique endemic equilibrium E  , when Re > 1. Sensitivity analysis is carried out to determine parameters that should be targeted by intervention strategies. The e ect of drug resistance and transmission rate of the resistant strain on the infected and the recovered is discussed.Results show that development of drug resistance and transmission of the resistant strain result in widespread of the resistant strain. A decrease in either of these two factors leads to a signi cant reduction in the number of infected individuals,hence, social distancing can be used as an intervention mechanism to curb the spread of the resistant strain.

Authors and Affiliations

Caroline W. Kanyiri, Mark Kimathi, L. S. Luboobi

Keywords

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  • EP ID EP322553
  • DOI 10.9734/JAMCS/2017/37442
  • Views 95
  • Downloads 0

How To Cite

Caroline W. Kanyiri, Mark Kimathi, L. S. Luboobi (2017). Modelling In uenza Dynamics with Drug Resistance Aspect. Journal of Advances in Mathematics and Computer Science, 25(3), 1-19. https://europub.co.uk./articles/-A-322553