Mathematical Assessment of the Impact of Vaccination and Personal Protection on the Dynamical Transmission of Avian Influenza A (H7N9)

EasyChair Preprint 4558

Abstract

In this article, we investigate the impact of vaccination and personal protection on the dynamical transmission of avian influenza A (H7N9) within a human community. We propose a mathematical model for the dynamical transmission of AI which integrates the key epidemiological and biological features of AI such as vaccine efficacy and the efficiency of personal protection. We provide a theoretical study of the model. We derive the basic reproduction number R0 which determines the extinction and persistence of the disease. We show that the disease-free equilibrium is globally asymptotically stable whenever R0 ≤ 1, while when R0 > 1, the disease-free equilibrium is unstable and there exists an endemic equilibrium point which is locally or globally (depending on the case) asymptotically stable on a positively invariant region of the positive orthant. The sensitivity analysis of the model has been performed in order to determine the impact of related parameters on outbreak severity. Theoretical results are supported by numerical simulations, which further demonstrate that some proposed control strategies will not lead to disease eradication, however, if we only employ vaccination, it will require slightly longer to eradicate the disease than applying a combination of pharmaceutical (vaccination) and non-pharmaceutical (personal protection) control methods. In conclusion, it is important to adopt a combination of control methods to fight an avian influenza outbreak.

Keyphrases: Avian Influenza, mathematical models, personal protection, sensitivity analysis, stability, vaccination

@booklet{EasyChair:4558,
  author    = {Calvin Tadmon and Berge Tsanou and Arnaud Fossi Feukouo},
  title     = {Mathematical Assessment of the Impact of Vaccination and Personal Protection on the Dynamical Transmission of Avian Influenza A (H7N9)},
  howpublished = {EasyChair Preprint 4558},
  year      = {EasyChair, 2020}}