Vaccination effect on the dynamics of dengue disease transmission models in Nepal: A fractional derivative approach

Abstract

Dengue is a vector-borne disease which is spreading rapidly around the world. It is one of the fastly growing public health problems in Nepal. Since 2004, dengue cases have been recorded in both tropical and subtropical regions of Nepal. There is no specific treatment for the dengue disease, which is brought on by the dengue virus. This study attempts the use of the Caputo fractional-order derivative to suggest SVEIRP-SEI epidemic model that integrates vaccination and hospitalization in order to precisely analyze the transmission of dengue infection phenomena. The existence and uniqueness are discussed for the model solutions. Basic reproduction number R0with vaccination is formulated using next generation matrix. Both the local and global stability of disease free and endemic equilibrium points are explored. The parameters are estimated from the actual outbreak of infected cases in Nepal. Sensitivity analysis is then presented graphically with appropriate memory index ψ. The findings of the mathematical and simulation results demonstrate that vaccination is one of the effective strategies that lowers the prevalence of the disease significantly.

Keywords

• Caputo fractional-order derivative
• Sensitivity analysis
• Stability
• Parameter estimation with real data
• Graphical results