Numerical Simulations of Vaccination and Wolbachia on Dengue Transmission Dynamics in the Nonlinear Model

In this study, it is indicated that the world can get rid of the dengue virus by using vaccines and Wolbachia. In many findings, it is observed that Wolbachia therapy is efficacious in those regions that display the minimal to moderate the transmission level. On the contrary, vaccination is highly successful when used in serologically persons and places with large transmission levels. The resilience of stochastic methodology based on the numerical computing schemes will be used to exploit the artificial neural networks (ANNs) modelling legacy, as well as the metaheuristic intelligence using the hybrid of global and local search schemes thru genetic algorithms (GAs) and active-set method (ASA). The combination of both strategies is used to manage the numerical therapies of the mathematical form of the dengue model. The optimal control results through GA-ASA can be retrieved by offering an error-based fitness function generated for dengue model represented via nonlinear systems of equations. The acquired findings are compared to the Adams numerical results to ensure that the suggested stochastic system is accurate. For determining convergence, the training contours are based on various contact rate values. Furthermore, the statistical achievements of the suggested stochastic scheme to solve the novel developed dengue model, which demonstrate the stability and dependability of the dynamical system scheme.

Automated summary

This study suggests that the dengue virus can be eliminated through the use of vaccines and Wolbachia. Wolbachia therapy is effective in regions with minimal to moderate transmission levels, while vaccination is successful in areas with high transmission levels and serologically strong individuals. A combination of stochastic methodology and artificial intelligence algorithms can be used to optimize the numerical therapies for the mathematical form of the dengue model.