AI- modelling of molecular identification and feminization of wolbachia infected Aedes aegypti.

BACKGROUND The genetic control strategies of vector borne diseases includes the replacement of a vector population by "disease-refractory" mosquitoes and the release of mosquitoes with a gene to control the vector's reproduction rates. Wolbachia are common intracellular bacteria that are found in arthropods and nematodes. Wolbachia infected male mosquitos have been used in different experimental trials around the world to suppress the target population of Aedes aegypti and this genetic control strategy has proved to be a promising alternative to other treatment strategies. Due to certain limitations, the successful application of this strategy is still awaited. METHODS Mathematical frame work for Wolbachia induced genetic control strategy has been developed in this article. With the aid of Artificial Intelligence (AI) tools, accurate parametric values are depicted. For the first time, the model is well synchronized with the experimental findings. The model is comprised of the generalized varying coefficient and multiple mating rates between infected and uninfected compartments of Aedes aegypti dengue to forecast the disease control. RESULTS Two mathematical models are developed in this article to demonstrate different mating rates of the genetic control strategy. The important parameters and time varying coefficients are well demonstrated with the aid of numerical computations. The resulting thresholds and forecasting may prove to be a useful tool for future experimental studies. CONCLUSIONS From our analysis, we have concluded that the genetic control strategy is a promising technique and the role of Wolbachia infected male mosquitos, in genetic control strategies, can be better interpreted in an inexpensive manner with the aid of a theoretical model.