Malaria is a deadly infectious disease causing over 200 million cases and over half a million deaths each year. It is transmitted through the bite of an infectious Anopheles mosquito. Control methods, primarily focused on affecting the ability of the mosquito to bite or transmit the disease by employing insecticides, have reduced the impact of malaria. However, in the past decade, due to an increase in insecticide resistance, new control methods are urgently needed. One proposed strategy is the use of Wolbachia, a natural bacterium that can infect mosquitoes and reduce their ability to transmit diseases. While initially discovered in the context of shortening the life span of the mosquitoes that transmit dengue, researchers are interested in its potential for malaria control. In this study, we develop and analyze a novel mathematical model to assess the use of Wolbachia-based strategies for malaria control. The model combines the complicated transmission dynamics of Wolbachia within the mosquito population along with transmission of malaria in the human population, while specifically tracking dynamical immunity feedback. Our findings reveal bifurcations in both Wolbachia transmission among mosquitoes and malaria transmission in humans, suggesting the potential for malaria elimination through Wolbachia-based interventions. We perform sensitivity analysis to identify the important parameters of the model for malaria reduction and elimination. To assess the potential for Wolbachia-based control of malaria, we use numerical simulations combining Wolbachia and other malaria control strategies aimed at humans. Our results suggest combining Wolbachia control of mosquitoes with reductions of malaria in the human population leads to the greatest reduction in total days of infection and the least rebound in malaria prevalence. This is joint work with Zhuolin Qu at the University of Texas, San Antonio.

Meeting ID: 924 1000 5098 Passcode: 288986