Using simulation models to understand mosquito-Wolbachia interactions

Mathematical and computer simulation models are remarkable resources for understanding and predicting insect population dynamics in response to human control efforts. Developing generic and/or detailed models allow scientists and regulators to conduct hypothesis driven research with a priori expectations concerning the behavior of impacted systems. Wolbachia pipientis is an intracellular bacterium that manipulates the reproduction of its host while also causing behavioral and physiological changes. Furthermore, Wolbachia can limit infection by pathogens in disease vectors. Here, a computer simulation model was developed to better understand the effects of Wolbachia invasions on mosquito populations. We built a hybrid model that combines deterministic and individual-based components to accurately describe a generic holometabolous insect. The model was designed for optimal flexibility while allowing high-level detail in all lifestages. The model was used to determine the probability of population replacement by Wolbachia into Aedes mosquito populations. Populations were initialized with no resident infection, then Wolbachia infections were introduced into the population at different rates. Parameters affecting Wolbachia infections were varied. The model was later modified to compare multiple Wolbachia infection types. In both cases, the model predicts that the costs associated Wolbachia infection dictates population replacement. Specifically, Wolbachia infections that are pathogenic to immature mosquitoes were identified as relatively poor invaders. The results provide testable hypotheses for future laboratory and field trials. Results are discussed in reference to ongoing control strategies for disease vectors.