Predicting the spatial dynamics of Wolbachia infections in Aedes aegypti arbovirus vector populations in heterogeneous landscapes

A promising strategy for reducing the transmission of dengue and other arboviral human diseases by Aedes aegypti mosquito vector populations involves field introductions of the endosymbiotic bacteria Wolbachia. Wolbachia infections inhibit viral transmission by the mosquito, and can spread between mosquito hosts to reach high frequencies in the vector population. Wolbachia spreads by maternal transmission, and spread dynamics can be variable and highly dependent on natural mosquito population dynamics, population structure and fitness components. We develop a mathematical model of an A. aegypti metapopulation that incorporates empirically validated relationships describing density-dependent mosquito fitness components. We assume that density dependent relationships differ across subpopulations, and construct heterogeneous landscapes for which model-predicted patterns of variation in mosquito abundance and demography approximate those observed in field populations. We then simulate Wolbachia release strategies similar to that used in field trials. We show that our model can produce rates of spatial spread of Wolbachia similar to those observed following field releases. We then investigate how different types of spatio-temporal variation in mosquito habitat, as well as different fitness costs incurred by Wolbachia on the mosquito host, influence predicted spread rates. We find that fitness costs reduce spread rates more strongly when the habitat landscape varies temporally due to stochastic and seasonal processes. Synthesis and applications: Our empirically based modelling approach represents effects of environmental heterogeneity on the spatial spread of Wolbachia. The models can assist in interpreting observed spread patterns following field releases and in designing suitable release strategies for targeting spatially heterogeneous vector populations.