Understanding the role of sexual transmission in the spread of ZIKA virus using an individual-based interconnected population model

Abstract

Zika virus has affected the world as a long-term threat. Modeling its transmission is important in order to facilitate forecasts and control measures. We propose a novel node-based interconnected population model to simulate both vectored and sexual transmission of Zika virus. Using a sexual contact network, we incorporate heterogeneous mixing in the host population with stochastic transmission for realistic predictions. We also incorporate climatic variations in our model, which affect the mosquito vector population and consequently the arbovirus transmission. We perform extensive simulations to understand the effects of sexual transmission rate and network topology on the spreading of infections. Sexual transmission contributes to the epidemic spread and under certain conditions, can sustain it up to several months without vectors. This can potentially lead to recurrences once the mosquitoes overwinter. We also find that sexual transmission can have a stronger effect when vectored transmission is relatively weaker due to climatic conditions. Our results show that vectored and sexual transmission affect the disease dynamics differently.