Probabilistic joint seasonal dengue and chikungunya forecasting in Brazil

Dengue and chikungunya are mosquito-borne viruses, which have been spreading into new parts of the world in recent years. They are both transmitted by the same two species of day-biting mosquitoes, Aedes aegypti and Aedes albopictus. With enough advanced notice, dengue and chikungunya outbreaks can be mitigated. As a climate-sensitive disease, environmental conditions and past patterns of dengue and chikungunya can be used to make predictions about future outbreak risk. These predictions improve public health planning and decision-making to ultimately reduce the burden of disease. For this project we partnered with Dr Leonardo Soares Bastos to develop a new method, inspired by the work in Colón-González et al (2021) and Pavani et al. (2023). Rowan will extend the method to model bivariate data and apply the model to the forecasting of dengue and chikungunya in Brazil. These two diseases are closely related, they share the same vector and the initial symptoms are very similar. Therefore the development of a joint model ensures borrowing strength over the two outcomes and will lead to more accurate predictions for both diseases