Inferencing the vector competence of Aedes mosquitoes incorporating environmental impact on dengue infection risk

Abstract Background: For decades, dengue has posed a significant threat as a viral infectious disease, affecting numerous lives, yet no cure has been discovered. Genetic traits are often challenging to quantify and particularly susceptible to environmental fluctuations. Assessing genetic traits such as the vector competence of Aedes mosquitoes, which enable transmitting dengue among humans, presents obstacles and is notably sensitive to climate variations, especially considering their probability to flourish in tropical regions of the world. Methods: In this study, we attempt, for the first time in a non-laboratory setting, to quantify the vector competence of Aedes mosquitoes using an existing mathematical model, originally developed for malaria, in a Bayesian inferencing setup. We conducted this study in the Colombo district of Sri Lanka where the highest number of populations are threatened with dengue. Results: Our research successfully deduced vector competence values for each identified season within a year. These estimated values have been corroborated through experimental studies documented in the literature, thereby validating the malaria model for dengue disease. Conclusion: Our research findings conclude that environmental conditions can amplify vector competence within specific seasons, categorized by their environmental attributes. Additionally, the deduced vector competence offers compelling evidence that it impacts disease