A Causal-based Analysis on the Role of Seasonal Climate Patterns in Aedes-borne Disease Transmission

Background: Vector-borne diseases transmitted by Aedes mosquitoes such as dengue, Zika, and chikungunya pose significant public health challenges worldwide in the wake of climate change. However, while their transmission is related to specific temperature, rainfall or humidity conditions, the overall role of large-scale climate drivers on the emergence of these diseases is not so well understood. Establishing the most important timeframes for Aedes-borne disease prediction and identifying specific climate patterns that drive its emergence can be key in the development of climate-based prediction systems for these arboviruses.&nbsp; <div> <br> </div> <div> Methods: The response of the climate component of Aedes-borne disease transmission to large-scale climate patterns is explored through their respective climate variability indices. A preliminary timescale decomposition analysis assesses the primary timescales over which climate processes condition disease transmissibility, while later correlation and causality analyses identify the most relevant climate drivers for Aedes-borne diseases.&nbsp; </div> <div> <br> </div> <div> Findings: Year-to-year variations in temperature and precipitation have a significant impact on the environmental suitability for Aedes-borne diseases in the tropics, whereas seasonal fluctuations have a stronger impact in temperate regions instead. Overall, while some climate indices such as Niño 3.4, Tropical North Atlantic and the Indian Ocean Basin Mode stand out as modulators of climate-driven disease risk, it is the effect of multiple climate patterns, through compound interactions, that ultimately shape climate-based transmission dynamics.&nbsp; </div> <div> <br> </div> <div> Interpretation: Aedes-borne disease transmission is susceptible to multiple climate factors, including long-term climate change and seasonal variability. The results of this study highlight the multi-faceted role of climate patterns in disease emergence, and their potential applicability in the development of climate-based early warning systems for Aedes-borne disease outbreaks. These findings can be integrated into an actionable disease prediction system using multiple climate patterns as predictors, which can ultimately better inform public health strategies to manage outbreaks. </div>