Projecting high-level dengue increases during low-incidence months in a large endemic urban area.

Background: Climate change projections impact dengue transmission in tropical regions, creating diverse and complex public health challenges. The aim of this study was to project future seasonal dengue incidence in a large tropical urban area of Brazil, where dengue is endemic, by systematically analyzing climatic and dengue case time series.

Methods: An epidemiological dengue model was developed using time series analysis techniques and forced with statistical downscaling from various Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models based on Shared Socioeconomic Pathway (SSP) scenarios for the late twenty-first century (2071-2100). The ecological time-series investigation analyzed 193 618 dengue cases from January 2008 to December 2018. Statistical downscaling transformed low-resolution Global Climate Models' outputs into high-resolution data, based on a 30-y climate baseline.

Results: The results indicated significant climate changes in seasonal temperature and precipitation by the end of the century. Under both SSP2-4.5 and SSP5-8.5 scenarios, substantial increases in dengue cases are projected during current low-incidence months, resulting in a reduced seasonality of dengue.

Conclusions: The findings represent considerable challenges for future public health systems, which may face sustained high levels of dengue incidence throughout the year.