A progressive increase in vector-borne infectious diseases is expected in the face of climate variability exacerbated by climate change. Tropical climate conditions favor the proliferation of Aedes aegypti , causing greater risk of dengue spreading. Therefore, taking action to adapt health systems to climate change is a priority. The objective of this study is to determine the geographic distribution of dengue and to projecti its potential changes associated with the impact of climate variability and change.

An ecological study conducted by combining time series and spatial statistics was undertaken. Entomological and epidemiological information, ecological niche data and climatic indicators were considered. Kriging and Co-kriging methods were used for interpolation and to obtain a 20 × 20 km grid. Moran’s I and bivariate index were calculated to determine the influence of climate on the variables. Local Moran’s I was applied to determine the clusters. Projections were made for the SSP2 RCP4.5 and SSP5 RCP8.5 scenarios using the mixed-regressive-spatial-autoregressive model.

Geographic distribution maps of dengue were generated, showing seasonal patterns and high circulation during the rainiest and warmest months. A strong spatial association between health indicators and climate pattern was evident. Maps of the dengue and Aedes aegypti scenarios were generated for 2050.

Climate ´s effect on dengue geographic distribution and its transmitting vector was evident. The Mixed-Regressive-Spatial-Autoregressive models are suitable for determining projections, which receive different levels of impact under climate change conditions. These models demonstrate their usefulness in epidemiological surveillance, early warning, and adaptation actions based on vulnerability levels.