Raster layers of bioclimatic, environmental, and anthropogenic variables in a metropolitan area of Mexico City

Mexico is considered both endemic and hyperendemic for the transmission of arboviruses. Since the 1970s, the highest burden of dengue transmission has been observed in coastal areas, coinciding with the distribution of the vectors. Currently, climate change is favoring the establishment of the vector and transmission of viruses in non-endemic areas with warm temperatures and altitudes greater than 1800 m above sea level.

During the 2023 and 2024 dengue serotype 3 epidemic outbreaks in Mexico, temperate localities where dengue transmission was very rare or had never been reported are now experiencing autochthonous dengue transmission. Autochthonous dengue transmission was recently documented in the metropolitan area of Mexico City a decade after the first report of the invasion of Aedes aegypti in Mexico City.

The generation of raster layers of bioclimatic, environmental, and anthropogenic variables in a metropolitan area of Mexico City is essential to understand the factors associated with the presence of the vector and imported cases and can also be used as inputs to predict the probability of the presence of the vector and cases. The following environmental layers are provided in this repository with a spatial resolution of 100 m maintained by the coordinate reference system with EPSG code 4326 (EPSG:4326).

The bioclimatic variables used were obtained from WorldClim V1 Bioclim (Hijmans, 2005) using Google Hearth Engine. The Bioclim database includes a time series from 1960 to 1991, and the native spatial resolution was 927.67 meters. The methodology used to access the databases is as follows. First, Google Hearth Engine services were authenticated and initialized through the credentials of the first author. Second, images from the WorldClim database (“WORLDCLIM/V1/BIO”) were defined. Third, the area of interest (Mexico City metropolitan area) was defined and its geographic rectangle (bounding box) was extracted. Fourth, the Google Hearth Engine image downscaled to 100 m was exported and locally hosted with a tif extension. The same process was followed for the heat islands, NDVI, temperature, altitude, word cover, and cover fraction. All layers were clipped to the geographic area of the metropolitan area of Mexico City and resampled using the bilinear method with a 100 downscaled layer from Worclim as a reference.

The databases for Dynamic Human Indices, Human footprint (Mu et al. 2022), and Population (pop) were accessed at the following links:

The accessibility index was built by the first author by using a geostatistical model with INLA. The model predictions were projected onto the centroids of a raster layer template (bio01), converted to a raster layer, and saved with a tif extension.