Abstract

MARIN MAMANI, Grover et al. Identification of COVID-19 contagion areas through spatial analysis of public urban facilities. InterSedes [online]. 2022, vol.23, n.48, pp.1-17. ISSN 2215-2458.  http://dx.doi.org/10.15517/isucr.v23i48.48131.

The health crisis of 2020 due to COVID-19 has become the main problem faced by governments, in this context spatial analysis is a tool that helps to control the pandemic from an urban approach. The purpose is to identify the COVID-19 contagion risk zones, through the spatial analysis of the banking and commercial equipment in the city of Puno. The banking and commercial equipment has been located in UTM WGS 84 coordinates, for the generation of response surfaces through the Kernel density, adding the partial results through the map algebra and also identified the spatial autocorrelation through the index of Moran I. High risk areas of contagion COVID-19 have been identified with an area of 127 210.44 m2 which represents 14% covering 13 blocks with centroid coordinates 389952. 43 East and 8248722.69 South, generating a concentric pattern in the center of the city of Puno, which allowed taking actions for dissemination, strengthening and prevention of biosecurity protocols in the identified area, this area is the result of the proximity of banking equipment with the commercial causing inequality with other sectors of the city.Key Words: Kernel density, Map algebra, Moran index, Spatial autocorrelation, Urban equipment.

Keywords : Kernel density; Map algebra; Moran index; Spatial autocorrelation; Urban equipment.

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