[Risk of transmission of SARS-CoV-2: multi-criteria spatial evaluation in a municipality of Colombia, 2020]

Rev Salud Publica (Bogota). 2020 Mar 1;22(2):205-213. doi: 10.15446/rsap.V22n2.88772.
[Article in Spanish]

Abstract

Objective: To zoning the risk of SARS-CoV-2 transmission in Villavicencio, Colombia, through a multi-criteria spatial evaluation.

Materials and methods: A multi-criteria evaluation model was implemented, through a hierarchical analysis process, integrated into a Geographic Information System. As criteria, descriptive attributes of the threats and vulnerabilities of viral transmission identified by means of an epidemiological model were included, on the same dimensionless numerical scale and proportional to the probability of contagion; the alternatives evaluated correspond to spatial entities represented by pixels. The criteria were weighted according to the expert judgment of the evaluators, with whom the calculation of a normalized matrix of relative priorities was performed, which allowed the estimation of a vector of weights, the degree of inconsistency of which was admissible. The magnitude of the risk was calculated with a weighted summation of the evaluation of the criteria, according to a map algebra geoprocessing.

Results: The spatial heterogeneity of the risk of SARS-CoV-2 transmission was described in Villavicencio, allowing the identification of the areas with the highest probability of transmission, located in neighborhoods characterized by high socioeconomic vulnerability.

Conclusions: The cartographic representation derived from the implementation of a multicriteria model, integrated to a Geographical Information System, in the SARS-CoV-2 transmission risk analysis, constitutes a relevant methodological contribution for decision-making defining strategies of mitigation at the local level, facilitating the location and optimization of resources by the health authorities.

Publication types

  • English Abstract

MeSH terms

  • COVID-19* / epidemiology
  • Cities
  • Colombia / epidemiology
  • Geographic Information Systems
  • Humans
  • SARS-CoV-2*