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Vulnerability interactive geographic viewer against COVID‐19 at the block level in Colombia: Analytical tool based on machine learning techniques

Author

Listed:
  • Oscar Espinosa
  • Jhonathan Rodríguez
  • Adriana Robayo
  • Lelio Arias
  • Sandra Moreno
  • Mariana Ospina
  • David Insuasti
  • Juan Oviedo

Abstract

To mitigate the effects of the coronavirus disease 2019 (COVID‐19) pandemic, different countries have developed computational tools and dashboards that generate value for decision‐making in public health. We aimed to build an interactive geographic viewer for vulnerability to COVID‐19 at the block level in Colombia to identify the location of populations that, because of sociodemographic characteristics and health conditions, could have more complications from COVID‐19 infections. The vulnerability levels of the different blocks of 1,102 municipal capitals were calculated. Additionally, the institutions that provide health services and hotels were georeferenced, and changes in people’s mobility dynamics in large cities were identified.

Suggested Citation

  • Oscar Espinosa & Jhonathan Rodríguez & Adriana Robayo & Lelio Arias & Sandra Moreno & Mariana Ospina & David Insuasti & Juan Oviedo, 2021. "Vulnerability interactive geographic viewer against COVID‐19 at the block level in Colombia: Analytical tool based on machine learning techniques," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(S1), pages 187-197, November.
    • Handle: RePEc:bla:rgscpp:v:13:y:2021:i:s1:p:187-197
    DOI: 10.1111/rsp3.12469
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