Geospatial analysis and mapping strategies for fine-grained and detailed COVID-19 Data with GIS
File(s)
Published version
Author(s)
Carballada, Angel Miramontes
Balsa-Barreiro, Jose
Type
Journal Article
Abstract
The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.
Date Issued
2021-09-01
Date Acceptance
2021-09-09
Citation
ISPRS International Journal of Geo-Information, 2021, 10 (9)
ISSN
2220-9964
Publisher
MDPI AG
Start Page
602
End Page
602
Journal / Book Title
ISPRS International Journal of Geo-Information
Volume
10
Issue
9
Copyright Statement
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
602
Date Publish Online
2021-09-12