Author
Listed:
- Dagnino, Ricardo
(UFRGS)
- Panitz, Lucas Manassi
- Weber, Eliseu José
- de Freitas, Marcos Wellausen Dias
- de Oliveira, Guilherme Garcia
- Batista, Sinthia Cristina
- Megiato, Érica Insaurriaga
- Rodrigues, Maicon dos Santos
- Presser, Martim Kowalczuk
- Sarmiento, Douglas Wesley Pires
Abstract
From the first cases of Covid-19 in Rio Grande do Sul, in March 2020, we started monitoring the pandemic using an online Geographic Information System (GIS). Within the SIG Litoral Project, from the Federal University of Rio Grande do Sul, we developed the platform as a strategy to provide society with spatial analysis and organized data on the disease, bringing together researchers, scholarship holders and volunteers. The portal, focused on health communication, allows the visualization of data on the global, national and regional scales, in addition to monitoring the indigenous populations of the Amazon and mapping the solidarity networks in the North Coast of Rio Grande do Sul. In the article in question, we mainly focus on monitoring Covid-19 in Rio Grande do Sul, addressing the tools used, the challenges to obtaining data and some spatial analysis performed. We show divergences between data sources, indicating the problem of underreporting and the different methodologies employed by health surveillance systems. Finally, we address the impact of the monitoring of Covid-19, having a positive impact on society by providing transparency to official data, contributing to the plurality of the debate, the interaction of multidisciplinary teams and the academic training of students.
Suggested Citation
Dagnino, Ricardo & Panitz, Lucas Manassi & Weber, Eliseu José & de Freitas, Marcos Wellausen Dias & de Oliveira, Guilherme Garcia & Batista, Sinthia Cristina & Megiato, Érica Insaurriaga & Rodrigues, , 2020.
"O monitoramento da Covid-19 através de Sistemas de Informação Geográfica: estratégias e desafios para a transparência de dados públicos no Rio Grande do Sul,"
SocArXiv
a6f73_v1, Center for Open Science.
Handle:
RePEc:osf:socarx:a6f73_v1
DOI: 10.31219/osf.io/a6f73_v1
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