Brazilian COVID-19 data streaming
N\'ivea B. da Silva, Luis Iv\'an O. Valencia, F\'abio M. H. S. Filho,, Andressa C. S. Ferreira, Felipe A. C. Pereira, Guilherme L. de Oliveira,, Paloma F. Oliveira, Moreno S. Rodrigues, Pablo I. P. Ramos, Juliane F., Oliveira
TL;DR
This paper presents a comprehensive real-time data streaming platform for COVID-19 in Brazil, integrating diverse data sources to support epidemiological research, modeling, and policy analysis.
Contribution
It introduces a novel data structure and pipeline for real-time collection, curation, and integration of COVID-19 related data at state and municipal levels in Brazil.
Findings
Enables detailed epidemiological studies and modeling.
Supports real-time data visualization and dissemination.
Facilitates analysis of interventions and mobility patterns.
Abstract
We collected individualized (unidentifiable) and aggregated openly available data from various sources related to suspected/confirmed SARS-CoV-2 infections, vaccinations, non-pharmaceutical government interventions, human mobility, and levels of population inequality in Brazil. In addition, a data structure allowing real-time data collection, curation, integration, and extract-transform-load processes for different objectives was developed. The granularity of this dataset (state- and municipality-wide) enables its application to individualized and ecological epidemiological studies, statistical, mathematical, and computational modeling, data visualization as well as the scientific dissemination of information on the COVID-19 pandemic in Brazil.
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Taxonomy
TopicsArtificial Intelligence in Healthcare · COVID-19 diagnosis using AI · COVID-19 epidemiological studies