ArticleInternational journal of environmental research and public health2020
Can Socioeconomic, Health, and Safety Data Explain the Spread of COVID-19 Outbreak on Brazilian Federative Units?
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Large language models for bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Effects of fundamental social motives on environmental variation of compliance during pandemics.Evolutionary human sciences · 2026Article
- Spatiotemporal evolution of COVID-19 in Portugal's Mainland with self-organizing maps.International journal of health geographics · 2023Article
- Visualization and Semantic Labeling of Mood States Based on Time-Series Features of Eye Gaze and Facial Expressions by Unsupervised Learning.Healthcare (Basel, Switzerland) · 2022Article
- Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study.International journal of environmental research and public health · 2022Article
- Distinct weather conditions and human mobility impacts on the SARS-CoV-2 outbreak in Colombia: Application of an artificial neural network approach.International journal of hygiene and environmental health · 2021Article
- Recent Applications of Mixture Designs in Beverages, Foods, and Pharmaceutical Health: A Systematic Review and Meta-Analysis.Foods (Basel, Switzerland) · 2021Review
- Dynamic Network Analysis of COVID-19 with a Latent Pandemic Space Model.International journal of environmental research and public health · 2021Article
- The Spread of the COVID-19 Outbreak in Brazil: An Overview by Kohonen Self-Organizing Map Networks.Medicina (Kaunas, Lithuania) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Infinite factors can influence the spread of COVID-19. Evaluating factors related to the spread of the disease is essential to point out measures that take effect. In this study, the influence of 14 variables was assessed together by Artificial Neural Networks (ANN) of the type Self-Organizing Maps (SOM), to verify the relationship between numbers of cases and deaths from COVID-19 in Brazilian states for 110 days. The SOM analysis showed that the variables that presented a more significant relationship with the numbers of cases and deaths by COVID-19 were influenza vaccine applied, Intensive Care Unit (ICU), ventilators, physicians, nurses, and the Human Development Index (HDI). In general, Brazilian states with the highest rates of influenza vaccine applied, ICU beds, ventilators, physicians, and nurses, per 100,000 inhabitants, had the lowest number of cases and deaths from COVID-19, while the states with the lowest rates were most affected by the disease. According to the SOM analysis, other variables such as Personal Protective Equipment (PPE), tests, drugs, and Federal funds, did not have as significant effect as expected.
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Registered trials
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