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Open AccessArticle

Can Socioeconomic, Health, and Safety Data Explain the Spread of COVID-19 Outbreak on Brazilian Federative Units?

1
COVID-19 Research Group, Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Cidade Universitária, Rio de Janeiro RJ 21941-598, Brazil
2
Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro RJ 21941-909, Brazil
3
Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro RJ 20020-000, Brazil
4
Chemistry Department, State University of Londrina (UEL), Londrina PR 86057-970, Brazil
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(23), 8921; https://doi.org/10.3390/ijerph17238921
Received: 19 October 2020 / Revised: 12 November 2020 / Accepted: 14 November 2020 / Published: 30 November 2020
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. View Full-Text
Keywords: coronavirus disease; artificial neural networks; SARS-CoV-2; ventilator; index development index; developing country coronavirus disease; artificial neural networks; SARS-CoV-2; ventilator; index development index; developing country
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MDPI and ACS Style

Galvan, D.; Effting, L.; Cremasco, H.; Adam Conte-Junior, C. Can Socioeconomic, Health, and Safety Data Explain the Spread of COVID-19 Outbreak on Brazilian Federative Units? Int. J. Environ. Res. Public Health 2020, 17, 8921. https://doi.org/10.3390/ijerph17238921

AMA Style

Galvan D, Effting L, Cremasco H, Adam Conte-Junior C. Can Socioeconomic, Health, and Safety Data Explain the Spread of COVID-19 Outbreak on Brazilian Federative Units? International Journal of Environmental Research and Public Health. 2020; 17(23):8921. https://doi.org/10.3390/ijerph17238921

Chicago/Turabian Style

Galvan, Diego; Effting, Luciane; Cremasco, Hágata; Adam Conte-Junior, Carlos. 2020. "Can Socioeconomic, Health, and Safety Data Explain the Spread of COVID-19 Outbreak on Brazilian Federative Units?" Int. J. Environ. Res. Public Health 17, no. 23: 8921. https://doi.org/10.3390/ijerph17238921

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