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.
【저자키워드】 coronavirus disease, SARS-CoV-2, developing country, artificial neural networks, ventilator, index development index, 【초록키워드】 COVID-19, Vaccine, Influenza, intensive care unit, drugs, ICU, Spread, Nurses, artificial, death, PPE, Physicians, network, Analysis, ANN, Human Development Index, Factor, significant effect, measure, variable, spread of COVID-19, lowest, highest, affected, the disease, applied, expected, Neural, Map, Evaluating, other variable, 【제목키워드】 COVID-19, Safety, Can,