The study looks at how the Covid-19 wave was in Peru, where and when it begins, where and when it culminates. As it faced, the shortcomings that were detected and especially that very little could be done to confront the disease as an emerging country. The wave began in May and ended in August with the greatest number of deaths and then fell. Methodology: Basic, explanatory level, with SINADEF data by region, of the situation room, to get the number of deaths, between January and September 2020/2019. Results. The relationship between infected and deceased was found a Pearson Rho of 0.94. The total death toll model depends on Lima, Huánuco, and Piura. The differences between the deaths of 2019 and 2020 were corroborated with the ANOVA, where a bilateral sig of 0.042 was got. The COVID cycle is found in the cluster algorithm model, of the nine months in 44.4% of them, it generated the highest lethality, between May and August. Conclusion. It is proven that COVID devastated regions of Peru.The model generated by the K-Means algorithm tells us that the COVID-19 cycle began in March and reached its highest peak of deceased and then descended.
In the world of science there are high-level, moderate-level, and low-level emerging countries. The indicators are an investment in research and development (I&D), number of universities, investment, researchers, intellectual production, expenditure on education, gross domestic product (PBI), and quality of life (IDH). In Methodology, it is basic, explanatory, of conglomerates. There are 37 countries analyzed. The data comes from the FMI, datosmacro.com, UNESCO, URWU. There are 11 indicators. These are data taken in two stages, 2006 and 2019. The Results shows R2= 0.9887, which explains the behavior of the PBI by the investment in I&D. The positive and significant relationship between IDH and PBI per capita, which is 0.824, is transcendent. In conclusion, there are three clusters with clearly differentiated indicators. Peru's problem is structural in that it does not have a per capita PBI of $ 30,000 per person or more. Investment in I&D in Peru is low and PBI is also low. Therefore, countries with higher investments in science have high PBIs and better IDH.
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