Clustering K-Means Algorithms and Econometric Lethality Model by Covid-19, Peru 2020

Objective: 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.

@article{Arocutipa2021,
  title     = {Clustering K-Means Algorithms and Econometric Lethality Model by Covid-19, Peru 2020},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {1},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Javier Pedro Flores Arocutipa and Jorge Jinchuña Huallpa and Gamaniel Carbajal Navarro and Luís Delfín Bermejo Peralta},
  doi       = {10.14569/IJACSA.2021.0120107},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120107}
}