Abstract
The SARS-COV-2 virus of the coronavirus family was identified in 2019. This is a type of virus that infects humans and some animals, in Peru it has seriously affected everyone, causing so many deaths, which has resulted in that people be tested to rule out contagion, using laboratory methods recommended by the government of the country. Therefore, the data science methodology was used with this research, where its objective is to predict what types of people are contaminated during SARS-COV-2 by the regions of Peru, identified through laboratory methods, therefore, the ”data bank” was taken by PNDA, the CSV file was used for that study, apart from the fact that it comes from the INS and the CDC of the MINSA. In which, machine learning was developed with the decision tree algorithm and then began coding, in such a way that the distribution called Anaconda was used where it is encoded in Python language, together with that distribution, Jupyter Notebook was used which is a client-server application. The results generated by this research prove that it was possible to identify the types of individuals by SARS-COV-2. These results can help prevention entities against SARS-COV-2 to apply the corresponding preventive measures in a more focused way.
Highlights
Since SARS-COV-2 affected all the countries of the world it has led to several deaths, for which the impact that laboratory methods have come to have been beneficial since they are used for the detection of the virus avoiding this way its spread, the use that is given to these methods are diverse, which can be used for people who have had contact with the virus, [1] people with symptoms of SARS-COV-2 and people who want to know if they have had the virus
The importance of this study is ”rooted” in reaching the greatest intellect concerning laboratory methods, this is done to know which laboratory methods are most used in each region of Peru since this gives us indications of that ”type of individuals” (Individuals who have been in possible contact with the virus, with symptoms of SARS-COV-2 and who want to know if they have had the virus) live in the majority in each region and be able to apply the corresponding preventive measures
This last journey of the data science methodology assessed the model with other elements, in the first place that was carried out before proceeding, the assessment was to check the forecast that was carried out in the preparation journey of the model where the prognosis is based on the elements of the index from 0 - 6, with which the value has to vary from that scale of indexes, for that reason in that route the elements of the index 101 were used to specify the efficiency of the model based on the outcome of the valued
Summary
Since SARS-COV-2 affected all the countries of the world it has led to several deaths, for which the impact that laboratory methods have come to have been beneficial since they are used for the detection of the virus avoiding this way its spread, the use that is given to these methods are diverse, which can be used for people who have had contact with the virus, [1] people with symptoms of SARS-COV-2 and people who want to know if they have had the virus. This study will provide an enormous advantage because thanks to it, prevention entities against SARS-COV-2 will be able to apply the corresponding preventive measures in a more focused way; in addition to deepening the knowledge about machine learning, with which the work of these entities will be more productive and in this way they will acquire adaptation to the novelty of the environment in which they live
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