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Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario

Brazil is one of the countries with the worst response against the pandemic scenario of coronavírus. At the beginning we were on average with 4000 deaths in a 24 hours period. In the course of this situation, large amounts of health and medicine datasets were being generated in real time, requiring...

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Autores principales: Cassão, Victor, Alves, Domingos, Mioto, Ana Clara de Andrade, Mozini, Mariana Tavares, Segamarchi, Renan Barbieri, Miyoshi, Newton Shydeo Brandão
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030184/
https://www.ncbi.nlm.nih.gov/pubmed/36968662
http://dx.doi.org/10.1016/j.procs.2023.01.435
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author Cassão, Victor
Alves, Domingos
Mioto, Ana Clara de Andrade
Mozini, Mariana Tavares
Segamarchi, Renan Barbieri
Miyoshi, Newton Shydeo Brandão
author_facet Cassão, Victor
Alves, Domingos
Mioto, Ana Clara de Andrade
Mozini, Mariana Tavares
Segamarchi, Renan Barbieri
Miyoshi, Newton Shydeo Brandão
author_sort Cassão, Victor
collection PubMed
description Brazil is one of the countries with the worst response against the pandemic scenario of coronavírus. At the beginning we were on average with 4000 deaths in a 24 hours period. In the course of this situation, large amounts of health and medicine datasets were being generated in real time, requiring effective ways to extract information and discover patterns that can help in the fight against this disease. And even more important is to monitor the progress of prophylactic measures and whether they are being effective in reducing the spread of the virus. Thus, the aim of this study is to analyze how the coronavirus has different ways to evolve in each Brazilian state with the influences of the vaccination process. To achieve this goal, the time series Clustering Technique based on a K-Means variation was applied, with the similarity metric Dynamic Time Warping (DTW). We produced this study using the data reported by the Ministry of Health in Brazil, referring to deaths per 100k inhabitants and all vaccination data available. Our results indicate an unevenly occurring vaccination and the need to identify other associated patterns with human development indices and other socio-economic indicators, being this the first analysis developed in the country, under the goals above.
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spelling pubmed-100301842023-03-22 Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario Cassão, Victor Alves, Domingos Mioto, Ana Clara de Andrade Mozini, Mariana Tavares Segamarchi, Renan Barbieri Miyoshi, Newton Shydeo Brandão Procedia Comput Sci Article Brazil is one of the countries with the worst response against the pandemic scenario of coronavírus. At the beginning we were on average with 4000 deaths in a 24 hours period. In the course of this situation, large amounts of health and medicine datasets were being generated in real time, requiring effective ways to extract information and discover patterns that can help in the fight against this disease. And even more important is to monitor the progress of prophylactic measures and whether they are being effective in reducing the spread of the virus. Thus, the aim of this study is to analyze how the coronavirus has different ways to evolve in each Brazilian state with the influences of the vaccination process. To achieve this goal, the time series Clustering Technique based on a K-Means variation was applied, with the similarity metric Dynamic Time Warping (DTW). We produced this study using the data reported by the Ministry of Health in Brazil, referring to deaths per 100k inhabitants and all vaccination data available. Our results indicate an unevenly occurring vaccination and the need to identify other associated patterns with human development indices and other socio-economic indicators, being this the first analysis developed in the country, under the goals above. The Author(s). Published by Elsevier B.V. 2023 2023-03-22 /pmc/articles/PMC10030184/ /pubmed/36968662 http://dx.doi.org/10.1016/j.procs.2023.01.435 Text en © 2023 The Author(s). Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Cassão, Victor
Alves, Domingos
Mioto, Ana Clara de Andrade
Mozini, Mariana Tavares
Segamarchi, Renan Barbieri
Miyoshi, Newton Shydeo Brandão
Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario
title Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario
title_full Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario
title_fullStr Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario
title_full_unstemmed Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario
title_short Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario
title_sort unsupervised analysis of covid-19 pandemic evolution in brazilian states: vaccination scenario
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030184/
https://www.ncbi.nlm.nih.gov/pubmed/36968662
http://dx.doi.org/10.1016/j.procs.2023.01.435
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