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Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020
One of the main categories of Neglected Tropical Diseases (NTDs) are arboviruses, of which Dengue and Chikungunya are the most common. Arboviruses mainly affect tropical countries. Brazil has the largest absolute number of cases in Latin America. This work presents a unified data set with clinical,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090806/ https://www.ncbi.nlm.nih.gov/pubmed/35538103 http://dx.doi.org/10.1038/s41597-022-01312-7 |
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author | da Silva Neto, Sebastião Rogério Tabosa de Oliveira, Thomás Teixiera, Igor Vitor Medeiros Neto, Leonides Souza Sampaio, Vanderson Lynn, Theo Endo, Patricia Takako |
author_facet | da Silva Neto, Sebastião Rogério Tabosa de Oliveira, Thomás Teixiera, Igor Vitor Medeiros Neto, Leonides Souza Sampaio, Vanderson Lynn, Theo Endo, Patricia Takako |
author_sort | da Silva Neto, Sebastião Rogério |
collection | PubMed |
description | One of the main categories of Neglected Tropical Diseases (NTDs) are arboviruses, of which Dengue and Chikungunya are the most common. Arboviruses mainly affect tropical countries. Brazil has the largest absolute number of cases in Latin America. This work presents a unified data set with clinical, sociodemographic, and laboratorial data on confirmed patients of Dengue and Chikungunya, as well as patients ruled out of infection from these diseases. The data is based on case notification data submitted to the Brazilian Information System for Notifiable Diseases, from Portuguese Sistema de Informação de Agravo de Notificação (SINAN), from 2013 to 2020. The original data set comprised 13,421,230 records and 118 attributes. Following a pre-processing process, a final data set of 7,632,542 records and 56 attributes was generated. The data presented in this work will assist researchers in investigating antecedents of arbovirus emergence and transmission more generally, and Dengue and Chikungunya in particular. Furthermore, it can be used to train and test machine learning models for differential diagnosis and multi-class classification. |
format | Online Article Text |
id | pubmed-9090806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90908062022-05-12 Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 da Silva Neto, Sebastião Rogério Tabosa de Oliveira, Thomás Teixiera, Igor Vitor Medeiros Neto, Leonides Souza Sampaio, Vanderson Lynn, Theo Endo, Patricia Takako Sci Data Data Descriptor One of the main categories of Neglected Tropical Diseases (NTDs) are arboviruses, of which Dengue and Chikungunya are the most common. Arboviruses mainly affect tropical countries. Brazil has the largest absolute number of cases in Latin America. This work presents a unified data set with clinical, sociodemographic, and laboratorial data on confirmed patients of Dengue and Chikungunya, as well as patients ruled out of infection from these diseases. The data is based on case notification data submitted to the Brazilian Information System for Notifiable Diseases, from Portuguese Sistema de Informação de Agravo de Notificação (SINAN), from 2013 to 2020. The original data set comprised 13,421,230 records and 118 attributes. Following a pre-processing process, a final data set of 7,632,542 records and 56 attributes was generated. The data presented in this work will assist researchers in investigating antecedents of arbovirus emergence and transmission more generally, and Dengue and Chikungunya in particular. Furthermore, it can be used to train and test machine learning models for differential diagnosis and multi-class classification. Nature Publishing Group UK 2022-05-10 /pmc/articles/PMC9090806/ /pubmed/35538103 http://dx.doi.org/10.1038/s41597-022-01312-7 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor da Silva Neto, Sebastião Rogério Tabosa de Oliveira, Thomás Teixiera, Igor Vitor Medeiros Neto, Leonides Souza Sampaio, Vanderson Lynn, Theo Endo, Patricia Takako Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 |
title | Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 |
title_full | Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 |
title_fullStr | Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 |
title_full_unstemmed | Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 |
title_short | Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013–2020 |
title_sort | arboviral disease record data - dengue and chikungunya, brazil, 2013–2020 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090806/ https://www.ncbi.nlm.nih.gov/pubmed/35538103 http://dx.doi.org/10.1038/s41597-022-01312-7 |
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