ArticleScientific data2022
Arboviral disease record data - Dengue and Chikungunya, Brazil, 2013-2020.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Integrating metagenomics and metatranscriptomics intoThe Journal of general virology · 2026Review
- Immune-mediated protection and enhancement of dengue drives patterns of infant cases in Brazil.Nature communications · 2026Article
- AI-Assisted Differentiation of Dengue and Chikungunya Using Big, Imbalanced Epidemiological Data.Tropical medicine and infectious disease · 2026Article
- Epidemiological and digital syndromic surveillance data on dengue, chikungunya, and SARI in Brazil.Scientific data · 2026Article
- Phenol and chromone compounds forPharmaceutical science advances · 2025Article
- Spatiotemporal dataset of dengue influencing factors in Brazil based on geospatial big data cloud computing.Scientific data · 2025Article
- Use of ProMED as a Surveillance System for Emerging and Re-Emerging Infectious Diseases in Brazil from 2015 to 2020.Viruses · 2025Article
- [The efficiency of the rapid chikungunya test in a scenario of Zika and dengue cocirculation in the municipality of Rio de Janeiro, Brazil].Cadernos de saude publica · 2025Article
- Sex-specific public health data: analyzing the arboviral impact on women in Brazil.Revista de saude publica · 2025Article
- A comprehensive seroepidemiology of dengue and chikungunya arboviruses in Iran, 2020-2023.Virology journal · 2024Article
- Cryptic circulation of chikungunya virus in São Jose do Rio Preto, Brazil, 2015-2019.PLoS neglected tropical diseases · 2024Article
- Climate change impacts on dengue transmission areas in Espírito Santo state, Brazil.Oxford open immunology · 2024Article
- Seroprevalence of Dengue, Chikungunya, and Zika viruses antibodies in a cohort of asymptomatic pregnant women in a low-income region of Minas Gerais, Brazil, 2018-2019.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023Article
- Review on Main Arboviruses Circulating on French Guiana, An Ultra-Peripheric European Region in South America.Viruses · 2023Review
- A Brazilian classified data set for prognosis of tuberculosis, between January 2001 and April 2020.Scientific data · 2022Article
- Forecasting Weekly Dengue Cases by Integrating Google Earth Engine-Based Risk Predictor Generation and Google Colab-Based Deep Learning Modeling in Fortaleza and the Federal District, Brazil.International journal of environmental research and public health · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.