ArticleOne health (Amsterdam, Netherlands)2021
Data quality and arbovirus infection associated factors in pregnant and non-pregnant women of childbearing age in Brazil: A surveillance database analysis.
Article in One health (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Common data quality elements for health information systems: a systematic review.BMC medical informatics and decision making · 2024Pooled it
- Optimizing adolescent HIV care: a review of EMR system quality for clinical monitoring in Zambia.Frontiers in public health · 2026Article
- Beyond COVID-19, the case for collecting, analysing and using sex-disaggregated data and gendered data to inform outbreak response: a scoping review.BMJ global health · 2025Article
- Epidemiological profile of arboviruses in two different scenarios: dengue circulation vs. dengue, chikungunya and Zika co-circulation.BMC infectious diseases · 2023Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The dengue surveillance system in Brazil has registered changes in the disease's morbidity and mortality profile over successive epidemics. Vulnerable groups, such as pregnant women, have been particularly hard hit. This study assessed the quality of notifications of dengue cases among pregnant women and non-pregnant women of childbearing age in Brazil, in addition to discussing the factors associated with arbovirus infection in the group of pregnant women. We carried out a retrospective study of cases registered in the national arbovirus surveillance system between 2007 and 2017. The indicator for assessing quality was incompleteness. Logistic regression was used to analyze the association between dengue during pregnancy and sociodemographic, epidemiological, clinical, and laboratory variables. The incompleteness of the data in the notification form for dengue cases in women of childbearing age and pregnant women indicates a significant loss of information. Dengue was shown to be positively associated with Social Determinants of Health in both groups, with more severe effects among pregnant women. The incompleteness of the data can limit the quality of information from the notification system and the national assessment of the situation of the disease in women of childbearing age and pregnant women.
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Registered trials
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