ArticleRevista da Sociedade Brasileira de Medicina Tropical2021
COVID-19 in children in the state of Pernambuco: Spatial analysis of confirmed severe cases and the Human Development Index.
Article in Revista da Sociedade Brasileira de Medicina Tropical, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Severity Profile of COVID-19 in Hospitalized Pediatric Patients.Children (Basel, Switzerland) · 2024Article
- Factors associated with covid-19 deaths in the city of Recife, Pernambuco, Brazil, 2020: a cross-sectional study with "Notifique Aqui" system data.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2023Article
- Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study.International journal of environmental research and public health · 2022Article
- Seroprevalence and factors associated with SARS-CoV-2 infection among education workers after the first wave: the first cross-sectional study in Brazil.Revista da Sociedade Brasileira de Medicina Tropical · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionHealth planning is required for the control and prevention of severe cases of COVID-19 in children.
methodsSpatial analysis of severe COVID-19 cases in children of Pernambuco in the first six months of the pandemic and its autocorrelation with the Human Development Index was conducted.
resultsA total of 551 severe cases (39.4 cases/100,000 inhabitants) was initially concentrated in the metropolitan area, with later interiorization. The spatial autocorrelation of cases was identified. The bivariate analysis revealed alert regions in less developed municipalities (I=0.341; p=0.001).
conclusionsConsidering the local particularities can assist in directing the priorities for decision making.
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