9882919a968179aa6ca877f9e3219777 pmc_33573323.pdf 62808862aba180378d3638c6c1c61423f771aad2 pmc_33573323.pdf 39858680deaafe1892e7a093215c3f5798458cf97d1d82a7a8f277e83ec7b903 pmc_33573323.pdf Title: Socioeconomic Inequalities in COVID-19 in a European Urban Area: Two Waves, Two Patterns Subject: Background: The objective of this paper is to analyze social inequalities in COVID-19 incidence, stratified by age, sex, geographical area, and income in Barcelona during the first two waves of the pandemic. Methods: We collected data on COVID-19 cases confirmed by laboratory tests during the first two waves of the pandemic (1 March to 15 July and 16 July to 30 November, 2020) in Barcelona. For each wave and sex, we calculated smooth cumulative incidence by census tract using a hierarchical Bayesian model. We analyzed income inequalities in the incidence of COVID-19, categorizing the census tracts into quintiles based on the income indicator. Results: During the two waves, women showed higher COVID-19 cumulative incidence under 64 years, while the trend was reversed after that threshold. The incidence of the disease was higher in some poor neighborhoods. The risk ratio (RR) increased in the poorest groups compared to the richest ones, mainly in the second wave, with RR being 1.67 (95% Credible Interval-CI-: 1.41–1.96) in the fifth quintile income group for men and 1.71 (95% CI: 1.44–1.99) for women. Conclusion: Our results indicate the existence of inequalities in the incidence of COVID-19 in an urban area of Southern Europe. Keywords: COVID-19; inequalities; geographical area; urban area Author: Marc Marí-Dell’Olmo, Mercè Gotsens, M Isabel Pasarín, Maica Rodríguez-Sanz, Lucía Artazcoz, Patricia Garcia de Olalla, Cristina Rius and Carme Borrell Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Mon Feb 1 10:39:50 2021 CET ModDate: Mon Feb 1 12:05:44 2021 CET Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 12 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 2560997 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- YSAOHE+VnURWPalladioL Type 1 Custom yes yes no 10 0 GEMJIH+URWPalladioL-Ital Type 1 Custom yes yes no 15 0 HGQCSA+URWPalladioL-Bold Type 1 Custom yes yes no 20 0 RGULKD+URWPalladioL-Roma Type 1 Custom yes yes no 24 0 LMOTSQ+VnURWPalladioL-Bold Type 1 Custom yes yes no 28 0 LWQXII+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 36 0 IRWHZX+TimesNewRomanPSMT Type 1C WinAnsi yes yes no 39 0 MCBCCI+SourceSansRoman-Regular Type 1C Custom yes yes no 61 0 MCBCCM+SourceSansRoman.613wght Type 1C Custom yes yes no 65 0 MCBCCO+SourceSansRoman-Bold Type 1C Custom yes yes no 69 0 QHMKWQ+PazoMath Type 1 Builtin yes yes no 84 0 NETBHX+EURM10 Type 1 Builtin yes yes no 88 0 FMKMLH+Cambria,Italic TrueType WinAnsi yes yes no 98 0 FMKKAP+Cambria,Bold TrueType WinAnsi yes yes no 101 0 FMKKBA+Cambria CID TrueType Identity-H yes yes yes 104 0 FMKKBE+PalatinoLinotype TrueType WinAnsi yes yes no 110 0 FMKKCF+PalatinoLinotype,Bold TrueType WinAnsi yes yes no 113 0 FMKMLH+Cambria,Italic TrueType WinAnsi yes yes no 124 0 FMKKAP+Cambria,Bold TrueType WinAnsi yes yes no 127 0 FMKKBA+Cambria CID TrueType Identity-H yes yes yes 130 0 FMKKBC+PalatinoLinotype,Italic TrueType WinAnsi yes yes no 136 0 FMKKBE+PalatinoLinotype TrueType WinAnsi yes yes no 139 0 FMKKCF+PalatinoLinotype,Bold TrueType WinAnsi yes yes no 142 0 FMKMLH+Cambria,Italic TrueType WinAnsi yes yes no 153 0 FMKKAP+Cambria,Bold TrueType WinAnsi yes yes no 156 0 FMKKBA+Cambria CID TrueType Identity-H yes yes yes 159 0 FMKKBE+PalatinoLinotype TrueType WinAnsi yes yes no 165 0 FMKKCF+PalatinoLinotype,Bold TrueType WinAnsi yes yes no 168 0 FMKMLH+Cambria,Italic TrueType WinAnsi yes yes no 179 0 FMKKAP+Cambria,Bold TrueType WinAnsi yes yes no 182 0 FMKKBA+Cambria CID TrueType Identity-H yes yes yes 185 0 FMKKBE+PalatinoLinotype TrueType WinAnsi yes yes no 191 0 FMKKCF+PalatinoLinotype,Bold TrueType WinAnsi yes yes no 194 0 NUUXUW+VnURWPalladioL-Italic Type 1 Custom yes yes no 211 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2024-10-02 03:31:12 CEST RepresentationInformation: pmc_33573323.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2023-03-31 12:08:52 CEST Size: 2560997 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 377 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Methodology Destination: section.2 Children: Item: Title: Design, Study Population, and Sources of Information Destination: subsection.2.1 Item: Title: Indicators and Data Analysis Destination: subsection.2.2 Item: Title: Result Destination: section.3 Children: Item: Title: First Wave Destination: subsection.3.1 Item: Title: Second Wave Destination: subsection.3.2 Item: Title: Discussion Destination: section.4 Children: Item: Title: Differences by Age Group Destination: subsection.4.1 Item: Title: Gender Inequalities Destination: subsection.4.2 Item: Title: Socioeconomic Inequalities Destination: subsection.4.3 Item: Title: Limitations Destination: subsection.4.4 Item: Title: Conclusions and Recommendations Destination: section.5 Item: Title: References Destination: section.5 Info: Title: Socioeconomic Inequalities in COVID-19 in a European Urban Area: Two Waves, Two Patterns Author: Marc Marí-Dell’Olmo, Mercè Gotsens, M Isabel Pasarín, Maica Rodríguez-Sanz, Lucía Artazcoz, Patricia Garcia de Olalla, Cristina Rius and Carme Borrell Subject: Background: The objective of this paper is to analyze social inequalities in COVID-19 incidence, stratified by age, sex, geographical area, and income in Barcelona during the first two waves of the pandemic. Methods: We collected data on COVID-19 cases confirmed by laboratory tests during the first two waves of the pandemic (1 March to 15 July and 16 July to 30 November, 2020) in Barcelona. For each wave and sex, we calculated smooth cumulative incidence by census tract using a hierarchical Bayesian model. We analyzed income inequalities in the incidence of COVID-19, categorizing the census tracts into quintiles based on the income indicator. Results: During the two waves, women showed higher COVID-19 cumulative incidence under 64 years, while the trend was reversed after that threshold. The incidence of the disease was higher in some poor neighborhoods. The risk ratio (RR) increased in the poorest groups compared to the richest ones, mainly in the second wave, with RR being 1.67 (95% Credible Interval-CI-: 1.41 1.96) in the fifth quintile income group for men and 1.71 (95% CI: 1.44 1.99) for women. Conclusion: Our results indicate the existence of inequalities in the incidence of COVID-19 in an urban area of Southern Europe. 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