Abstract

Background: Social inequalities in health have been linked to disproportional impacts in COVID-19 mortality. Therefore, this study aimed to analyze the spatiotemporal distribution of the COVID-19-related mortality and its association with the Social Determinants of Health (SDH) in Sergipe, Northeastern Brazil.Method: Ecological study using spatiotemporal analysis tools. All confirmed deaths related to COVID-19 in Sergipe, Brazil, from March 14 th to October 31 st 2020, were included and we calculated moving averages. Mortality crude rates were smoothed through Empirical Bayesian Method and were used for spatial analysis. We carried out the retrospective spatiotemporal scan statistics using the Poisson’s probability model. We used the spatial regression models to identify the association between COVID-19 mortality and Social Determinants of Health.Findings: 2,206 deaths by COVID-19 were registered in Sergipe. There was an increase of the moving averages, reaching the peak at of July 2020. A spatiotemporal cluster of mortality, comprising the metropolitan area and the neighboring cities. Illiteracy rate of people ≥15 years-old, percentage of children Interpretation: COVID-19 mortality in Sergipe was increasing until the end of July 2020 and it showed a spatiotemporal risk cluster in the metropolitan area. Educational and aging indicators were associated to mortality, which points out the necessity of prioritization and resources redirection to risk areas.Funding Information: No funding source was required for this study.Declaration of Interests: None to declare. Ethics Approval Statement: This study followed national ethical recommendations and the rules of Helsinki Convention. The research project was approved by the Research Ethics Committee of Federal University of Sergipe (CEP/UFS), registered under the approval 4,086,909.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.