ArticleEpidemiology and infection2020
COVID-19 mortality in an area of northeast Brazil: epidemiological characteristics and prospective spatiotemporal modelling.
Article in Epidemiology and infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled 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
- Elderly patients in crisis: unveiling outcomes and management approaches in severe COVID-19 cases - a retrospective analysis from Brazil.Einstein (Sao Paulo, Brazil) · 2025Article
- Estimating the Relative Risks of Spatial Clusters Using a Predictor-Corrector Method.Mathematics (Basel, Switzerland) · 2025Article
- Spatiotemporal pattern of COVID-19 mortality and its relationship with socioeconomic and environmental factors in England.Spatial and spatio-temporal epidemiology · 2023Article
- Spatiotemporal clusters and the socioeconomic determinants of COVID-19 in Toronto neighbourhoods, Canada.Spatial and spatio-temporal epidemiology · 2022Article
- Article
- COVID-19 in Brazil: spatial risk, social vulnerability, human development, clinical manifestations and predictors of mortality - a retrospective study with data from 59 695 individuals.Epidemiology and infection · 2021Observational
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to analyse the spatial-temporal distribution of COVID-19 mortality in Sergipe, Northeast, Brazil. It was an ecological study utilising spatiotemporal analysis techniques that included all deaths confirmed by COVID-19 in Sergipe, from 2 April to 14 June 2020. Mortality rates were calculated per 100 000 inhabitants and the temporal trends were analysed using a segmented log-linear model. For spatial analysis, the Kernel estimator was used and the crude mortality rates were smoothed by the empirical Bayesian method. The space-time prospective scan statistics applied the Poisson's probability distribution model. There were 391 COVID-19 registered deaths, with the majority among ⩾60 years old (62%) and males (53%). The most prevalent comorbidities were hypertension (40%), diabetes (31%) and cardiovascular disease (15%). An increasing mortality trend across the state was observed, with a higher increase in the countryside. An active spatiotemporal cluster of mortality comprising the metropolitan area and neighbouring cities was identified. The trend of COVID-19 mortality in Sergipe was increasing and the spatial distribution of deaths was heterogeneous with progression towards the countryside. Therefore, the use of spatial analysis techniques may contribute to surveillance and control of COVID-19 pandemic.
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