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COVID-19 mortality in an area of northeast Brazil: epidemiological characteristics and prospective spatiotemporal modelling.
Andrade, L A; Gomes, D S; Lima, S V M A; Duque, A M; Melo, M S; Góes, M A O; Ribeiro, C J N; Peixoto, M V S; Souza, C D F; Santos, A D.
  • Andrade LA; Graduate Nursing Programme, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Gomes DS; Collective Health Research Center, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Lima SVMA; Collective Health Research Center, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Duque AM; Graduate Programme in Parasitic Biology, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Melo MS; Collective Health Research Center, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Góes MAO; Department of Nursing, Federal University of Sergipe, Lagarto, Sergipe, Brazil.
  • Ribeiro CJN; Collective Health Research Center, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Peixoto MVS; Department of Occupational Therapy, Federal University of Sergipe, Lagarto, Sergipe, Brazil.
  • Souza CDF; Graduate Nursing Programme, Federal University of Sergipe, Aracaju, Sergipe, Brazil.
  • Santos AD; Sergipe State Department of Health, Aracaju, Sergipe, Brazil.
Epidemiol Infect ; 148: e288, 2020 12 01.
Article in English | MEDLINE | ID: covidwho-965256
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Topics: Long Covid Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: South America / Brazil Language: English Journal: Epidemiol Infect Journal subject: Communicable Diseases / Epidemiology Year: 2020 Document Type: Article Affiliation country: S0950268820002915

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Topics: Long Covid Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: South America / Brazil Language: English Journal: Epidemiol Infect Journal subject: Communicable Diseases / Epidemiology Year: 2020 Document Type: Article Affiliation country: S0950268820002915