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Spatiotemporal Pattern of COVID-19–Related Mortality during the First Year of the Pandemic in Brazil: A Population-based Study in a Region of High Social Vulnerability

Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the s...

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Detalles Bibliográficos
Autores principales: Almeida Andrade, Lucas, Silva da Paz, Wandklebson, Fontes Lima, Alanna G. C., da Conceição Araújo, Damião, Duque, Andrezza M., Peixoto, Marcus Valerius S., Góes, Marco Aurélio O., Freire de Souza, Carlos Dornels, Nunes Ribeiro, Caíque J., Almeida Lima, Shirley V. M., Bezerra-Santos, Márcio, Dantas dos Santos, Allan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society of Tropical Medicine and Hygiene 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733529/
https://www.ncbi.nlm.nih.gov/pubmed/34758451
http://dx.doi.org/10.4269/ajtmh.21-0744
Descripción
Sumario:Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space–time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19–related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2; P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.