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  4. Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
 
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Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
File(s)
s41591-022-01807-1.pdf (9.57 MB)
Published version (online)
Author(s)
Brizzi, Andrea
Whittaker, Charles
Servo, Luciana MS
Hawryluk, Iwona
Prete Jr, Carlos A
more
Type
Journal Article
Abstract
The SARS-CoV-2 Gamma variant of concern spread rapidly across Brazil since late 2020, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed Gamma’s spread across 14 state capitals, during which typically more than half of hospitalised patients aged 70 and over died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed prior to detection of Gamma. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil’s COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.
Date Issued
2022-05-10
Date Acceptance
2022-03-31
Citation
Nature Medicine, 2022, 28
URI
http://hdl.handle.net/10044/1/96349
URL
https://www.nature.com/articles/s41591-022-01807-1
DOI
https://www.dx.doi.org/10.1038/s41591-022-01807-1
ISSN
1078-8956
Publisher
Nature Research
Journal / Book Title
Nature Medicine
Volume
28
Copyright Statement
© 2022 The Author(s). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
License URL
http://creativecommons.org/licenses/by/4.0/
Sponsor
Medical Research Council-São Paulo Research Foundation (FAPESP)
Medical Research Council (MRC)
Engineering & Physical Science Research Council (EPSRC)
Wellcome Trust
UK Research and Innovation
Bill & Melinda Gates Foundation
Identifier
https://www.nature.com/articles/s41591-022-01807-1
Grant Number
MR/S0195/1
MR/R015600/1
EP/V002910/1
204311/Z/16/Z
MR/V038109/1
INV-034540
Subjects
Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Cell Biology
Medicine, Research & Experimental
Research & Experimental Medicine
NCOV-19 AZD1222 VACCINE
HEALTH
EFFICACY
Aged
Aged, 80 and over
Bayes Theorem
Brazil
COVID-19
Hospitals
Humans
SARS-CoV-2
Humans
Bayes Theorem
Aged
Aged, 80 and over
Hospitals
Brazil
COVID-19
SARS-CoV-2
11 Medical and Health Sciences
Immunology
Publication Status
Published
Date Publish Online
2022-06-11
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