Evidence map›Paper›PMID 34751273›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.

Andrea Brizzi, Charles Whittaker, Luciana M S Servo, Iwona Hawryluk, Carlos A Prete, William M de Souza, Renato S Aguiar, Leonardo J T Araujo, Leonardo S Bastos, Alexandra Blenkinsop and 31 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

41 authors.

Andrea BrizziDepartment of Mathematics, Imperial College London, London, United Kingdom.
Charles WhittakerMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Luciana M S ServoInstitute for Applied Economic Research - IPEA, Brasília, Brazil.
Iwona HawrylukMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Carlos A PreteDepartamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica da Universidade de São Paulo, São Paulo, Brazil.
William M de SouzaWorld Reference Center for Emerging Viruses and Arboviruses and Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA.
Renato S AguiarDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Leonardo J T AraujoLaboratory of Quantitative Pathology, Center of Pathology, Adolfo Lutz Institute, São Paulo, Brazil.
Leonardo S BastosPrograma de Computação Científica, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Alexandra BlenkinsopDepartment of Mathematics, Imperial College London, London, United Kingdom.
Lewis F BussDepartamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brasil.
Darlan CandidoDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Marcia C CastroDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, United States.
Silvia F CostaDepartamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brasil.
Julio CrodaDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, United States.
Andreza Aruska de Souza SantosLatin American Centre, University of Oxford, Oxford, United Kingdom.
Christopher DyeDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Seth FlaxmanDepartment of Computer Science, University of Oxford, Oxford, United Kingdom.
Paula L C FonsecaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Victor E V GeddesDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Bernardo GutierrezDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Philippe LemeyDepartment of Microbiology, Immunology and Transplantation, KU Leuven - University of Leuven, Leuven, Belgium.
Anna S LevinDepartment of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Thomas MellanMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Diego M BonfimDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Xenia MiscouridouDepartment of Mathematics, Imperial College London, London, United Kingdom.
Swapnil MishraMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Mélodie MonodDepartment of Mathematics, Imperial College London, London, United Kingdom.
Filipe R R MoreiraDepartamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Bruce NelsonEnvironmental Dynamics, INPA, National Institute for Amazon Research, Bairro Petropolis, Brazil.
Rafael H M PereiraInstitute for Applied Economic Research - IPEA, Brasília, Brazil.
Otavio RanzaniBarcelona Institute for Global Health, ISGlobal, Barcelona, Spain.
Ricardo P SchnekenbergNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Elizaveta SemenovaDepartment of Mathematics, Imperial College London, London, United Kingdom.
Raphael SonnabendMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Renan P SouzaDepartamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Xiaoyue XiDepartment of Mathematics, Imperial College London, London, United Kingdom.
Ester C SabinoPrograma de Computação Científica, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Nuno R FariaMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Samir BhattMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.
Oliver RatmannDepartment of Mathematics, Imperial College London, London, United Kingdom.

Funding

Medical Research Council MR/S019510/1
6 · The paper itself

Abstract

The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gamma's spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gamma's detection, and were largely transient after Gamma's detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazil's COVID-19 deaths in hospitals 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. NOTE: The following manuscript has appeared as 'Report 46 - Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals' at https://spiral.imperial.ac.uk:8443/handle/10044/1/91875 . ONE SENTENCE SUMMARY: COVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity.

Identifiers

PMID34751273
PMCPMC8575144

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.