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

Autor:	Brizzi A; Department of Mathematics, Imperial College London, London, United Kingdom., Whittaker C; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom., Servo LMS; Institute for Applied Economic Research - IPEA, Brasília, Brazil., Hawryluk I; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom., Prete CA Jr; Departamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica da Universidade de São Paulo, São Paulo, Brazil., de Souza WM; World Reference Center for Emerging Viruses and Arboviruses and Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA., Aguiar RS; Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.; Instituto D'Or de Pesquisa e Ensino (IDOR), Rio de Janeiro, Brazil., Araujo LJT; Laboratory of Quantitative Pathology, Center of Pathology, Adolfo Lutz Institute, São Paulo, Brazil., Bastos LS; Programa de Computação Científica, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil., Blenkinsop A; Department of Mathematics, Imperial College London, London, United Kingdom., Buss LF; Departamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brasil., Candido D; Department of Zoology, University of Oxford, Oxford, United Kingdom., Castro MC; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, United States., Costa SF; Departamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brasil., Croda J; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, United States., de Souza Santos AA; Latin American Centre, University of Oxford, Oxford, United Kingdom., Dye C; Department of Zoology, University of Oxford, Oxford, United Kingdom., Flaxman S; Department of Computer Science, University of Oxford, Oxford, United Kingdom., Fonseca PLC; Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Geddes VEV; Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Gutierrez B; Department of Zoology, University of Oxford, Oxford, United Kingdom., Lemey P; Department of Microbiology, Immunology and Transplantation, KU Leuven - University of Leuven, Leuven, Belgium., Levin AS; Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom., Mellan T; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom., Bonfim DM; Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Miscouridou X; Department of Mathematics, Imperial College London, London, United Kingdom., Mishra S; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.; Section of Epidemiology, School of Public Health, University of Copenhagen, Denmark, Copenhagen., Monod M; Department of Mathematics, Imperial College London, London, United Kingdom., Moreira FRR; Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil., Nelson B; Environmental Dynamics, INPA, National Institute for Amazon Research, Bairro Petropolis, Brazil., Pereira RHM; Institute for Applied Economic Research - IPEA, Brasília, Brazil., Ranzani O; Barcelona Institute for Global Health, ISGlobal, Barcelona, Spain., Schnekenberg RP; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom., Semenova E; Department of Mathematics, Imperial College London, London, United Kingdom., Sonnabend R; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom., Souza RP; Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil., Xi X; Department of Mathematics, Imperial College London, London, United Kingdom., Sabino EC; Programa de Computação Científica, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil., Faria NR; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.; Department of Zoology, University of Oxford, Oxford, United Kingdom.; Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.; Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil., Bhatt S; MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, United Kingdom.; Section of Epidemiology, School of Public Health, University of Copenhagen., Ratmann O; Department of Mathematics, Imperial College London, London, United Kingdom.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2021 Nov 02. Date of Electronic Publication: 2021 Nov 02.
DOI:	10.1101/2021.11.01.21265731
Abstrakt:	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.
Databáze:	MEDLINE
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