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; Lewis F. Buss; Darlan Candido; Marcia C. Castro; Silvia F. Costa; Julio Croda; Andreza Aruska de Souza Santos; Christopher Dye; Seth Flaxman; Paula L.C. Fonseca; Victor E.V. Geddes; Bernardo Gutierrez; Philippe Lemey; Anna S. Levin; Thomas Mellan; Diego M. Bonfim; Xenia Miscouridou; Swapnil Mishra; Mélodie Monod; Filipe R.R. Moreira; Bruce Nelson; Rafael H.M. Pereira; Otavio Ranzani; Ricardo P. Schnekenberg; Elizaveta Semenova; Raphael Sonabend; Renan P. Souza; Xiaoyue Xi; Ester C. Sabino; Nuno R. Faria; Samir Bhatt; Oliver Ratmann

doi:10.1038/s41591-022-01807-1

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, Lewis F. Buss, Darlan Candido, Marcia C. Castro, Silvia F. Costa, Julio Croda, Andreza Aruska de Souza Santos, Christopher Dye, Seth Flaxman, Paula L.C. Fonseca, Victor E.V. GeddesBernardo Gutierrez, Philippe Lemey, Anna S. Levin, Thomas Mellan, Diego M. Bonfim, Xenia Miscouridou, Swapnil Mishra, Mélodie Monod, Filipe R.R. Moreira, Bruce Nelson, Rafael H.M. Pereira, Otavio Ranzani, Ricardo P. Schnekenberg, Elizaveta Semenova, Raphael Sonabend, Renan P. Souza, Xiaoyue Xi, Ester C. Sabino, Nuno R. Faria, Samir Bhatt, Oliver Ratmann

Microbiology, Immunology, and Molecular Genetics

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found 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.

Original language	English
Pages (from-to)	1476-1485
Number of pages	10
Journal	Nature Medicine
Volume	28
Issue number	7
DOIs	https://doi.org/10.1038/s41591-022-01807-1
State	Published - Jul 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s).

Funding

We thank all contributors to GISAID for making SARS-CoV-2 sequence data and metadata publicly available, as listed in ; all contributors to Rede Genomica Fiocruz for making SARS-CoV-2 variant frequency data publicly available; all members of the CADDE network for their comments throughout the project and earlier versions of the manuscript; O. G. Pybus, A. Rambaut and J. T. McCrone for their insightful comments on SARS-CoV-2 phylogenetic analyses; and the Imperial College Research Computing Service ( https://doi.org/10.14469/hpc/2232 ) for providing the computational resources to perform this study. This study was supported by the Medical Research Council-S\u00E3o Paulo Research Foundation (FAPESP) CADDE partnership award (MR/S0195/1 and FAPESP18/143890) ( https://caddecentre.org ), the Bill & Melinda Gates Foundation (INV-034540 and INV-034652) and the EPSRC through the EPSRC Centre for Doctoral Training in Modern Statistics and Statistical Machine Learning at Imperial and Oxford (EP/S023151/1). The authors acknowledge funding from the MRC Centre for Global Infectious Disease Analysis (MR/R015600/1), jointly funded by the UK Medical Reseach Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement, and also part of the EDCTP2 programme supported by the European Union. R.S.A. acknowledges support from the Rede Corona\u00F4mica BR MCTI/FINEP affiliated to RedeV\u00EDrus/MCTI (FINEP 01.20.0029.000462/20, CNPq 404096/20204), from CNPq (312688/2017-2 and 439119/2018-9), from MEC/CAPES (14/2020 -23072.211119/2020-10) and from FINEP (0494/20 01.20.0026.00). S.B. acknowledges support from UK Research and Innovation (MR/V038109/1), the MRC (MR/R015600/1), the Novo Nordisk Young Investigator Award (NNF20OC0059309), the Danish National Research Foundation via a chair position and the NIHR Health Protection Research Unit in Modelling Methodology. L.S.B. acknowledges support from Inova Fiocruz (48401485034116). D.S.C. acknowledges support from the Clarendon Fund, the University of Oxford Department of Zoology and Merton College. N.R.F. acknowledges support from the Wellcome Trust and the Royal Society (Sir Henry Dale Fellowship. 204311/Z/16/Z). S.F. acknowledges support from the EPSRC (EP/V002910/2). C.A.P. acknowledges support from FAPESP (2019/21858-0) and Funda\u00E7\u00E3o Faculdade de Medicina and Coordena\u00E7\u00E3o de Aperfei\u00E7oamento de Pessoal de N\u00EDvel Superior Brasil (CAPES). O.T.R. acknowledges support from the Instituto de Salud Carlos III (Sara Borrell fellowship, CD19/00110), from the Spanish Ministry of Science and Innovation and State Research Agency through the \u2018Centro de Excelencia Severo Ochoa 2019-2023\u2019 program (CEX2018-000806-S) and from the \u2018Generalitat de Catalunya\u2019 through the CERCA program. O.R. acknowledges support from the Bill & Melinda Gates Foundation (OPP1175094) and the Medical Research Council (MR/V038109/1). R.P.S. acknowledges support from the Rede Corona\u00F4mica BR MCTI/FINEP affiliated with RedeV\u00EDrus/MCTI (FINEP 01.20.0029.000462/20 and CNPq 404096/2020-4), from CNPq (310627/2018-4), from MEC/CAPES (14/2020 \u2013 23072.211119/2020-10), from FINEP (0494/20 01.20.0026.00) and from FAPEMIG (APQ-00475-20). W.M.S. acknowledges support from the Global Virus Network Fellowship and the National Institutes of Health (AI12094). C.W. acknowledges support from the Medical Research Council (Doctoral Training Partnership Studentship 1975152). P.L. acknowledges support from the European Research Council (grant 725422). We thank all contributors to GISAID for making SARS-CoV-2 sequence data and metadata publicly available, as listed in Methods ; all contributors to Rede Genomica Fiocruz for making SARS-CoV-2 variant frequency data publicly available; all members of the CADDE network for their comments throughout the project and earlier versions of the manuscript; O. G. Pybus, A. Rambaut and J. T. McCrone for their insightful comments on SARS-CoV-2 phylogenetic analyses; and the Imperial College Research Computing Service (https://doi.org/10.14469/hpc/2232) for providing the computational resources to perform this study.

Funders	Funder number
Fundação Universitaria do ABC, Faculdade de Medicina do ABC
University of Oxford Department of Zoology and Merton College
Commonwealth & Development Office
Spanish Ministry of Science and Innovation and State Research Agency
National Institute for Health and Care Research
Medical Engineering Centre King’s College London
Danmarks Grundforskningsfond
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
European Commission
Ministério da Ciência, Tecnologia e Inovação
H2020 European Research Council
Clarendon Fund
Foreign, Commonwealth and Development Office
UK Industrial Decarbonization Research and Innovation Centre
Imperial College Research Computing Service
Bill and Melinda Gates Foundation	INV-034540, INV-034652
Medical Research Council-São Paulo Research Foundation	MR/V038109/1, 310627/2018-4, MR/R015600/1, 14/2020 -23072.211119/2020-10
Horizon 2020 Framework Programme	725422
ICREA Foundation-Generalitat de Catalunya	OPP1175094
Royal Society of Medicine	204311/Z/16/Z, EP/V002910/2, 2019/21858-0
Engineering and Physical Sciences Research Council	EP/S023151/1
National Institutes of Health (NIH)	AI12094, 1975152
Fundação de Amparo à Pesquisa do Estado de Minas Gerais	APQ-00475-20
Medical Research Council-São Paulo Research Foundation	FAPESP18/143890, MR/S0195/1
Inova Fiocruz	48401485034116
Conselho Nacional de Desenvolvimento Científico e Tecnológico	312688/2017-2, 404096/2020-4, 439119/2018-9
Wellcome Trust	204311
Instituto de Salud Carlos III	CD19/00110
Financiadora de Estudos e Projetos	0494/20 01.20.0026.00
Centro de Excelencia Severo Ochoa 2019-2023	CEX2018-000806-S
Novo Nordisk A/S	NNF20OC0059309

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology

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10.1038/s41591-022-01807-1

Cite this

Brizzi, A., Whittaker, C., Servo, L. M. S., Hawryluk, I., Prete, C. A., de Souza, W. M., Aguiar, R. S., Araujo, L. J. T., Bastos, L. S., Blenkinsop, A., Buss, L. F., Candido, D., Castro, M. C., Costa, S. F., Croda, J., de Souza Santos, A. A., Dye, C., Flaxman, S., Fonseca, P. L. C., ... Ratmann, O. (2022). Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals. Nature Medicine, 28(7), 1476-1485. https://doi.org/10.1038/s41591-022-01807-1

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title = "Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals",

abstract = "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil{\textquoteright}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.",

author = "Andrea Brizzi and Charles Whittaker and Servo, \{Luciana M.S.\} and Iwona Hawryluk and Prete, \{Carlos A.\} and \{de Souza\}, \{William M.\} and Aguiar, \{Renato S.\} and Araujo, \{Leonardo J.T.\} and Bastos, \{Leonardo S.\} and Alexandra Blenkinsop and Buss, \{Lewis F.\} and Darlan Candido and Castro, \{Marcia C.\} and Costa, \{Silvia F.\} and Julio Croda and \{de Souza Santos\}, \{Andreza Aruska\} and Christopher Dye and Seth Flaxman and Fonseca, \{Paula L.C.\} and Geddes, \{Victor E.V.\} and Bernardo Gutierrez and Philippe Lemey and Levin, \{Anna S.\} and Thomas Mellan and Bonfim, \{Diego M.\} and Xenia Miscouridou and Swapnil Mishra and M{\'e}lodie Monod and Moreira, \{Filipe R.R.\} and Bruce Nelson and Pereira, \{Rafael H.M.\} and Otavio Ranzani and Schnekenberg, \{Ricardo P.\} and Elizaveta Semenova and Raphael Sonabend and Souza, \{Renan P.\} and Xiaoyue Xi and Sabino, \{Ester C.\} and Faria, \{Nuno R.\} and Samir Bhatt and Oliver Ratmann",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = jul,

doi = "10.1038/s41591-022-01807-1",

language = "English",

volume = "28",

pages = "1476--1485",

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Brizzi, A, Whittaker, C, Servo, LMS, Hawryluk, I, Prete, CA, de Souza, WM, Aguiar, RS, Araujo, LJT, Bastos, LS, Blenkinsop, A, Buss, LF, Candido, D, Castro, MC, Costa, SF, Croda, J, de Souza Santos, AA, Dye, C, Flaxman, S, Fonseca, PLC, Geddes, VEV, Gutierrez, B, Lemey, P, Levin, AS, Mellan, T, Bonfim, DM, Miscouridou, X, Mishra, S, Monod, M, Moreira, FRR, Nelson, B, Pereira, RHM, Ranzani, O, Schnekenberg, RP, Semenova, E, Sonabend, R, Souza, RP, Xi, X, Sabino, EC, Faria, NR, Bhatt, S & Ratmann, O 2022, 'Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals', Nature Medicine, vol. 28, no. 7, pp. 1476-1485. https://doi.org/10.1038/s41591-022-01807-1

TY - JOUR

T1 - Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

AU - Brizzi, Andrea

AU - Whittaker, Charles

AU - Servo, Luciana M.S.

AU - Hawryluk, Iwona

AU - Prete, Carlos A.

AU - de Souza, William M.

AU - Aguiar, Renato S.

AU - Araujo, Leonardo J.T.

AU - Bastos, Leonardo S.

AU - Blenkinsop, Alexandra

AU - Buss, Lewis F.

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AU - de Souza Santos, Andreza Aruska

AU - Dye, Christopher

AU - Flaxman, Seth

AU - Fonseca, Paula L.C.

AU - Geddes, Victor E.V.

AU - Gutierrez, Bernardo

AU - Lemey, Philippe

AU - Levin, Anna S.

AU - Mellan, Thomas

AU - Bonfim, Diego M.

AU - Miscouridou, Xenia

AU - Mishra, Swapnil

AU - Monod, Mélodie

AU - Moreira, Filipe R.R.

AU - Nelson, Bruce

AU - Pereira, Rafael H.M.

AU - Ranzani, Otavio

AU - Schnekenberg, Ricardo P.

AU - Semenova, Elizaveta

AU - Sonabend, Raphael

AU - Souza, Renan P.

AU - Xi, Xiaoyue

AU - Sabino, Ester C.

AU - Faria, Nuno R.

AU - Bhatt, Samir

AU - Ratmann, Oliver

PY - 2022/7

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N2 - The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found 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.

AB - The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found 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.

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Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Abstract

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