Cargando…
Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
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 ac...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575144/ https://www.ncbi.nlm.nih.gov/pubmed/34751273 http://dx.doi.org/10.1101/2021.11.01.21265731 |
_version_ | 1784595615150243840 |
---|---|
author | Brizzi, Andrea Whittaker, Charles Servo, Luciana M. S. Hawryluk, Iwona Prete, Carlos A. de Souza, William M. Aguiar, Renato S. Araujo, Leonardo J. T. Bastos, Leonardo S. Blenkinsop, Alexandra Buss, Lewis F. Candido, Darlan Castro, Marcia C. Costa, Silvia F. Croda, Julio de Souza Santos, Andreza Aruska Dye, Christopher Flaxman, Seth Fonseca, Paula L. C. Geddes, Victor E. V. Gutierrez, Bernardo Lemey, Philippe Levin, Anna S. Mellan, Thomas Bonfim, Diego M. Miscouridou, Xenia Mishra, Swapnil Monod, Mélodie Moreira, Filipe R. R. Nelson, Bruce Pereira, Rafael H. M. Ranzani, Otavio Schnekenberg, Ricardo P. Semenova, Elizaveta Sonnabend, Raphael Souza, Renan P. Xi, Xiaoyue Sabino, Ester C. Faria, Nuno R. Bhatt, Samir Ratmann, Oliver |
author_facet | Brizzi, Andrea Whittaker, Charles Servo, Luciana M. S. Hawryluk, Iwona Prete, Carlos A. de Souza, William M. Aguiar, Renato S. Araujo, Leonardo J. T. Bastos, Leonardo S. Blenkinsop, Alexandra Buss, Lewis F. Candido, Darlan Castro, Marcia C. Costa, Silvia F. Croda, Julio de Souza Santos, Andreza Aruska Dye, Christopher Flaxman, Seth Fonseca, Paula L. C. Geddes, Victor E. V. Gutierrez, Bernardo Lemey, Philippe Levin, Anna S. Mellan, Thomas Bonfim, Diego M. Miscouridou, Xenia Mishra, Swapnil Monod, Mélodie Moreira, Filipe R. R. Nelson, Bruce Pereira, Rafael H. M. Ranzani, Otavio Schnekenberg, Ricardo P. Semenova, Elizaveta Sonnabend, Raphael Souza, Renan P. Xi, Xiaoyue Sabino, Ester C. Faria, Nuno R. Bhatt, Samir Ratmann, Oliver |
author_sort | Brizzi, Andrea |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8575144 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-85751442021-11-09 Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals Brizzi, Andrea Whittaker, Charles Servo, Luciana M. S. Hawryluk, Iwona Prete, Carlos A. de Souza, William M. Aguiar, Renato S. Araujo, Leonardo J. T. Bastos, Leonardo S. Blenkinsop, Alexandra Buss, Lewis F. Candido, Darlan Castro, Marcia C. Costa, Silvia F. Croda, Julio de Souza Santos, Andreza Aruska Dye, Christopher Flaxman, Seth Fonseca, Paula L. C. Geddes, Victor E. V. Gutierrez, Bernardo Lemey, Philippe Levin, Anna S. Mellan, Thomas Bonfim, Diego M. Miscouridou, Xenia Mishra, Swapnil Monod, Mélodie Moreira, Filipe R. R. Nelson, Bruce Pereira, Rafael H. M. Ranzani, Otavio Schnekenberg, Ricardo P. Semenova, Elizaveta Sonnabend, Raphael Souza, Renan P. Xi, Xiaoyue Sabino, Ester C. Faria, Nuno R. Bhatt, Samir Ratmann, Oliver medRxiv Article 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. Cold Spring Harbor Laboratory 2021-11-02 /pmc/articles/PMC8575144/ /pubmed/34751273 http://dx.doi.org/10.1101/2021.11.01.21265731 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Brizzi, Andrea Whittaker, Charles Servo, Luciana M. S. Hawryluk, Iwona Prete, Carlos A. de Souza, William M. Aguiar, Renato S. Araujo, Leonardo J. T. Bastos, Leonardo S. Blenkinsop, Alexandra Buss, Lewis F. Candido, Darlan Castro, Marcia C. Costa, Silvia F. Croda, Julio de Souza Santos, Andreza Aruska Dye, Christopher Flaxman, Seth Fonseca, Paula L. C. Geddes, Victor E. V. Gutierrez, Bernardo Lemey, Philippe Levin, Anna S. Mellan, Thomas Bonfim, Diego M. Miscouridou, Xenia Mishra, Swapnil Monod, Mélodie Moreira, Filipe R. R. Nelson, Bruce Pereira, Rafael H. M. Ranzani, Otavio Schnekenberg, Ricardo P. Semenova, Elizaveta Sonnabend, Raphael Souza, Renan P. Xi, Xiaoyue Sabino, Ester C. Faria, Nuno R. Bhatt, Samir Ratmann, Oliver Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals |
title | Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals |
title_full | Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals |
title_fullStr | Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals |
title_full_unstemmed | Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals |
title_short | Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals |
title_sort | report 46: factors driving extensive spatial and temporal fluctuations in covid-19 fatality rates in brazilian hospitals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575144/ https://www.ncbi.nlm.nih.gov/pubmed/34751273 http://dx.doi.org/10.1101/2021.11.01.21265731 |
work_keys_str_mv | AT brizziandrea report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT whittakercharles report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT servolucianams report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT hawrylukiwona report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT pretecarlosa report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT desouzawilliamm report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT aguiarrenatos report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT araujoleonardojt report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT bastosleonardos report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT blenkinsopalexandra report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT busslewisf report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT candidodarlan report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT castromarciac report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT costasilviaf report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT crodajulio report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT desouzasantosandrezaaruska report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT dyechristopher report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT flaxmanseth report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT fonsecapaulalc report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT geddesvictorev report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT gutierrezbernardo report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT lemeyphilippe report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT levinannas report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT mellanthomas report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT bonfimdiegom report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT miscouridouxenia report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT mishraswapnil report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT monodmelodie report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT moreirafiliperr report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT nelsonbruce report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT pereirarafaelhm report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT ranzaniotavio report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT schnekenbergricardop report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT semenovaelizaveta report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT sonnabendraphael report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT souzarenanp report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT xixiaoyue report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT sabinoesterc report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT farianunor report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT bhattsamir report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals AT ratmannoliver report46factorsdrivingextensivespatialandtemporalfluctuationsincovid19fatalityratesinbrazilianhospitals |