Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil
Introduction Little evidence exists on the differential health effects of COVID-19 on disadvantaged population groups. Here we characterise the differential risk of hospitalisation and death in São Paulo state, Brazil, and show how vulnerability to COVID-19 is shaped by socioeconomic inequalities.Me...
| Published in: | BMJ Global Health |
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BMJ Publishing Group
2021-04-01
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| Online Access: | https://gh.bmj.com/content/6/4/e004959.full |
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| author | Chieh-hsi Wu Sabrina L Li Rafael H M Pereira Carlos A Prete Jr Alexander E Zarebski Lucas Emanuel Pedro J H Alves Pedro S Peixoto Carlos K V Braga Andreza Aruska de Souza Santos William M de Souza Rogerio J Barbosa Lewis F Buss Alfredo Mendrone Cesar de Almeida-Neto Suzete C Ferreira Nanci A Salles Izabel Marcilio Nelson Gouveia Vitor H Nascimento Ester C Sabino Nuno R Faria Jane P Messina |
| author_facet | Chieh-hsi Wu Sabrina L Li Rafael H M Pereira Carlos A Prete Jr Alexander E Zarebski Lucas Emanuel Pedro J H Alves Pedro S Peixoto Carlos K V Braga Andreza Aruska de Souza Santos William M de Souza Rogerio J Barbosa Lewis F Buss Alfredo Mendrone Cesar de Almeida-Neto Suzete C Ferreira Nanci A Salles Izabel Marcilio Nelson Gouveia Vitor H Nascimento Ester C Sabino Nuno R Faria Jane P Messina |
| author_sort | Chieh-hsi Wu |
| collection | DOAJ |
| container_title | BMJ Global Health |
| description | Introduction Little evidence exists on the differential health effects of COVID-19 on disadvantaged population groups. Here we characterise the differential risk of hospitalisation and death in São Paulo state, Brazil, and show how vulnerability to COVID-19 is shaped by socioeconomic inequalities.Methods We conducted a cross-sectional study using hospitalised severe acute respiratory infections notified from March to August 2020 in the Sistema de Monitoramento Inteligente de São Paulo database. We examined the risk of hospitalisation and death by race and socioeconomic status using multiple data sets for individual-level and spatiotemporal analyses. We explained these inequalities according to differences in daily mobility from mobile phone data, teleworking behaviour and comorbidities.Results Throughout the study period, patients living in the 40% poorest areas were more likely to die when compared with patients living in the 5% wealthiest areas (OR: 1.60, 95% CI 1.48 to 1.74) and were more likely to be hospitalised between April and July 2020 (OR: 1.08, 95% CI 1.04 to 1.12). Black and Pardo individuals were more likely to be hospitalised when compared with White individuals (OR: 1.41, 95% CI 1.37 to 1.46; OR: 1.26, 95% CI 1.23 to 1.28, respectively), and were more likely to die (OR: 1.13, 95% CI 1.07 to 1.19; 1.07, 95% CI 1.04 to 1.10, respectively) between April and July 2020. Once hospitalised, patients treated in public hospitals were more likely to die than patients in private hospitals (OR: 1.40%, 95% CI 1.34% to 1.46%). Black individuals and those with low education attainment were more likely to have one or more comorbidities, respectively (OR: 1.29, 95% CI 1.19 to 1.39; 1.36, 95% CI 1.27 to 1.45).Conclusions Low-income and Black and Pardo communities are more likely to die with COVID-19. This is associated with differential access to quality healthcare, ability to self-isolate and the higher prevalence of comorbidities. |
| format | Article |
| id | doaj-art-e0ddfb2984bf4e5599d8d5a3632c60ee |
| institution | Directory of Open Access Journals |
| issn | 2059-7908 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| spelling | doaj-art-e0ddfb2984bf4e5599d8d5a3632c60ee2025-08-20T00:57:44ZengBMJ Publishing GroupBMJ Global Health2059-79082021-04-016410.1136/bmjgh-2021-004959Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, BrazilChieh-hsi Wu0Sabrina L Li1Rafael H M Pereira2Carlos A Prete Jr3Alexander E Zarebski4Lucas Emanuel5Pedro J H Alves6Pedro S Peixoto7Carlos K V Braga8Andreza Aruska de Souza Santos9William M de Souza10Rogerio J Barbosa11Lewis F Buss12Alfredo Mendrone13Cesar de Almeida-Neto14Suzete C Ferreira15Nanci A Salles16Izabel Marcilio17Nelson Gouveia18Vitor H Nascimento19Ester C Sabino20Nuno R Faria21Jane P Messina22Mathematical Sciences, University of Southampton, Southampton, UK1 School of Geography, University of Nottingham, Nottingham, UKInstitute of Applied Economic Research, Brasília, BrazilDepartment of Electronic Systems Engineering, University of São Paulo, São Paulo, Brazil4 School of Mathematics and Statistics, The University of Melbourne, Melbourne, Victoria, Australia1 Center of Data and Knowledge Integration for Health, Fiocruz/BA, Salvador, BrazilInstitute of Applied Economic Research, Brasília, BrazilDepartment of Applied Mathematics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo, BrazilInstitute of Applied Economic Research, Brasília, Brazil6 Oxford School of Global and Area Studies and Latin American Centre, University of Oxford, Oxford, UKDepartment of Zoology, University of Oxford, Oxford, UKInstitute of Social and Political Studies (IESP), State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazilacademic clinical fellow in general practiceFundação Pró-Sangue Hemocentro de São Paulo, São Paulo, BrazilFundação Pró-Sangue Hemocentro de São Paulo, São Paulo, BrazilFundação Pró-Sangue Hemocentro de São Paulo, São Paulo, BrazilFundação Pró-Sangue Hemocentro de São Paulo, São Paulo, BrazilHospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo, University of São Paulo, São Paulo, BrazilDepartment of Preventive Medicine, University of São Paulo Medical School, São Paulo, Brazil3 Department of Electronic Systems Engineering, University of São Paulo, São Paulo, Brazil8 Departamento de Molestias Infecciosas e Parasitarias & Instituto de Medicina Tropical da Faculdade de Medicina, University of São Paulo, São Paulo, BrazilDepartment of Zoology, University of Oxford, Oxford, UK2 School of Geography and the Environment, University of Oxford, Oxford, UKIntroduction Little evidence exists on the differential health effects of COVID-19 on disadvantaged population groups. Here we characterise the differential risk of hospitalisation and death in São Paulo state, Brazil, and show how vulnerability to COVID-19 is shaped by socioeconomic inequalities.Methods We conducted a cross-sectional study using hospitalised severe acute respiratory infections notified from March to August 2020 in the Sistema de Monitoramento Inteligente de São Paulo database. We examined the risk of hospitalisation and death by race and socioeconomic status using multiple data sets for individual-level and spatiotemporal analyses. We explained these inequalities according to differences in daily mobility from mobile phone data, teleworking behaviour and comorbidities.Results Throughout the study period, patients living in the 40% poorest areas were more likely to die when compared with patients living in the 5% wealthiest areas (OR: 1.60, 95% CI 1.48 to 1.74) and were more likely to be hospitalised between April and July 2020 (OR: 1.08, 95% CI 1.04 to 1.12). Black and Pardo individuals were more likely to be hospitalised when compared with White individuals (OR: 1.41, 95% CI 1.37 to 1.46; OR: 1.26, 95% CI 1.23 to 1.28, respectively), and were more likely to die (OR: 1.13, 95% CI 1.07 to 1.19; 1.07, 95% CI 1.04 to 1.10, respectively) between April and July 2020. Once hospitalised, patients treated in public hospitals were more likely to die than patients in private hospitals (OR: 1.40%, 95% CI 1.34% to 1.46%). Black individuals and those with low education attainment were more likely to have one or more comorbidities, respectively (OR: 1.29, 95% CI 1.19 to 1.39; 1.36, 95% CI 1.27 to 1.45).Conclusions Low-income and Black and Pardo communities are more likely to die with COVID-19. This is associated with differential access to quality healthcare, ability to self-isolate and the higher prevalence of comorbidities.https://gh.bmj.com/content/6/4/e004959.full |
| spellingShingle | Chieh-hsi Wu Sabrina L Li Rafael H M Pereira Carlos A Prete Jr Alexander E Zarebski Lucas Emanuel Pedro J H Alves Pedro S Peixoto Carlos K V Braga Andreza Aruska de Souza Santos William M de Souza Rogerio J Barbosa Lewis F Buss Alfredo Mendrone Cesar de Almeida-Neto Suzete C Ferreira Nanci A Salles Izabel Marcilio Nelson Gouveia Vitor H Nascimento Ester C Sabino Nuno R Faria Jane P Messina Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil |
| title | Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil |
| title_full | Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil |
| title_fullStr | Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil |
| title_full_unstemmed | Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil |
| title_short | Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil |
| title_sort | higher risk of death from covid 19 in low income and non white populations of sao paulo brazil |
| url | https://gh.bmj.com/content/6/4/e004959.full |
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