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1.
BMJ Glob Health ; 6(4)2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33926892

RESUMO

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.


Assuntos
COVID-19/etnologia , COVID-19/mortalidade , Etnicidade/estatística & dados numéricos , Mortalidade Hospitalar/etnologia , Pneumonia Viral , Áreas de Pobreza , Características de Residência/estatística & dados numéricos , Adulto , Idoso , Idoso de 80 Anos ou mais , Brasil/epidemiologia , Estudos Transversais , Feminino , Disparidades nos Níveis de Saúde , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/epidemiologia , SARS-CoV-2 , Estudos Soroepidemiológicos , Fatores Socioeconômicos
2.
Nat Hum Behav ; 4(8): 856-865, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32737472

RESUMO

The first case of COVID-19 was detected in Brazil on 25 February 2020. We report and contextualize epidemiological, demographic and clinical findings for COVID-19 cases during the first 3 months of the epidemic. By 31 May 2020, 514,200 COVID-19 cases, including 29,314 deaths, had been reported in 75.3% (4,196 of 5,570) of municipalities across all five administrative regions of Brazil. The R0 value for Brazil was estimated at 3.1 (95% Bayesian credible interval = 2.4-5.5), with a higher median but overlapping credible intervals compared with some other seriously affected countries. A positive association between higher per-capita income and COVID-19 diagnosis was identified. Furthermore, the severe acute respiratory infection cases with unknown aetiology were associated with lower per-capita income. Co-circulation of six respiratory viruses was detected but at very low levels. These findings provide a comprehensive description of the ongoing COVID-19 epidemic in Brazil and may help to guide subsequent measures to control virus transmission.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus , Transmissão de Doença Infecciosa , Influenza Humana , Pandemias , Pneumonia Viral , Adulto , Idoso , Brasil/epidemiologia , COVID-19 , Teste para COVID-19 , Criança , Técnicas de Laboratório Clínico/métodos , Técnicas de Laboratório Clínico/estatística & dados numéricos , Coinfecção/epidemiologia , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/mortalidade , Infecções por Coronavirus/terapia , Infecções por Coronavirus/transmissão , Transmissão de Doença Infecciosa/prevenção & controle , Transmissão de Doença Infecciosa/estatística & dados numéricos , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Lactente , Influenza Humana/diagnóstico , Influenza Humana/epidemiologia , Influenza Humana/virologia , Masculino , Mortalidade , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Pneumonia Viral/terapia , Pneumonia Viral/transmissão , SARS-CoV-2 , Fatores Socioeconômicos , Tratamento Farmacológico da COVID-19
3.
Science ; 369(6508): 1255-1260, 2020 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-32703910

RESUMO

Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February and 11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.


Assuntos
Betacoronavirus/genética , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Número Básico de Reprodução , Teorema de Bayes , Betacoronavirus/classificação , Brasil/epidemiologia , COVID-19 , Teste para COVID-19 , Cidades/epidemiologia , Técnicas de Laboratório Clínico , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/virologia , Europa (Continente) , Evolução Molecular , Genoma Viral , Humanos , Modelos Genéticos , Modelos Estatísticos , Pandemias/prevenção & controle , Filogenia , Filogeografia , Pneumonia Viral/prevenção & controle , Pneumonia Viral/virologia , SARS-CoV-2 , Análise Espaço-Temporal , Viagem , População Urbana
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