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Since May 2020, we have been conducting a comprehensive study to understand the natural history of SARS-CoV-2 infection in Rio de Janeiro, Brazil. Our focus has been on following families, systematically collecting respiratory tract swabs and blood samples, monitoring symptoms, and gathering data on vaccine status. This paper aims to describe the household cohort across five epidemic waves of SARS-CoV-2, providing an overview of the collected data and a description of the epidemiological, clinical, and immunological characteristics and incidence of SARS-CoV-2 infection. Our cohort includes 691 participants from 189 households. During the five epidemic waves, we detected 606 infections. The incidence density of SARS-CoV-2 infection ranged from 4 (Delta) to 56 (B.1.1.33) per 1,000 person-week, with a peak in wave B.1.1.33 in all age groups. The seroprevalence of SARS-CoV-2 antibodies (IgG anti spike protein) varied from 37%, in the pre-VoC period, to 99%, in the Omicron period, progressively increasing after each wave in a similar manner regardless of age. As we have monitored the cohort continuously since the beginning of the pandemic, we were able to collect data across different scenarios according to the predominant lineage in circulation. Via active monitoring of families, we were able to carry out an epidemiological surveillance on SARS-CoV-2, including its variants, persistence of symptoms, and changes in immunity over time in the population, contributing to knowledge of the natural history of SARS-CoV-2 infection.
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COVID-19 , Composición Familiar , SARS-CoV-2 , Humanos , COVID-19/epidemiología , COVID-19/inmunología , Brasil/epidemiología , Adulto , Masculino , Femenino , SARS-CoV-2/inmunología , Persona de Mediana Edad , Niño , Adolescente , Adulto Joven , Preescolar , Estudios de Cohortes , Incidencia , Lactante , Anticuerpos Antivirales/sangre , Estudios Seroepidemiológicos , Estudios de Seguimiento , AncianoRESUMEN
The influenza-like illness (ILI) sentinel surveillance operates in Brazil to identify respiratory viruses of public health relevance circulating in the country and was first implemented in 2000. Recently, the COVID-19 pandemic reinforced the importance of early detection of the circulation of new viruses in Brazil. Therefore, an analysis of the design of the ILI sentinel surveillance is timely. To this end, we simulated a sentinel surveillance network, identifying the municipalities that would be part of the network according to the criteria defined in the design of the ILI sentinel surveillance and, based on data from tested cases of severe acute respiratory illness (SARI) from 2014 to 2019, we drew samples for each sentinel municipality per epidemiological week. The draw was performed 1,000 times, obtaining the median and 95% quantile interval (95%QI) of virus positivity by Federative Unit and epidemiological week. According to the ILI sentinel surveillance design criteria, sentinel units would be in 64 municipalities, distributed mainly in capitals and their metropolitan areas, recommending 690 weekly samples. The design showed good sensitivity (91.65% considering the 95%QI) for qualitatively detecting respiratory viruses, even those with low circulation. However, there was important uncertainty in the quantitative estimate of positivity, reaching at least 20% in 11.34% of estimates. The results presented here aim to assist in evaluating and updating the ILI sentinel surveillance design. Strategies to reduce uncertainty in positivity estimates need to be evaluated, as does the need for greater spatial coverage.
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COVID-19 , Gripe Humana , Vigilancia de Guardia , Humanos , Brasil/epidemiología , Gripe Humana/epidemiología , Gripe Humana/diagnóstico , COVID-19/epidemiología , COVID-19/diagnóstico , SARS-CoV-2 , PandemiasRESUMEN
BACKGROUND: The occurrence of multimorbidity and its impacts have differentially affected population subgroups. Evidence on its incidence has mainly come from high-income regions, with limited exploration of racial disparities. This study investigated the association between racial groups and the development of multimorbidity and chronic conditions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). METHODS: Data from self-reported white, brown (pardos or mixed-race), and black participants at baseline of ELSA-Brasil (2008-2010) who were at risk for multimorbidity were analysed. The development of chronic conditions was assessed through in-person visits and self-reported diagnosis via telephone until the third follow-up visit (2017-2019). Multimorbidity was defined when, at the follow-up visit, the participant had two or more morbidities. Cumulative incidences, incidence rates, and adjusted incidence rate ratios (IRRs) were estimated using Poisson models. RESULTS: Over an 8.3-year follow-up, compared to white participants: browns had a 27% greater incidence of hypertension and obesity; and blacks had a 62% and 45% greater incidence, respectively. Blacks also had 58% more diabetes. The cancer incidence was greater among whites. Multimorbidity affected 41% of the participants, with a crude incidence rate of 57.5 cases per 1000 person-years (ranging from 56.3 for whites to 63.9 for blacks). Adjusted estimates showed a 20% higher incidence of multimorbidity in black participants compared to white participants (IRR: 1.20; 95% CI: 1.05-1.38). CONCLUSIONS: Significant racial disparities in the risk of chronic conditions and multimorbidity were observed. Many associations revealed a gradient increase in illness risk according to darker skin tones. Addressing fundamental causes such as racism and racial discrimination, alongside considering social determinants of health, is vital for comprehensive multimorbidity care. Intersectoral, equitable policies are essential for ensuring health rights for historically marginalized groups.
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Multimorbilidad , Humanos , Brasil/epidemiología , Femenino , Masculino , Persona de Mediana Edad , Estudios Prospectivos , Enfermedad Crónica , Adulto , Disparidades en el Estado de Salud , Estudios Longitudinales , Anciano , Incidencia , Población Blanca/estadística & datos numéricos , Factores SocioeconómicosRESUMEN
OBJECTIVE: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. METHODS: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. RESULTS: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. CONCLUSION: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.
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COVID-19 , Humanos , COVID-19/epidemiología , Brasil/epidemiología , Análisis Espacio-Temporal , Pandemias , IncidenciaRESUMEN
ABSTRACT Objective: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. Methods: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. Results: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. Conclusion: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.
RESUMO Objetivo: Analisar a dinâmica espaço-temporal de COVID-19 no estado do Rio de Janeiro nas nove regiões de saúde, entre março de 2020 e dezembro de 2022. Métodos: Utilizou-se o modelo de Poisson com efeitos aleatórios para suavizar a curva de incidência de hospitalizações por COVID-19 notificadas no Sistema de Informação da Vigilância Epidemiológica da Gripe (Sivep-Gripe) para verificar a sincronicidade da epidemia no estado. Resultados: A epidemia de COVID-19 no estado é caracterizada pela presença de sete picos no período analisado correspondentes a sete variantes encontradas. Identificou-se uma assincronicidade nas hospitalizações, variando de acordo com as diferentes variantes do vírus nas nove regiões de saúde do estado. Os picos de incidência das hospitalizações variaram de 1 a 12 casos por 100 mil habitantes no decorrer da pandemia. Conclusão: Essa análise espaço-temporal é extensível em outros cenários, sendo possível o monitoramento e a tomada de decisões de controle de doenças epidêmicas em várias áreas.
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Abstract: The influenza-like illness (ILI) sentinel surveillance operates in Brazil to identify respiratory viruses of public health relevance circulating in the country and was first implemented in 2000. Recently, the COVID-19 pandemic reinforced the importance of early detection of the circulation of new viruses in Brazil. Therefore, an analysis of the design of the ILI sentinel surveillance is timely. To this end, we simulated a sentinel surveillance network, identifying the municipalities that would be part of the network according to the criteria defined in the design of the ILI sentinel surveillance and, based on data from tested cases of severe acute respiratory illness (SARI) from 2014 to 2019, we drew samples for each sentinel municipality per epidemiological week. The draw was performed 1,000 times, obtaining the median and 95% quantile interval (95%QI) of virus positivity by Federative Unit and epidemiological week. According to the ILI sentinel surveillance design criteria, sentinel units would be in 64 municipalities, distributed mainly in capitals and their metropolitan areas, recommending 690 weekly samples. The design showed good sensitivity (91.65% considering the 95%QI) for qualitatively detecting respiratory viruses, even those with low circulation. However, there was important uncertainty in the quantitative estimate of positivity, reaching at least 20% in 11.34% of estimates. The results presented here aim to assist in evaluating and updating the ILI sentinel surveillance design. Strategies to reduce uncertainty in positivity estimates need to be evaluated, as does the need for greater spatial coverage.
Resumen: La vigilancia centinela de la enfermedad tipo infuenza (ETI) funciona en Brasil para identificar los virus respiratorios de importancia para la salud pública que circulan en el país y comenzó a ser implementada en 2000. Recientemente, la pandemia de COVID-19 ha reforzado la importancia de la detección temprana de la circulación de nuevos virus en el territorio brasileño. Así, se hace oportuno un análisis del diseño de la vigilancia centinela de la ETI. Para ello, simulamos una red centinela identificando los municipios que formarían parte de la red según los criterios definidos en el diseño de la vigilancia centinela de la ETI y, a partir de los datos de casos testados de infección respiratoria aguda grave (IRAG) de 2014 a 2019, se extrajeron muestras para cada municipio centinela por semana epidemiológica. El sorteo se repitió 1.000 veces y se obtuvo la mediana y el intervalo cuantílico del 95% (IC95%) de la positividad por virus, por Unidad Federativa y semana epidemiológica. Según los criterios del diseño de la vigilancia centinela de la ETI, unidades centinelas estarían en 64 municipios, distribuidas principalmente en capitales y zonas metropolitanas de las capitales, preconizando 690 muestras semanales. El diseño presentó una buena sensibilidad (total de 91,65% considerando el IC95%) para la detección cualitativa de los virus respiratorios, incluso los de baja circulación. Sin embargo, hubo una importante incertidumbre en la estimación cuantitativa de la positividad, alcanzando al menos el 20% en el 11,34% de las estimaciones. Los resultados presentados aquí tienen como objetivo ayudar en la evaluación y actualización del diseño de la red centinela. Es necesario evaluar las estrategias para reducir la incertidumbre en las estimaciones de positividad, al igual que la necesidad de una mayor cobertura espacial.
Resumo: A vigilância sentinela de síndrome gripal atua no Brasil identificando os vírus respiratórios de importância para a saúde pública circulantes no país, e começou a ser implementada em 2000. Recentemente, a pandemia de COVID-19 reforçou a importância da detecção precoce de novos vírus em circulação no território brasileiro. Assim, se faz oportuna uma análise do desenho da vigilância sentinela de síndrome gripal. Para tal, simulamos uma rede sentinela, identificando os municípios que fariam parte da rede segundo os critérios definidos no desenho da vigilância sentinela de síndrome gripal, e, a partir dos dados de casos testados de síndrome respiratória aguda grave (SRAG) de 2014 a 2019, sorteamos amostras para cada município sentinela por semana epidemiológica. O sorteio foi repetido mil vezes, obtendo-se a mediana e intervalo quantílico de 95% (IQ95%) da positividade para cada vírus por Unidade Federativa e semana epidemiológica. Segundo os critérios do desenho da vigilância sentinela de síndrome gripal, unidades sentinelas estariam em 64 municípios, distribuídas principalmente em capitais e suas zonas metropolitanas, o que preconizou 690 amostras semanais. O desenho apresentou boa sensibilidade (total de 91,65%, considerando o IQ95%) para a detecção qualitativa dos vírus respiratórios, mesmo os de baixa circulação. Porém, houve importante incerteza na estimativa quantitativa de positividade, chegando a, pelo menos, 20% em 11,34% das estimativas. Os resultados aqui apresentados visam auxiliar a avaliação e a atualização do desenho da rede sentinela. Estratégias para reduzir a incerteza nas estimativas de positividade precisam ser avaliadas, assim como a necessidade de maior cobertura espacial.
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OBJECTIVE: The present study carried out an analysis of survival according to the status of registration with Primary Health Care (PHC) and of factors associated with death from COVID-19, in cases residing in Programmatic Area 3.1 (PA3.1) with a diagnosis of diabetes (in the notification form or in the electronic medical record), of the Municipality of Rio de Janeiro (RJ), Brazil, in 2020-2021. METHODS: A probabilistic linkage of databases was performed based on information on cases notified as COVID-19 and data from the electronic medical records of people living with diabetes. A survival analysis was carried out, using the Cox regression model stratified by age group and adjusted for confounding variables. RESULTS: Individuals registered with the PHC of PA3.1 had almost twice the risk of death from COVID-19 (adjusted hazard ratio [HRadj]=1.91) when compared to those unregistered. This association was stronger in individuals aged 18 to 59 years registered with the PHC (HRadj=2.82) than in individuals aged 60 years or over (HRadj=1.56). CONCLUSION: Surveillance strategies for identifying and adequately monitoring higher-risk groups, among individuals living with diabetes, within the scope of Primary Health Care, can contribute to reducing mortality from COVID-19.
OBJETIVO: O presente estudo realizou uma análise de sobrevivência segundo situação de cadastro na Atenção Primária à Saúde (APS) e de fatores associados ao óbito por COVID-19, nos casos residentes da Área Programática 3.1 (AP3.1) com diagnóstico de diabetes (na ficha de notificação ou no prontuário eletrônico) do município do Rio de Janeiro, em 20202021. MÉTODOS: Foi realizado relacionamento probabilístico de bases de dados com base nas informações dos casos notificados por COVID-19 e dos dados de prontuário eletrônico de pessoas que vivem com diabetes. Conduziu-se uma análise de sobrevivência, utilizando-se o modelo de regressão de Cox estratificado por faixa etária e ajustando-se por variáveis confundidoras. RESULTADOS: Verificou-se que indivíduos cadastrados na APS da AP3.1 possuíam risco quase duas vezes maior de óbito por COVID-19 (hazard ratio ajustada HRaj=1,91) quando comparados aos não cadastrados na APS da AP3.1. Essa associação foi mais forte naqueles com 18 a 59 anos, cadastrados na APS (HRaj=2,82), do que nos de 60 anos ou mais (HRaj=1,56). CONCLUSÃO: Estratégias de vigilância para a identificação e acompanhamento adequado de grupos de maior risco de mortalidade, dentre indivíduos que vivem com DM, no âmbito da APS podem contribuir para a redução da mortalidade em decorrência da COVID-19.
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COVID-19 , Diabetes Mellitus , Humanos , Brasil/epidemiología , Bases de Datos Factuales , Atención Primaria de SaludRESUMEN
This was a household-based prospective cohort study conducted in Rio de Janeiro, in which people with laboratory-confirmed coronavirus disease 2019 (COVID-19) and their household contacts were followed from April 2020 through June 2022. Ninety-eight reinfections were identified, with 71 (72.5%) confirmed by genomic analyses and lineage definition in both infections. During the pre-Omicron period, 1 dose of any COVID-19 vaccine was associated with a reduced risk of reinfection, but during the Omicron period not even booster vaccines had this effect. Most reinfections were asymptomatic or milder in comparison with primary infections, a justification for continuing active surveillance to detect infections in vaccinated individuals. Our findings demonstrated that vaccination may not prevent infection or reinfection with severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). Therefore we highlight the need to continuously update the antigenic target of SARS CoV-2 vaccines and administer booster doses to the population regularly, a strategy well established in the development of vaccines for influenza immunization programs.
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COVID-19 , SARS-CoV-2 , Humanos , COVID-19/epidemiología , COVID-19/prevención & control , Estudios Prospectivos , Reinfección/epidemiología , Vacunas contra la COVID-19 , Brasil/epidemiologíaRESUMEN
Background: Brazil started the COVID-19 mass vaccination in January 2021 with CoronaVac and ChAdOx1, followed by BNT162b2 and Ad26.COV2.S vaccines. By the end of 2021, more than 317 million vaccine doses were administered in the adult population. This study aimed at estimating the effectiveness of the primary series of COVID-19 vaccination and booster shots in protecting against severe cases and deaths in Brazil during the first year of vaccination. Methods: A cohort dataset of over 158 million vaccination and severe cases records linked from official national registries was analyzed via a mixed-effects Poisson model, adjusted for age, state of residence, time after immunization, and calendar time to estimate the absolute vaccine effectiveness of the primary series of vaccination and the relative effectiveness of the booster. The method permitted analysis of effectiveness against hospitalizations and deaths, including in the periods of variant dominance. Findings: Vaccine effectiveness against severe cases and deaths remained over 25% and 50%, respectively, after 19 weeks from primary vaccination of BNT162b2, ChAdOx1, or CoronaVac vaccines. The boosters conferred greater protection than the primary series of vaccination, with heterologous boosters providing marginally greater protection than homologous. The effectiveness against hospitalization during the Omicron dominance in the 60+ years old population started at 61.7% (95% CI, 26.1-86.2) for ChAdOx1, 95.6% (95% CI, 82.4-99.9) for CoronaVac, and 72.3% (95% CI, 51.4-87.4) for the BNT162b2 vaccine. Interpretation: This study provides real-world evidence of the effectiveness of COVID-19 vaccination in Brazil, including during the Omicron wave, demonstrating protection even after waning effectiveness. Comparisons of the effectiveness among different vaccines require caution due to potential bias effects related to age groups, periods in the pandemic, and eventual behavioural changes. Funding: Fundação Oswaldo Cruz (FIOCRUZ), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), Pan American Health Organization (PAHO), Departamento de Ciência e Tecnologia da Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos em Saúde do Ministério da Saúde do Brasil (DECIT/SCTIE/MS).
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Background: Vaccines developed between 2020 and 2021 against the SARS-CoV-2 virus were designed to diminish the severity and prevent deaths due to COVID-19. However, estimates of the effectiveness of vaccination campaigns in achieving these goals remain a methodological challenge. In this work, we developed a Bayesian statistical model to estimate the number of deaths and hospitalisations averted by vaccination of older adults (above 60 years old) in Brazil. Methods: We fit a linear model to predict the number of deaths and hospitalisations of older adults as a function of vaccination coverage in this group and casualties in younger adults. We used this model in a counterfactual analysis, simulating alternative scenarios without vaccination or with faster vaccination roll-out. We estimated the direct effects of COVID-19 vaccination by computing the difference between hypothetical and realised scenarios. Findings: We estimated that more than 165,000 individuals above 60 years of age were not hospitalised due to COVID-19 in the first seven months of the vaccination campaign. An additional contingent of 104,000 hospitalisations could have been averted if vaccination had started earlier. We also estimated that more than 58 thousand lives were saved by vaccinations in the period analysed for the same age group and that an additional 47 thousand lives could have been saved had the Brazilian government started the vaccination programme earlier. Interpretation: Our estimates provided a lower bound for vaccination impacts in Brazil, demonstrating the importance of preventing the suffering and loss of older Brazilian adults. Once vaccines were approved, an early vaccination roll-out could have saved many more lives, especially when facing a pandemic. Funding: The Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brazil (Finance Code 001 to F.M.D.M. and L.S.F.), Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brazil (grant number: 315854/2020-0 to M.E.B., 141698/2018-7 to R.L.P.d.S., 313055/2020-3 to P.I.P., 311832/2017-2 to R.A.K.), Fundação de Amparo à Pesquisa do Estado de São Paulo - Brazil (contract number: 2016/01343-7 to R.A.K.), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro - Brazil (grant number: E-26/201.277/2021 to L.S.B.) and Inova Fiocruz/Fundação Oswaldo Cruz - Brazil (grant number: 48401485034116) to L.S.B., O.G.C. and M.G.d.F.C. The funding agencies had no role in the conceptualization of the study.
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RESUMO Objetivo: O presente estudo realizou uma análise de sobrevivência segundo situação de cadastro na Atenção Primária à Saúde (APS) e de fatores associados ao óbito por COVID-19, nos casos residentes da Área Programática 3.1 (AP3.1) com diagnóstico de diabetes (na ficha de notificação ou no prontuário eletrônico) do município do Rio de Janeiro, em 2020-2021. Métodos: Foi realizado relacionamento probabilístico de bases de dados com base nas informações dos casos notificados por COVID-19 e dos dados de prontuário eletrônico de pessoas que vivem com diabetes. Conduziu-se uma análise de sobrevivência, utilizando-se o modelo de regressão de Cox estratificado por faixa etária e ajustando-se por variáveis confundidoras. Resultados: Verificou-se que indivíduos cadastrados na APS da AP3.1 possuíam risco quase duas vezes maior de óbito por COVID-19 (hazard ratio ajustada — HRaj=1,91) quando comparados aos não cadastrados na APS da AP3.1. Essa associação foi mais forte naqueles com 18 a 59 anos, cadastrados na APS (HRaj=2,82), do que nos de 60 anos ou mais (HRaj=1,56). Conclusão: Estratégias de vigilância para a identificação e acompanhamento adequado de grupos de maior risco de mortalidade, dentre indivíduos que vivem com DM, no âmbito da APS podem contribuir para a redução da mortalidade em decorrência da COVID-19.
ABSTRACT Objective: The present study carried out an analysis of survival according to the status of registration with Primary Health Care (PHC) and of factors associated with death from COVID-19, in cases residing in Programmatic Area 3.1 (PA3.1) with a diagnosis of diabetes (in the notification form or in the electronic medical record), of the Municipality of Rio de Janeiro (RJ), Brazil, in 2020-2021. Methods: A probabilistic linkage of databases was performed based on information on cases notified as COVID-19 and data from the electronic medical records of people living with diabetes. A survival analysis was carried out, using the Cox regression model stratified by age group and adjusted for confounding variables. Results: Individuals registered with the PHC of PA3.1 had almost twice the risk of death from COVID-19 (adjusted hazard ratio [HRadj]=1.91) when compared to those unregistered. This association was stronger in individuals aged 18 to 59 years registered with the PHC (HRadj=2.82) than in individuals aged 60 years or over (HRadj=1.56). Conclusion: Surveillance strategies for identifying and adequately monitoring higher-risk groups, among individuals living with diabetes, within the scope of Primary Health Care, can contribute to reducing mortality from COVID-19.
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BACKGROUND: Evidence of multimorbidity has come mainly from high-income regions, while disparities among racial groups have been less explored. This study examined racial differences in multimorbidity in the multiracial cohort of the Longitudinal Study of Adult Health (Estudo Longitudinal de Saúde do Adulto), ELSA-Brasil. METHODS: The study examined baseline (2008-2010) data for 14 099 ELSA-Brasil participants who self-reported being white, mixed-race, or black. A list of 16 morbidities was used to evaluate multimorbidity, operationalised by simple count into ≥ 2, ≥ 3, ≥ 4, ≥ 5 and ≥ 6 morbidities, in addition to evaluating the number of coexisting conditions. Prevalence ratios (PR) were estimated from logistic models and a quantile model was used to examine racial differences graphically in the distribution quantiles for the number of morbidities. RESULTS: Overall prevalence of multimorbidity (≥ 2 morbidities) was 70% and, after controlling for age and sex, was greater among mixed-race and black participants - by 6% (PR: 1.06; 95% CI: 1.03-1.08) and 9% (PR: 1.09; 95% CI: 1.06-1.12), respectively - than among white participants. As the cutoff value for defining multimorbidity was raised, so the strength of the association increased, especially among blacks: if set at ≥ 6 morbidities, the prevalence was 27% greater for those of mixed-race (PR: 1.27; 95% CI: 1.07-1.50) and 47% greater for blacks (PR: 1.47; 95% CI: 1.22-1.76) than for whites. The disparities were smaller in the lower morbidity distribution quantiles and larger in the upper quantiles, indicating a heavier burden of disease, particularly on blacks. CONCLUSIONS: Multimorbidity was common among adults and older adults in a Brazilian cohort, but important racial inequalities were found. Raising the cutoff point for defining multimorbidity revealed stronger associations between race/skin colour and multimorbidity, indicating a higher prevalence of multimorbidity among mixed-race and black individuals than among whites and that the former groups coexisted more often with more complex health situations (with more coexisting morbidities). Interventions to prevent and manage the condition of multimorbidity that consider the social determinants of health and historically discriminated populations in low- and middle-income regions are necessary.
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Multimorbilidad , Grupos Raciales , Anciano , Brasil/epidemiología , Humanos , Estudios Longitudinales , PrevalenciaRESUMEN
Background: Incidence rates of SARS-CoV-2 infections in low-resource communities can inform vaccination strategies and non-pharmaceutical interventions (NPIs). Our objective was to estimate incidence over four epidemic waves in a slum in Rio de Janeiro, a proxy for economically deprived areas in the Global South. Methods: Prospective cohort of children and household contacts screened for SARS-CoV-2 by PCR and serology (IgG). The incidence density of PCR positive infections estimated for each wave - the first wave, Zeta, Gamma and Delta - was compared to an index combining NPIs and vaccination coverage. Findings: 718 families and 2501 individuals were enrolled, from May 2020 to November 2021. The incidence density of SARS-CoV-2 infection due to the first wave was 2, 3 times that of the other waves. The incidence among children was lower than that of older participants, except in later waves, when vaccination of the elderly reached 90%. Household agglomeration was significantly associated with incidence only during the first wave. Interpretation: The incidence of infection greatly exceeded rates reported in similar cohorts. The observed reduction in incidence in the elderly during the Delta variant wave, in spite of the rollback of NPIs, can be attributed to increased vaccine coverage. The high incidence in young people reinforces the importance of vaccination in this age group, a policy that has yet to receive the full support of some sectors of society. Funding: UK Medical Research Council, Foundation for the Advancement of Science of the State of Rio de Janeiro, National Council for Scientific and Technological Development.
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Chikungunya, a mosquito-borne disease, is a growing threat in Brazil, where over 640,000 cases have been reported since 2017. However, there are often long delays between diagnoses of chikungunya cases and their entry in the national monitoring system, leaving policymakers without the up-to-date case count statistics they need. In contrast, weekly data on Google searches for chikungunya is available with no delay. Here, we analyse whether Google search data can help improve rapid estimates of chikungunya case counts in Rio de Janeiro, Brazil. We build on a Bayesian approach suitable for data that is subject to long and varied delays, and find that including Google search data reduces both model error and uncertainty. These improvements are largest during epidemics, which are particularly important periods for policymakers. Including Google search data in chikungunya surveillance systems may therefore help policymakers respond to future epidemics more quickly.
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Fiebre Chikungunya , Virus Chikungunya , Animales , Teorema de Bayes , Brasil/epidemiología , Fiebre Chikungunya/epidemiología , Incidencia , Motor de BúsquedaRESUMEN
Epidemiological surveillance and notification of respiratory infections are important for management and control of epidemics and pandemics. Fact-based decisions, like social distancing policies and preparation of hospital beds, are taken based on several factors, including case numbers; hence, health authorities need quick access to reliable and well-analysed data. We aimed to analyse the role of the Brazilian public health system in the notification and hospitalization of patients with severe acute respiratory infection (SARI). Data of SARI cases in Brazil (2013-20) were obtained from SIVEP-Gripe platform, and legal status of each healthcare unit (HCU) responsible for case notification and hospitalization was obtained from the National Registry of Health Facilities (CNES) database. HCUs that are part of the hospital network were classified as 'Public Administration', 'Business Entities', 'Philanthropic Entities' or 'Individuals'. SARI notification data from Brazilian macro-regions (North, Northeast, Midwest, Southeast and South) were analysed and compared between administrative spheres. This study reveals that hospitalizations due to SARI increased significantly in Brazil during the coronavirus disease 2019 (COVID-19) pandemic, especially in HCUs of Public Administration. In the Southeast and South, where incidence of SARI is high, philanthropic HCUs also contribute to hospitalization of SARI cases and attend up to 7.4% of the cases notified by the Public Administration. The number of cases is usually lower in other regions, but in 2020 the Northeast showed more hospitalizations than the South. In the South, SARI season occurs later; however, in 2020, an early peak was observed because of COVID-19. Notably, the contribution of each administrative sphere that manages hospital networks in Brazil in the control and management of SARI varies between regions. Our approach will allow managers to assess the use of public resources, given that there are different profiles of healthcare in each region of Brazil and that the public health system has a major role in notifying and attending SARI cases.
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COVID-19 , Obtención de Fondos , Gripe Humana , Infecciones del Sistema Respiratorio , Brasil/epidemiología , COVID-19/epidemiología , Atención a la Salud , Instituciones de Salud , Hospitalización , Humanos , Gripe Humana/epidemiología , Pandemias , Infecciones del Sistema Respiratorio/epidemiologíaRESUMEN
The study aimed to analyze the socio-spatial differences in COVID-19 mortality in the pandemic's three waves in the city of Buenos Aires, Argentina. COVID-19 mortality data were obtained from the COVID-19 Database and reported by the Buenos Aires Autonomous Government from March 7, 2020, to September 30, 2021. Three waves were identified: the first from March to December 2020, the second from December 2020 to March 2021, and the third from March to September 2021. Multivariate regressions were calculated for each wave to analyze the association between risk of COVID-19 mortality in two age groups (0-59 years and 60 years or older) and the percentage of households with unmet basic needs as indicator of neighborhood poverty level, and population density. During the first wave and in both age groups, the neighborhood in the tertile with the highest percentages of households with unmet basic needs showed higher risk of COVID-19 mortality when compared to neighborhoods in the tertile with the lowest percentages of households with unmet basic needs. These inequalities disappeared in the second wave in both age groups, while the third wave saw a similar geographic pattern to the first wave. Higher levels of immunity in neighborhoods with high poverty levels might partially explain the absence of socio-spatial inequalities in the second wave, while the emergence of the gamma and lambda variants could partially explain the return to inequalities observed in the first wave.
Nuestro propósito fue investigar las diferencias de las desigualdades socioespaciales de la mortalidad por COVID-19 entre tres olas de propagación del virus en la Ciudad Autónoma de Buenos Aires (CABA), Argentina. Los datos de mortalidad por COVID-19 se obtuvieron de la base de datos de casos de COVID-19, informados por el gobierno de la CABA, desde el 7 de marzo de 2020 hasta el 30 de septiembre de 2021. Se determinaron tres olas: la primera ola, entre los meses de marzo y diciembre de 2020, la segunda ola, entre diciembre y marzo de 2021, y la tercera ola, entre marzo y septiembre de 2021. En cada ola se calcularon regresiones multivariadas para analizar la asociación entre el riesgo de mortalidad por COVID-19, en dos grupos etarios (0-59 años y 60 o más años), y el porcentaje de hogares con necesidades básicas insatisfechas, como indicador del nivel de pobreza de los barrios, y la densidad poblacional. Durante la primera ola y en ambos grupos etarios, los barrios del tercil con mayores porcentajes de hogares con necesidades básicas insatisfechas tuvieron un riesgo mayor de mortalidad por COVID-19, en comparación a los barrios del tercil con menores porcentajes de hogares con necesidades básicas insatisfechas. Estas desigualdades desaparecieron durante la segunda ola en ambos grupos etarios, mientras que en la tercera ola pareció emerger un patrón geográfico similar al de la primera ola. Es posible que mayores niveles de inmunidad en barrios con niveles altos de pobreza pudieran explicar parcialmente la ausencia de desigualdades socioespaciales durante la segunda ola, mientras que la irrupción de las variantes gamma y lambda podría explicar parcialmente el retorno a las desigualdades observadas en la primera ola.
A proposta era investigar as diferenças nas desigualdades socioespaciais da mortalidade por COVID-19 entre três ondas de propagação do vírus na Cidade Autônoma de Buenos Aires, Argentina. Os dados de mortalidade por COVID-19 foram obtidos a partir da base de dados dos casos de COVID-19 informados pelo governo da Cidade Autônoma de Buenos Aires, do dia 7 de março de 2020, até 30 de setembro de 2021. Foram identificadas três ondas: a primeira, entre os meses de março e dezembro de 2020, a segunda, entre dezembro e março de 2021, e a terceira, entre março e setembro de 2021. Para cada uma delas, foram calculadas regressões multivariadas, visando analisar a associação entre o risco de mortalidade por COVID-19 em dois grupos etários (0-59 anos e 60 anos ou mais), e o percentual de domicílios com necessidades básicas não atendidas, como indicador do nível de pobreza dos bairros, e a densidade populacional. Durante a primeira onda e em ambos grupos etários, os bairros do tercil com maiores percentuais de domicílios com necessidades básicas não atendidas apresentaram um risco maior de mortalidade por COVID-19 na comparação com os bairros do tercil com menores taxas de domicílios com necessidades básicas não atendidas. Estas desigualdades desapareceram durante a segunda onda nos dois grupos etários, ao passo que, na terceira onda parece ter emergido um padrão geográfico similar ao da primeira onda. Maiores níveis de imunidade em bairros com altas taxas de pobreza poderiam explicar parcialmente a ausência de desigualdades socioespaciais durante a segunda onda, sendo que a irrupção das variantes gama e lambda poderia explicar parcialmente a volta para as desigualdades observadas na primeira onda.
Asunto(s)
COVID-19 , Adolescente , Adulto , Argentina/epidemiología , Brasil , Niño , Preescolar , Humanos , Lactante , Recién Nacido , Persona de Mediana Edad , SARS-CoV-2 , Adulto JovenRESUMEN
We conducted a systematic review and meta-analysis of studies assessing HCV infection rates in haemodialysis patients in Brazil (Prospero CRD #42021275068). We included studies on patients under haemodialysis, comprising both convenience samples and exhaustive information from selected services. Patients underwent HCV serological testing with or without confirmation by HCV RNA PCR. Exclusion criteria were the following: absence of primary empirical information and studies without information on their respective settings, study year, accurate infection rates, or full specification of diagnostic tests. Studies with samples ≤ 30 and serial assessments with repeated information were also excluded. Reference databases included PubMed, LILACS, Scopus, and Web of Science for the period 1989-2019. A systematic review was carried out, followed by two independent meta-analyses: (i) studies with data on HCV prevalence and (ii) studies with a confirmatory PCR (i.e., active infection), respectively. A comprehensive set of different methods and procedures were used: forest plots and respective statistics, polynomial regression, meta-regression, subgroup influence, quality assessment, and trim-and-fill analysis. 29 studies and 11,290 individuals were assessed. The average time patients were in haemodialysis varied from 23.5 to 56.3 months. Prevalence of HCV infection was highly heterogeneous, with a pronounced decrease from 1992 to 2001, followed by a plateau and a slight decrease in recent years. The summary measure for HCV prevalence was 34% (95% CI 26-43%) for studies implemented before 2001. For studies implemented after 2001, the corresponding summary measure was 11% (95% CI 8-15%). Estimates for prevalence of active HCV infection were also highly heterogeneous. There was a marked decline from 1996 to 2001, followed by a plateau and a slight increase after 2010. The summary measure for active HCV infection was 19% (95% CI 15-25%) in studies carried out before 2001. For studies implemented after 2001, the corresponding summary measure was 9% (95% CI 6-13%). Heterogeneity was pervasive, but different analyses helped to identify its underlying sources. Besides the year each study was conducted, the findings differed markedly between geographic regions and were heavily influenced by the size of the studies and publication biases. Our systematic review and meta-analysis documented a substantial decline in HCV prevalence among Brazilian haemodialysis patients from 1992 to 2015. CKD should be targeted with specific interventions to prevent HCV infection, and if prevention fails, prompt diagnosis and treatment. Although the goal of HCV elimination by 2030 in Brazil remains elusive, it is necessary to adopt measures to achieve micro-elimination and to launch initiatives towards targeted interventions to curb the spread of HCV in people with CKD, among other high-risk groups. This is of particular concern in the context of a protracted COVID-19 pandemic and a major economic and political crisis.
Asunto(s)
COVID-19/diagnóstico , Hepacivirus/genética , Hepatitis C/diagnóstico , Diálisis Renal/estadística & datos numéricos , SARS-CoV-2/genética , Brasil/epidemiología , COVID-19/epidemiología , COVID-19/virología , Hepacivirus/fisiología , Hepatitis C/epidemiología , Hepatitis C/virología , Humanos , Técnicas de Amplificación de Ácido Nucleico/métodos , Pandemias , Prevalencia , ARN Viral/genética , Diálisis Renal/métodos , SARS-CoV-2/fisiologíaRESUMEN
Nuestro propósito fue investigar las diferencias de las desigualdades socioespaciales de la mortalidad por COVID-19 entre tres olas de propagación del virus en la Ciudad Autónoma de Buenos Aires (CABA), Argentina. Los datos de mortalidad por COVID-19 se obtuvieron de la base de datos de casos de COVID-19, informados por el gobierno de la CABA, desde el 7 de marzo de 2020 hasta el 30 de septiembre de 2021. Se determinaron tres olas: la primera ola, entre los meses de marzo y diciembre de 2020, la segunda ola, entre diciembre y marzo de 2021, y la tercera ola, entre marzo y septiembre de 2021. En cada ola se calcularon regresiones multivariadas para analizar la asociación entre el riesgo de mortalidad por COVID-19, en dos grupos etarios (0-59 años y 60 o más años), y el porcentaje de hogares con necesidades básicas insatisfechas, como indicador del nivel de pobreza de los barrios, y la densidad poblacional. Durante la primera ola y en ambos grupos etarios, los barrios del tercil con mayores porcentajes de hogares con necesidades básicas insatisfechas tuvieron un riesgo mayor de mortalidad por COVID-19, en comparación a los barrios del tercil con menores porcentajes de hogares con necesidades básicas insatisfechas. Estas desigualdades desaparecieron durante la segunda ola en ambos grupos etarios, mientras que en la tercera ola pareció emerger un patrón geográfico similar al de la primera ola. Es posible que mayores niveles de inmunidad en barrios con niveles altos de pobreza pudieran explicar parcialmente la ausencia de desigualdades socioespaciales durante la segunda ola, mientras que la irrupción de las variantes gamma y lambda podría explicar parcialmente el retorno a las desigualdades observadas en la primera ola.
The study aimed to analyze the socio-spatial differences in COVID-19 mortality in the pandemic's three waves in the city of Buenos Aires, Argentina. COVID-19 mortality data were obtained from the COVID-19 Database and reported by the Buenos Aires Autonomous Government from March 7, 2020, to September 30, 2021. Three waves were identified: the first from March to December 2020, the second from December 2020 to March 2021, and the third from March to September 2021. Multivariate regressions were calculated for each wave to analyze the association between risk of COVID-19 mortality in two age groups (0-59 years and 60 years or older) and the percentage of households with unmet basic needs as indicator of neighborhood poverty level, and population density. During the first wave and in both age groups, the neighborhood in the tertile with the highest percentages of households with unmet basic needs showed higher risk of COVID-19 mortality when compared to neighborhoods in the tertile with the lowest percentages of households with unmet basic needs. These inequalities disappeared in the second wave in both age groups, while the third wave saw a similar geographic pattern to the first wave. Higher levels of immunity in neighborhoods with high poverty levels might partially explain the absence of socio-spatial inequalities in the second wave, while the emergence of the gamma and lambda variants could partially explain the return to inequalities observed in the first wave.
A proposta era investigar as diferenças nas desigualdades socioespaciais da mortalidade por COVID-19 entre três ondas de propagação do vírus na Cidade Autônoma de Buenos Aires, Argentina. Os dados de mortalidade por COVID-19 foram obtidos a partir da base de dados dos casos de COVID-19 informados pelo governo da Cidade Autônoma de Buenos Aires, do dia 7 de março de 2020, até 30 de setembro de 2021. Foram identificadas três ondas: a primeira, entre os meses de março e dezembro de 2020, a segunda, entre dezembro e março de 2021, e a terceira, entre março e setembro de 2021. Para cada uma delas, foram calculadas regressões multivariadas, visando analisar a associação entre o risco de mortalidade por COVID-19 em dois grupos etários (0-59 anos e 60 anos ou mais), e o percentual de domicílios com necessidades básicas não atendidas, como indicador do nível de pobreza dos bairros, e a densidade populacional. Durante a primeira onda e em ambos grupos etários, os bairros do tercil com maiores percentuais de domicílios com necessidades básicas não atendidas apresentaram um risco maior de mortalidade por COVID-19 na comparação com os bairros do tercil com menores taxas de domicílios com necessidades básicas não atendidas. Estas desigualdades desapareceram durante a segunda onda nos dois grupos etários, ao passo que, na terceira onda parece ter emergido um padrão geográfico similar ao da primeira onda. Maiores níveis de imunidade em bairros com altas taxas de pobreza poderiam explicar parcialmente a ausência de desigualdades socioespaciais durante a segunda onda, sendo que a irrupção das variantes gama e lambda poderia explicar parcialmente a volta para as desigualdades observadas na primeira onda.
Asunto(s)
Humanos , Recién Nacido , Lactante , Preescolar , Niño , Adolescente , Adulto , Persona de Mediana Edad , Adulto Joven , COVID-19 , Argentina/epidemiología , Brasil , SARS-CoV-2RESUMEN
In a context of community transmission and shortage of vaccines, COVID-19 vaccination should focus on directly reducing the morbidity and mortality caused by the disease. It was thus essential to define priority groups for vaccination by the Brazilian National Immunization Program (PNI in Portuguese), based on the risk of hospitalization and death from the disease. We calculated overrisk according to sex, age group, and comorbidities using hospitalization and death records from severe acute respiratory illness with confirmation of COVID-19 (SARI-COVID) in all of Brazil in the first 6 months of the epidemic. Higher overrisk was associated with male sex (hospitalization = 1.1 and death = 1.2), age over 45 years for hospitalization (OvRag ranging from 1.1 to 8.5), and age over 55 year for death (OvRag ranging from 1.5 to 18.3). In the groups with comorbidities, chronic kidney disease, diabetes mellitus, cardiovascular disease, and chronic lung disease were associated with overrisk, while there was no such evidence for asthma. Chronic kidney disease or diabetes and age over 60 showed an even stronger association, reaching overrisk of death 14 and 10 times greater than in the general population, respectively. For all the comorbidities, there was higher overrisk at older ages, with a downward gradient in the oldest age groups. This pattern was reversed when examining overrisk in the general population, for both hospitalization and death. The current study provided evidence of overrisk of hospitalization and death from SARI-COVID, assisting the definition of priority groups for COVID-19 vaccination.
Em um contexto de transmissão comunitária e escassez de vacinas, a vacinação contra a COVID-19 deve focar na redução direta da morbidade e da mortalidade causadas pela doença. Portanto, é fundamental a definição de grupos prioritários para a vacinação pelo Programa Nacional de Imunizações (PNI), baseada no risco de hospitalização e óbito pela doença. Para tal, calculamos o sobrerrisco por sexo, faixa etária e comorbidades por meio dos registros de hospitalização e óbito por síndrome respiratória aguda grave com confirmação de COVID-19 (SRAG-COVID) em todo o Brasil nos primeiros seis meses de epidemia. Apresentaram maior sobrerrisco pessoas do sexo masculino (hospitalização = 1,1 e óbito = 1,2), pessoas acima de 45 anos para hospitalização (SRfe variando de 1,1 a 8,5) e pessoas acima de 55 anos para óbitos (SRfe variando de 1,5 a 18,3). Nos grupos de comorbidades, doença renal crônica, diabetes mellitus, doença cardiovascular e pneumopatia crônica conferiram sobrerrisco, enquanto para asma não houve evidência. Ter doença renal crônica ou diabetes mellitus e 60 anos ou mais mostrou-se um fator ainda mais forte, alcançando sobrerrisco de óbito 14 e 10 vezes maior do que na população geral, respectivamente. Para todas as comorbidades, houve um sobrerrisco mais alto em idades maiores, com um gradiente de diminuição em faixas mais altas. Esse padrão se inverteu quando consideramos o sobrerrisco em relação à população geral, tanto para hospitalização quanto para óbito. O presente estudo forneceu evidências a respeito do sobrerrisco de hospitalização e óbito por SRAG-COVID, auxiliando na definição de grupos prioritários para a vacinação contra a COVID-19.
En un contexto de transmisión comunitaria y escasez de vacunas, la vacunación contra la COVID-19 debe enfocarse en la reducción directa de la morbilidad y de la mortalidad causadas por la enfermedad. Por lo tanto, es fundamental la definición de grupos prioritarios para la vacunación por el Programa Nacional de Inmunizaciones (PNI), basada en el riesgo de hospitalización y óbito por la enfermedad. Para tal fin, calculamos el sobrerriesgo por sexo, franja de edad y comorbilidades mediante los registros de hospitalización y óbito por síndrome respiratorio agudo grave con confirmación de COVID-19 (SRAG-COVID) en todo Brasil, durante los primeros seis meses de epidemia. Presentaron mayor sobrerriesgo personas del sexo masculino (hospitalización = 1,1 y óbito = 1,2), personas por encima de 45 años para hospitalización (SRfe variando de 1,1 a 8,5) y personas por encima de 55 años para óbitos (SRfe variando de 1,5 a 18,3). En los grupos de comorbilidades, enfermedad renal crónica, diabetes mellitus, enfermedad cardiovascular y neumopatía crónica ofrecieron sobrerriesgo, mientras que para el asma no hubo evidencia. Sufrir una enfermedad renal crónica o diabetes mellitus y tener 60 años o más mostró un factor todavía más fuerte, alcanzando sobrerriesgo de enfermedad 14 y 10 veces mayor que en la población general, respectivamente. Para todas las comorbilidades, hubo un sobrerriesgo más alto en edades mayores, con un gradiente de disminución en franjas más altas. Este patrón se invirtió cuando consideramos el sobrerriesgo en relación con la población general, tanto para hospitalización como para óbito. El presente estudio proporcionó evidencias respecto al sobrerriesgo de hospitalización y óbito por SRAG-COVID, ayudando en la definición de grupos prioritarios para la vacunación contra la COVID-19.