Abstract

Introduction

The first case of COVID-19 in Brazil was confirmed on February 26, 2020, in the State of São Paulo. Social distancing measures were only implemented in the state nearly a month later ¹1. Secretaria de Vigilância em Saúde, Ministério da Saúde. Boletim Epidemiológico Especial - COE-COVID-19 2020; (14). https://portalarquivos.saude.gov.br/images/pdf/2020/April/27/2020-04-27-18-05h-BEE14-Boletim-do-COE.pdf.
https://portalarquivos.saude.gov.br/imag... , contributing to the rapid spread of the disease in the state and in Brazil. Shortly more than a month after confirmation of the first case, all 26 states and the Federal District already had ten or more cases each, with the heaviest concentration in the Southeast region (62.5%), followed by the Northeast (15.4%), South (10.8%), Central (6.6%), and North (4.7%) ²2. Secretaria de Vigilância em Saúde; Ministério da Saúde. Boletim Epidemiológico Especial - COE-COVID-19 2020; (6). https://portalarquivos.saude.gov.br/images/pdf/2020/April/03/BE6-Boletim-Especial-do-COE.pdf.
https://portalarquivos.saude.gov.br/imag... .

Brazil’s reality is heterogeneous, both in the epidemic’s evolution and in access to healthcare ³3. Viacava F, Bellido JG. Condições de saúde, acesso a serviços e fontes de pagamento, segundo inquéritos domiciliares. Ciênc Saúde Colet 2016; 21:351-70., since the country has continental dimensions, with different population distribution patterns, transportation conditions (roadways, availability, and costs), income inequalities, and education ⁴4. Xavier DR, Oliveira RAD, Barcellos C, Saldanha RF, Ramalho WM, Laguardia J, et al. As Regiões de Saúde no Brasil segundo internações: método para apoio na regionalização de saúde. Cad Saúde Pública 2019; 35 Suppl 2:e00076118.. By the month of May, the states of Rio de Janeiro, Amazonas, Ceará, Pará, and Pernambuco were already facing critical situations, especially in the respective state capitals and metropolitan areas, overloading the health system ⁵5. Por coronavírus, ocupação dos leitos de UTI supera 70% em ao menos seis estados. Estadão 2020; 1 mai. https://saude.estadao.com.br/noticias/geral,por-coronavirus-ocupacao-dos-leitos-de-uti-supera-70-em-ao-menos-seis-estados,70003289185 (acessado em 25/Mai/2020).
https://saude.estadao.com.br/noticias/ge... ^,66. Pitombo JP, Pasquini P, Valadares J, Barbon J, Albuquerque AL, Maisonnave F, et al. Estados abrem 1.400 leitos de UTI para Covid-19, mas ocupação segue alta. Folha de S. Paulo 2020; 12 mai. https://www1.folha.uol.com.br/equilibrioesaude/2020/05/estados-abrem-1400-leitos-de-uti-para-covid-19-mas-ocupacao-segue-alta.shtml (acessado em 25/Mai/2020).
https://www1.folha.uol.com.br/equilibrio... , while in other states the disease was spreading more slowly. The disease has gradually spread from the state capitals into the interior, a phenomenon that could impact the country’s health system even more heavily, since many municipalities (counties) lack even a single hospital, and the population is forced to seek health treatment in the regional hub cities ⁷7. Grupo de Métodos Analíticos em Vigilância Epidemiológica. Estimativa de risco de espalhamento da COVID-19 nos estados brasileiros e avaliação da vulnerabilidade socioeconômica nos municípios. https://bit.ly/mave-covi19-relatorio3-atual (acessado em 17/Abr/2020).
https://bit.ly/mave-covi19-relatorio3-at... ^,88. MonitoraCovid-19. Regiões e redes Covid-19: acesso aos serviços de saúde e fluxo de deslocamento de pacientes em busca de internação. https://bigdata-covid19.icict.fiocruz.br/nota_tecnica_7.pdf (acesasado em 20/Mai/2020).
https://bigdata-covid19.icict.fiocruz.br... (Ministério da Saúde. Painel coronavírus. https://covid.saude.gov.br, accessed on May/2020).

Despite the increasing number of municipalities with cases and the growing number of hospitalizations and deaths from COVID-19 in Brazil (Ministério da Saúde. Painel coronavírus. https://covid.saude.gov.br, accessed on May/2020) there is still limited information for characterizing the hospitalized cases in Brazil (as elsewhere in the world). Studies in China, Italy, and the United States have analyzed the profile of patients hospitalized for COVID-19 and found high prevalence of elderly individuals, males, and preexisting comorbidities such as hypertension and diabetes ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62.^,1010. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81.^,1111. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59..

In order to monitor hospitalized COVID-19 cases in Brazil, the Ministry of Health incorporated testing for SARS-CoV-2 (the virus that causes COVID-19) into surveillance of the severe acute respiratory illness (SARI). Case notification is compulsory, and the records are stored in the SIVEP-Gripe (Influenza Epidemiological Surveillance Information System) database ¹²12. Secretaria de Vigilância em Saúde, Ministério da Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019. https://portalarquivos.saude.gov.br/images/pdf/2020/April/07/GuiaDeVigiEpidemC19-v2.pdf (acessado em 30/Abr/2020).
https://portalarquivos.saude.gov.br/imag... ^,1313. Ministério da Saúde. Definição de caso e notificação. https://coronavirus.saude.gov.br/definicao-de-caso-e-notificacao (acessado em 21/Mai/2020).
https://coronavirus.saude.gov.br/definic... . The system was created during the influenza H1N1 pandemic in 2009 and has been maintained since then to monitor SARI cases and for the surveillance of unusual events associated with this syndrome in the country.

Among the cases of hospitalization for SARI reported to the national surveillance system from 2010 to 2019, the infectious agents according to the predominant laboratory test in each season were influenza A and B viruses and respiratory syncytial virus (RSV). In the years when hospitalizations for SARI were predominantly due to RSV, children from zero to two years were by far the most heavily affected group, while in years with influenza peaks, the other age groups showed large percentages of hospitalizations, although small children were also the most affected ¹⁴14. Bastos LS, Niquini RP, Lana RM, Villela DAM, Cruz OG, Coelho FC, et al. COVID-19 e hospitalizações por SRAG no Brasil: uma comparação até a 12 a semana epidemiológica de 2020. Cad Saúde Pública 2020; 36:e00070120.. According to a meta-analysis ¹⁵15. Mertz D, Kim TH, Johnstone J, Lam P-P, Science M, Kuster SP, et al. Populations at risk for severe or complicated influenza illness: systematic review and meta-analysis. BMJ 2013; 347:f5061., the highest risk of hospitalization for seasonal influenza was also among the elderly and individuals with comorbidities such as diabetes, chronic lung disease, and cardiovascular disease, which highlights the relevance and timeliness of comparing hospitalizations for SARI due to influenza and COVID-19.

In this context, the current study aims to describe patients hospitalized for SARI due to COVID-19 (SARI-COVID) in Brazil, according to their demographic characteristics and comorbidities up to the 21st Epidemiological Week (EW) of 2020. The study also aims to compare these characteristics to those of patients hospitalized for SARI from influenza in 2019/2020 (SARI-FLU), due to their relevance in SARI reporting, and to the Brazilian general population, in order to identify groups potentially at increased risk of hospitalization for the disease. The analysis is intended to help orient public policies and protocols for decision-making.

Method

Data

Data on hospitalizations for SARI

The SIVEP-Gripe database (https://sivepgripe.saude.gov.br/sivepgripe/login.html?0) was used to obtain data on the number of new hospitalizations in Brazil for SARI-COVID in 2020 and SARI-FLU in 2019 and 2020 (both up to the 21st EW, ending on May 23, 2020), by age bracket, race/color, sex, and major geographic region of Brazil, as well as comorbidities (diabetes, chronic kidney disease, asthma, other chronic lung diseases, and cardiovascular disease) and the proportion of pregnant and postpartum women.

SARI cases are defined as individuals that simultaneously meet four criteria: (i) fever, even if self-reported; (ii) cough or sore throat; (iii) dyspnea or O₂ saturation < 95% or respiratory discomfort; and (iv) hospitalization or evolution to death independently of previous hospitalization ¹⁶16. Secretaria de Vigilância em Saúde, Ministério da Saúde. Ficha de registro individual: casos de síndrome respiratória aguda grave hospitalizado. https://saude.rs.gov.br/upload/arquivos/carga20190433/05143355-25141516-1-ficha-srag-hospital.pdf (acessado em 07/Mai/2020).
https://saude.rs.gov.br/upload/arquivos/... . Once a hospitalized SARI case is identified, it is mandatory to report it, and it is recorded individually in the influenza surveillance information system (SIVEP-Gripe). In addition, a biological sample needs to be collected for laboratory analysis.

This analysis considered all the records in the SIVEP-Gripe database that met the criteria for definition of a hospitalized SARI case, ruling out the records of non-hospitalized deaths, with completion of the data field for the first symptoms and notification date corresponding to the years 2019 and 2020. Hospitalization for SARI-COVID is confirmed after a positive result on the RT-PCR molecular test for SARS-CoV-2. Analogously, hospitalization for SARI-FLU is confirmed after a positive result on a laboratory test for influenza A or B virus ¹1. Secretaria de Vigilância em Saúde, Ministério da Saúde. Boletim Epidemiológico Especial - COE-COVID-19 2020; (14). https://portalarquivos.saude.gov.br/images/pdf/2020/April/27/2020-04-27-18-05h-BEE14-Boletim-do-COE.pdf.
https://portalarquivos.saude.gov.br/imag... .

Data on the Brazilian general population

The projection of the Brazilian population by age bracket, sex, and region of residence for the year 2020 used in the study was performed by the Brazilian Institute of Geography and Statistics (IBGE. População residente: projeção da população do Brasil e Unidades da Federação por sexo e idade para o período 2000-2030. https://datasus.saude.gov.br/populacao-residente/, accessed on 26/May/2020), and the estimate for relative proportions of the population according to color or race was obtained from the Brazilian National Household Sample Survey (PNAD) of 2015 (IBGE. Pesquisa Nacional por Amostra de Domicílios - PNAD 2015. https://www.ibge.gov.br/estatisticas/sociais/populacao/9127-pesquisa-nacional-por-amostra-de-domicilios.html, accessed on 01/May/2020).

Prevalence rates for diabetes mellitus, chronic kidney disease (CKD), asthma (or asthmatic bronchitis), lung diseases such as emphysema, chronic bronchitis, or chronic obstructive pulmonary disease (COPD), and cardiovascular diseases (CVD) were obtained from the Brazilian National Health Survey (PNS) conducted in 2013 ¹⁷17. Malta DC, Stopa SR, Szwarcwald CL, Gomes NL, Silva Júnior JB, Reis AAC. A vigilância e o monitoramento das principais doenças crônicas não transmissíveis no Brasil - Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol 2015; 18:3-16.. CVD was defined in the PNS as arterial hypertension and/or heart diseases (myocardial infarction, angina, heart failure, or others). To compare the prevalence of CVD in the SIVEP-Gripe database, a composite variable was created as the sum of the prevalence rates for hypertension and heart diseases, with the confidence intervals constructed as the sum of the associated variances.

We estimated the relative proportion of pregnant or postpartum women in the general population as a ratio between the number of liveborn infants in the year 2018 in each age bracket, obtained from the Brazilian Information System on Live Births (SINASC), and the population size obtained from the population projections by age bracket for females in 2018, conducted by IBGE (População residente: projeção da população do Brasil e Unidades da Federação por sexo e idade para o período 2000-2030. https://datasus.saude.gov.br/populacao-residente/, accessed on 26/May/2020).

Data analysis

The relative proportions of demographic characteristics of patients hospitalized for SARI-COVID and SARI-FLU were calculated and compared to the proportions in the Brazilian general population using the chi-square test for homogeneity. Using these same tests, the relative proportions of patients hospitalized for SARI-COVID and SARI-FLU with comorbidities and of pregnant or postpartum women were compared to the proportions in the Brazilian general population, according to age bracket. The analyses were performed in the R software, version 3.6.3 (https://www.r-project.org/).

Results

Table 1 shows the distribution according to region of residence, sex, age bracket, and race or color of the Brazilian general population and of individuals hospitalized for SARI-COVID in 2020 and hospitalized for SARI-FLU in 2019 and 2020 up to the 21st EW of 2020. In 2019, 39,349 hospitalizations for SARI were reported, 14.7% of which (n = 5,780) for SARI-FLU. In 2020, until the 21st EW, 94,807 hospitalizations for SARI were reported, 33.7% of which (n = 31,968) for SARI-COVID, 1.5% (n = 1,463) for SARI-FLU, and 39 cases of co-infection excluded from the analysis. Nearly all of the characteristics of individuals hospitalized for SARI-COVID and SARI-FLU that were compared were significantly different from the Brazilian general population, except for those marked with an asterisk (*) in Table 1.

The Southeast region of Brazil, home to 41.8% of the country’s population, accounted for approximately 2/3 of the hospitalizations for SARI-COVID and 2/5 of the hospitalizations for SARI-FLU (Table 1).

The distribution by sex of individuals hospitalized for SARI-FLU shows a similar pattern to that of the Brazilian general population (49% males), which differs from individuals hospitalized for SARI-COVID, with a predominance of males (60%) (Table 1).

Distribution of the age brackets in individuals hospitalized for SARI-COVID and SARI-FLU differed considerably and also proved dissimilar to that of the Brazilian general population. Hospitalizations for SARI-FLU occurred predominantly in individuals from zero to four years of age (23.4%) and 60 years or older (22.5%), corresponding to 6.5% and 13.8% of the Brazilian population, respectively. Meanwhile, hospitalizations for SARI-COVID were concentrated in elderly individuals (45.2%) and the 40-59-year age bracket (37.7%) (Table 1). Median age of patients hospitalized for SARI-FLU was 33 years, with interquartile range (IQR) 5-57, while median age of patients hospitalized for SARI-COVID was 57 years (IQR: 44-70).

Individuals that self-identified as white predominated among patients hospitalized for SARI-COVID (47.5%) and for SARI-FLU (57.2%), The race/color profile in individuals hospitalized for SARI-COVID was more similar to that of the Brazilian general population, when compared to patients hospitalized for SARI-FLU (Table 1). Importantly, this information was missing for 34.5% of the individuals hospitalized for SARI-COVID, as compared to 17.7% of those hospitalized for SARI-FLU.

Table 2 shows the prevalence of comorbidities in the Brazilian general population according to the PNS of 2013, and among patients hospitalized for SARI-COVID in 2020 or SARI-FLU in 2019/2020, according to age bracket.

Both patients hospitalized for SARI-COVID and for SARI-FLU showed higher prevalence rates of diabetes and CKD when compared to the general population, in all the age brackets (Table 2).

In the three age brackets analyzed, prevalence of CVD in patients hospitalized for SARI-FLU was lower than in the general population, and when considering adults, the prevalence was similar to that of the general population. Meanwhile, among patients hospitalized for SARI-COVID, the prevalence of CVD for all adults (41%) was higher than in the general population, as well as in the age bracket from 18 to 39 years (Table 2).

Patients hospitalized for SARI-COVID showed similar prevalence rates for asthma compared to those of the general population from 18 to 39 years and from 40 to 59 years of age, while among patients hospitalized for SARI-FLU, asthma prevalence was higher than in the general population in these same age brackets. Prevalence rates for other chronic lung diseases were higher than in the general population, both for patients hospitalized for SARI-COVID and for SARI-FLU (Table 2).

Table 3 shows the relative proportion of pregnant or postpartum women hospitalized for SARI-COVID in 2020 and for SARI-FLU in 2019/2020 according to age bracket, compared to the relative proportion of women with liveborn children in 2018 in the Brazilian population.

Among female patients hospitalized for SARI-FLU and SARI-COVID, the proportion of pregnant or postpartum women was significantly higher than in the general population for all the age brackets (Table 3).

Discussion

The concentration of hospitalizations for SARI-COVID in the Southeast of Brazil reflects the fact that the disease first reached the country in the State of São Paulo, followed by Rio de Janeiro. Social distancing measures were not implemented evenly in the states of Brazil, Rio de Janeiro launched social distancing measures on March 13, while São Paulo only adopted them nearly a month after confirmation of the first case, which contributed to the rapid spread of the disease both in the state and in the country as a whole ¹1. Secretaria de Vigilância em Saúde, Ministério da Saúde. Boletim Epidemiológico Especial - COE-COVID-19 2020; (14). https://portalarquivos.saude.gov.br/images/pdf/2020/April/27/2020-04-27-18-05h-BEE14-Boletim-do-COE.pdf.
https://portalarquivos.saude.gov.br/imag... . Some three months after identification of the first case of COVID-19 in Brazil, 26% (62,345) of the cases and 30% (4,782) of the deaths from the disease were recorded in São Paulo. The other three states of the Southeast region accounted for 14% of the cases and 20% of the deaths ¹⁸18. Secretaria de Vigilância em Saúde, Ministério da Saúde. Boletim Epidemiológico Especial - COE-COVID-19 2020; (16). https://portalarquivos.saude.gov.br/images/pdf/2020/May/21/2020-05-19---BEE16---Boletim-do-COE-13h.pdf (acessado em 26/Mai/2020).
https://portalarquivos.saude.gov.br/imag... .

The higher percentage of residents in the South of Brazil among patients hospitalized for SARI-FLU (22%) when compared to residents of the South as a proportion of the total Brazilian population (14%) is consistent with the fact that the South is the only region of Brazil with a subtropical climate (as opposed to tropical), which favors the higher incidence of influenza there ¹⁹19. Almeida A, Codeço C, Luz PM. Seasonal dynamics of influenza in Brazil: the latitude effect. BMC Infect Dis 2018; 18:695..

The median age of patients hospitalized for SARI-COVID was similar to that of patients hospitalized in Wuhan, China (56, IQR: 46-67) ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62. and lower than that of patients hospitalized in New York in the United States (63, IQR: 52-75) ¹¹11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59. and in those admitted to intensive care units in Lombardy, Italy (63, IQR: 56-70) ¹⁰10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81.. The differences can be explained by the age profiles of the general population in the respective countries. The Brazilian and Chinese populations have lower proportions of individuals 60 years or older (14% and 17%, respectively), compared to the United States and Italy (23% and 30%, respectively) (United Nations. World population prospects 2019. Estimates: 1950-2020. https://population.un.org/wpp/Download/Standard/Population/, accessed on 19/May/2020).

The higher proportion of male patients among patients hospitalized for COVID-19 also appeared in the above-mentioned studies in China ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62. and the United States ¹¹11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59., with an even higher percentage in patients admitted to intensive care units in Lombardy (82%) ¹⁰10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81.. Since males account for approximately half of the population in these countries (United Nations. World population prospects 2019. Estimates: 1950-2020. https://population.un.org/wpp/Download/Standard/Population/, accessed on 19/May/2020) the current study’s findings and the available scientific literature point to male gender as associated with more serious evolution of the disease and death ²⁰20. Onder G, Rezza G, Brusaferro S. Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy. JAMA 2020; 323:1775-6..

There is no evidence in the international literature of any race or color at greater risk of hospitalization for seasonal influenza ¹⁵15. Mertz D, Kim TH, Johnstone J, Lam P-P, Science M, Kuster SP, et al. Populations at risk for severe or complicated influenza illness: systematic review and meta-analysis. BMJ 2013; 347:f5061.. Thus, the higher relative frequency of self-identified whites among Brazilians hospitalized for SARI-FLU may reflect the higher proportion of hospitalized patients among individuals in the South (which has a proportionally larger white population than the rest of Brazil).

The prevalence of comorbidities (diabetes, CVD, CKD, and chronic lung diseases) in patients hospitalized for SARI-COVID in Brazil was higher than the estimates in the general population, highlighting the hypothesis that this group has higher odds of hospitalization for the disease.

Prevalence of diabetes among patients hospitalized for SARI-COVID in Brazil (25%) was higher than in patients hospitalized in Wuhan (19%) ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62. and in Lombardy (17%) ¹⁰10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81., but lower than in New York (34%) ¹¹11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59.. The same was true for prevalence of CKD (4%, 1% ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62., 3% ¹⁰10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81., and 5% ¹¹11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59., respectively) and other chronic lung diseases (4%, 3% ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62., 4% ¹⁰10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81., and 5% ¹¹11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59., respectively).

Meanwhile, the prevalence of CVD in patients hospitalized for SARI-COVID in Brazil (41%) was higher than for hypertension (30%) plus coronary artery disease (8%) in Wuhan ⁹9. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu A, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395:1054-62., but lower than for hypertension in patients in Lombardy (49%) ¹⁰10. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA 2020; 323:1574-81. and New York (57%) ¹¹11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA 2020; 323:2052-59..

Differences in the profile of comorbidities are also observed in the general populations of Brazil and the United States. Prevalence of diabetes in the Brazilian adult population in 2013 (6.2%, 95%CI: 5.9-6.6) was lower than in the United States (10.2%, 95%CI: 9.3-11.2) in the years 2013-2016 ²¹21. Centers for Disease Control and Prevention. National Diabetes Statistics Report 2020: estimates of diabetes and its burden in the United States. https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf (acessado em 12/Mai/2020).
https://www.cdc.gov/diabetes/pdfs/data/s... , as was the prevalence of hypertension (21.4% vs. 41.7% in 2013-2014) ²²22. Centers for Disease Control and Prevention. Hypertension prevalence among adults aged 18 and over: United States, 2017-2018. https://www.cdc.gov/nchs/data/databriefs/db364-h.pdf (acessado em 12/Mai/2020).
https://www.cdc.gov/nchs/data/databriefs... , which is consistent with the differences observed in the profiles of patients hospitalized for COVID-19 in the two countries.

As for patients hospitalized for SARI-FLU, the current study’s findings are corroborated by a meta-analysis pointing to elderly age and diabetes and chronic lung disease as risk factors for hospitalization for seasonal influenza. Meanwhile, age under five years and asthma were identified as risk factors for the development of pneumonia ¹⁵15. Mertz D, Kim TH, Johnstone J, Lam P-P, Science M, Kuster SP, et al. Populations at risk for severe or complicated influenza illness: systematic review and meta-analysis. BMJ 2013; 347:f5061.. An important difference identified in the current study was the higher prevalence of asthma among individuals hospitalized for SARI-FLU, but not for SARI-COVID. This may be related to the pathophysiology of COVID-19, pointing to an exacerbated systemic immune response (but not necessarily local pulmonary factors) as an important factor for aggravation of the disease ²³23. José RJ, Manuel A. COVID-19 cytokine storm: the interplay between inflammation and coagulation. Lancet Respir Med 2020; 8:e46-7..

Despite the hypothesis raised in this study of more hospitalization of pregnant and postpartum women for SARI-COVID, the literature has not reported greater susceptibility to the infection or greater risk of serious evolution of the disease in pregnant women. Risk factors already detected in the general population, such as preexisting comorbidities and more advanced age, are factors for severity that have been identified thus far in this group. However, since the disease is still recent and incompletely understood, longitudinal studies are necessary to assess the effect of asymptomatic, mild, moderate, and severe infections on the occurrence of spontaneous abortion, intrauterine growth restriction, and congenital anomalies and the long-term health effects in the child ²⁴24. The UK Obstetric Surveillance System SARS-CoV-2 Infection in Pregnancy Collaborative Group. Characteristics and outcomes of pregnant women hospitalised with confirmed SARS-CoV-2 infection in the UK: a national cohort study using the UK Obstetric Surveillance System (UKOSS). https://www.npeu.ox.ac.uk/downloads/files/ukoss/annual-reports/UKOSS%20COVID-19%20Paper%20pre-print%20draft%2011-05-20.pdf (acessado em 29/Mai/2020).
https://www.npeu.ox.ac.uk/downloads/file... . In relation to influenza, evidence points to greater risk of hospitalization for influenza A(H1N1) among pregnant women and greater risk of death among postpartum women ¹⁵15. Mertz D, Kim TH, Johnstone J, Lam P-P, Science M, Kuster SP, et al. Populations at risk for severe or complicated influenza illness: systematic review and meta-analysis. BMJ 2013; 347:f5061., which corroborates this study’s finding.

Our study has some limitations. First, hospitalization is an event that is not based exclusively on the severity of the disease, since it also includes the health professional’s clinical assessment of the potential for aggravation of the case in the short term, which can be influenced by patient characteristics such as age, presence of comorbidities, or pregnancy. However, since the current study only included cases that met all the clinical criteria for SARI, we assume that this bias was minimized.

Since in most cases the laboratory test results are only obtained after the patient has already been hospitalized, we believe that the effect of this bias is occurring in the same way for cases of SARI-FLU and SARI-COVID in the year 2020.

As for the use of the total number of live births as the denominator for estimating the proportion of pregnant or postpartum women in the general population in 2018, a limitation was the fact that we did not discount the number of children born to multiple gestations, besides not including stillbirths (which are not tabulated in the SINASC database) or pregnant women who suffered fetal losses. However, considering that the women who had liveborn children in 2018 were pregnant up to 42 weeks in the year, with late postpartum up to the 6th week after delivery (the period in which the postpartum follow-up appointment is supposed to be scheduled) ²⁵25. Ministério da Saúde. Manual técnico: pré-natal e puerpério: atenção qualificada e humanizada. Brasília: Ministério da Saúde; 2005. (Série A. Normas e Manuais Técnicos) (Série Direitos Sexuais e Direitos Reprodutivos - Caderno nº 5)., we believe that by using the number of live births during a year, the prevalence of pregnant and postpartum women in the general population may be overestimated. Importantly, there are discrepancies in the literature concerning the duration of the postpartum period, which may lead to non-standardized completion of this variable in the SIVEP-Gripe database ²⁶26. Vieira CS, Brito MB, Yazlle MEHD. Contracepção no puerpério. Rev Bras Ginecol Obstet 2008; 30:470-9., in addition to possible problems of underreporting of this information.

The limitations of data obtained from the SIVEP-Gripe database include possible loss of false- negatives due to the sample collection period ²⁷27. Kucirka LM, Lauer SA, Laeyendecker O, Boon D, Lessler J. Variation in false-negative rate of reverse transcriptase polymerase chain reaction - based SARS-CoV-2 tests by time since exposure. Ann Intern Med 2020; M20-1495., delays in test results, and the possibility of hospitalizations for COVID-19 not being recorded in the system because they did not present obvious respiratory signs to record them as SARI cases. In relation to the first two limitations, although relevant in terms of potential underreporting and delay in case confirmation, respectively, it is reasonable to assume that they do not affect the current study’s analyses, since they potentially affect all the cases evenly. Meanwhile, hospitalizations for COVID-19 that do not enter the SIVEP-Gripe database because they do not present signs suggestive of SARI may be associated with distinct comorbidities.

Due to the COVID-19 epidemic, the national surveillance guidelines expanded the criterion for notification to also include cases without fever ¹²12. Secretaria de Vigilância em Saúde, Ministério da Saúde. Guia de vigilância epidemiológica: emergência de saúde pública de importância nacional pela doença pelo coronavírus 2019. https://portalarquivos.saude.gov.br/images/pdf/2020/April/07/GuiaDeVigiEpidemC19-v2.pdf (acessado em 30/Abr/2020).
https://portalarquivos.saude.gov.br/imag... ^,1313. Ministério da Saúde. Definição de caso e notificação. https://coronavirus.saude.gov.br/definicao-de-caso-e-notificacao (acessado em 21/Mai/2020).
https://coronavirus.saude.gov.br/definic... , defined as acute respiratory illness (ARI). However, in order to maintain comparability with SARI cases according to the international definition, the option in the current analysis was to maintain only the records that met all the symptomatic criteria.

Information on comorbidities in the SIVEP-Gripe database is reported by patients or family members, which can impact its accuracy. However, the data’s comparability is favored by the fact that information on comorbidity in the PNS is also self-reported.

The prevalence of cardiovascular disease in the PNS is overestimated because it includes acute events such as myocardial infarction. The associated uncertainty is also overestimated because it does not discount the covariance between hypertension and heart diseases. Since the analysis of individuals hospitalized for SARI only included chronic CVD, the possible classification bias between the groups is against what we demonstrated, since the prevalence rates should be overestimated in the comparison group (general population). Despite the above-mentioned limitations, it was possible to show higher prevalence of CVD among individuals hospitalized for SARI-COVID in the age bracket from 18 to 39 years and for all adults. However, among patients hospitalized for SARI-FLU, possibly due to the above-mentioned limitation, it was not possible to show the association between CVD and hospitalization for influenza (which has been reported elsewhere in the literature) ¹⁵15. Mertz D, Kim TH, Johnstone J, Lam P-P, Science M, Kuster SP, et al. Populations at risk for severe or complicated influenza illness: systematic review and meta-analysis. BMJ 2013; 347:f5061.. Thus, importantly, the difference between the prevalence rates of CVD in the general population and in hospitalizations for SARI must be greater in all the age groups analyzed.

Finally, another important limitation was the potential bias in the completion and recording of the case notification forms, a bias that is inherent to any study based on data from information systems without direct case-by-case follow-up in the hospital network. On the other hand, the use of data on hospitalizations for SARI-COVID obtained from the SIVEP-Gripe database allows an analysis of a larger population and is extremely relevant for monitoring the profile of severe cases of the disease in the country.

In short, the current study corroborates the literature on more advanced age, male gender, and comorbidities as factors associated with hospitalization for COVID-19, which can be considered a marker for severity of the disease.

Compared to the Brazilian general population, the high proportion of elderly patients and those 40 to 59 years of age and/or with comorbidities (diabetes, CVD, CKD, and chronic lung diseases) among patients hospitalized for SARI-COVID indicates that these patients may be presenting more serious cases of the disease. This hypothesis should be confirmed through longitudinal studies to support public health policies, for example, defining these risk groups as a priority for vaccination campaigns.

Acknowledgments

R. M. Lana receives a scholarship from PDJ Inova Fiocruz. D. A. M. Villela and A. G. Pacheco receive scholarships from Brazilian National Research Council (CNPq; Ref. 309569/2019-2 and 307489/2018-3). A. G. Pacheco received a Young Scientist of the State grant from Rio de Janeiro State Research Foundation (FAPERJ; E26/203.172/2017). The authors wish to acknowledge the National Influenza Surveillance Network (LACENs, NICs, state and municipal surveillance systems, Influenza Working Group, Department of Immunization and Transmissible Diseases of the Health Surveillance Secretariat, Ministry of Health) for their partnership, and Claudia Codeço for her valuable comments and suggestions.

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