OBJETIVOS: Estimar a prevalência e fatores associados à hesitação ao uso da vacina contra o vírus SARS-CoV-2 no Maranhão, Brasil. MÉTODOS: Estudo transversal de base populacional realizado de 19 a 30 de outubro de 2020. As estimativas consideraram agrupamento, estratificação e não resposta. A seleção da amostra foi realizada em três estágios (estrato, setores censitários e domicílio). Após análise sistemática, em cada estrato foram selecionados trinta setores, totalizando 150 setores, sendo o número de domicílios em cada setor fixado em 34, totalizando 5.100 domicílios e um indivíduo por domicílio (residente pelo menos há seis meses e com um ano de idade ou mais) selecionado por amostra aleatória simples. A intenção de ser vacinado foi questionada aos participantes. Foi realizada análise descritiva (frequências ponderadas) e teste do qui-quadrado de Pearson para verificar associação univariada entre as variáveis independentes e o desfecho (p < 0,05). Realizou-se análise multivariada robusta utilizando-se modelagem hierarquizada em três níveis. RESULTADOS: Foram entrevistados 4.630 indivíduos. A prevalência de hesitação vacinal foi de 17,5% (IC95% 16,1–19,1%). Após ajuste final do modelo, a hesitação vacinal foi estatisticamente maior entre moradores das cidades de Imperatriz (24,0%; RP = 1,48; IC95% 1,09–2,02) e de munícipios da Grande Ilha de São Luís (20,7%; RP = 1,34; IC95% 1,02–1,76), pessoas do sexo feminino (19,8%; RP = 1,44; IC95% 1,20–1,75), idosos (22,8%; RP = 1,79; IC95% 1,30–2,46), pertencentes às religiões de denominação evangélica (24,1%; RP = 1,49; IC95% 1,24–1,79) e entre aqueles sem relato de sintomas (18,6%; RP = 1,24; IC95% 1,02–1,51). Outras características socioeconômicas e demográficas, assim como variáveis relacionadas ao mercado de trabalho, comportamentos e condições de saúde dos entrevistados, não tiveram diferença estatística. CONCLUSÃO: A prevalência de hesitação vacinal no Maranhão e sua associação com fatores individuais, contextuais e clínicos revelam os grupos e contextos mais resistentes e que devem merecer atenção especial das estratégias públicas para garantir a ampla vacinação.

OBJECTIVE To estimate the 2020 all-cause and COVID-19 excess mortality according to sex, age, race/color, and state, and to compare mortality rates by selected causes with that of the five previous years in Brazil. METHODS Data from the Mortality Information System were used. Expected deaths for 2020 were estimated from 2015 to 2019 data using a negative binomial log-linear model. RESULTS Excess deaths in Brazil in 2020 amounted to 13.7%, and the ratio of excess deaths to COVID-19 deaths was 0.90. Reductions in deaths from cardiovascular diseases (CVD), respiratory diseases, and external causes, and an increase in ill-defined causes were all noted. Excess deaths were also found to be heterogeneous, being higher in the Northern, Center-Western, and Northeastern states. In some states, the number of COVID-19 deaths was lower than that of excess deaths, whereas the opposite occurred in others. Moreover, excess deaths were higher in men aged 20 to 59, and in black, yellow, or indigenous individuals. Meanwhile, excess mortality was lower in women, in individuals aged 80 years or older, and in whites. Additionally, deaths among those aged 0 to 19 were 7.2% lower than expected, with reduction in mortality from respiratory diseases and external causes. There was also a drop in mortality due to external causes in men and in those aged 20 to 39 years. Moreover, reductions in deaths from CVD and neoplasms were noted in some states and groups. CONCLUSION There is evidence of underreporting of COVID-19 deaths and of the possible impact of restrictive measures in the reduction of deaths from external causes and respiratory diseases. The impacts of COVID-19 on mortality were heterogeneous among the states and groups, revealing that regional, demographic, socioeconomic, and racial differences expose individuals in distinct ways to the risk of death from both COVID-19 and other causes.

Preterm birth (PTB) is a growing health issue worldwide, currently considered the leading cause of newborn deaths. To address this challenge, the present work aims to develop an algorithm capable of accurately predicting the week of delivery supporting the identification of a PTB in Brazil. This a population-based study analyzing data from 3,876,666 mothers with live births distributed across the 3,929 Brazilian municipalities. Using indicators comprising delivery characteristics, primary care work processes, and physical infrastructure, and sociodemographic data we applied a machine learning-based approach to estimate the week of delivery at the point of care level. We tested six algorithms: eXtreme Gradient Boosting, Elastic Net, Quantile Ordinal Regression - LASSO, Linear Regression, Ridge Regression and Decision Tree. We used the root-mean-square error (RMSE) as a precision. All models obtained RMSE indexes close to each other. The lower levels of RMSE were obtained using the eXtreme Gradient Boosting approach which was able to estimate the week of delivery within a 2.09 window 95%IC (2.090–2.097). The five most important variables to predict the week of delivery were: number of previous deliveries through Cesarean-Section, number of prenatal consultations, age of the mother, existence of ultrasound exam available in the care network, and proportion of primary care teams in the municipality registering the oral care consultation. Using simple data describing the prenatal care offered, as well as minimal characteristics of the pregnant, our approach was capable of achieving a relevant predictive performance regarding the week of delivery. Bill and Melinda Gates Foundation, and National Council for Scientific and Technological Development – Brazil, (Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPQ acronym in portuguese) Support of the research project named: Data-Driven Risk Stratification for Preterm Birth in Brazil: Development of a Machine Learning-Based Innovation for Health Care- Grant: OPP1202186

This study describes the COVID-19 death reporting delay in the city of São Luís, Maranhão State, Brazil, and shows its impact on timely monitoring and modeling of the COVID-19 pandemic, while seeking to ascertain how nowcasting can improve death reporting delay. We analyzed COVID-19 death data reported daily in the Epidemiological Bulletin of the State Health Secretariat of Maranhão and calculated the reporting delay from March 23 to August 29, 2020. A semi-mechanistic Bayesian hierarchical model was fitted to illustrate the impact of death reporting delay and test the effectiveness of a Bayesian Nowcasting in improving data quality. Only 17.8% of deaths were reported without delay or the day after, while 40.5% were reported more than 30 days late. Following an initial underestimation due to reporting delay, 644 deaths were reported from June 7 to August 29, although only 116 deaths occurred during this period. Using the Bayesian nowcasting technique partially improved the quality of mortality data during the peak of the pandemic, providing estimates that better matched the observed scenario in the city, becoming unusable nearly two months after the peak. As delay in death reporting can directly interfere with assertive and timely decision-making regarding the COVID-19 pandemic, the Brazilian epidemiological surveillance system must be urgently revised and notifying the date of death must be mandatory. Nowcasting has proven somewhat effective in improving the quality of mortality data, but only at the peak of the pandemic.

Summary: Background: Few population-based studies on the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been performed to date, and most of them have used lateral flow immunoassays with finger-prick, which may yield false-negative results and thus underestimate the true infection rate. Methods: A population-based household survey was performed in the State of Maranhão, Brazil, from 27 July 2020 to 8 August 2020 to estimate the seroprevalence of SARS-CoV-2 using a serum testing electrochemiluminescence immunoassay. A three-stage cluster sampling stratified by four state regions was used. The estimates took clustering, stratification, and non-response into account. Qualitative detection of IgM and IgG antibodies was performed in a fully-automated Elecsys® Anti-SARS-CoV-2 electrochemiluminescence immunoassay on the Cobas® e601 analyser (Roche Diagnostics). Findings: A total of 3156 individuals were interviewed. Seroprevalence of total antibodies against SARS-CoV-2 was 40·4% (95%CI 35·6-45·3). Population adherence to non-pharmaceutical interventions was higher at the beginning of the pandemic than in the last month. SARS-CoV-2 infection rates were significantly lower among mask wearers and among those who maintained social and physical distancing in the last month compared to their counterparts. Among the infected, 62·2% had more than three symptoms, 11·1% had one or two symptoms, and 26·0% were asymptomatic. The infection fatality rate was 0·17%, higher for males and advanced age groups. The ratio of estimated infections to reported cases was 22·2. Interpretation: To the best of our knowledge, the seroprevalence of SARS-CoV-2 estimated in this population-based survey was the highest and the closest to the herd immunity threshold reported to date. Our results suggest that the herd immunity threshold is not as low as 20%, but at least higher than or equal to around 40%. The infection fatality rate was one of the lowest reported so far, and the proportion of asymptomatic cases was low.

Penile cancer (PC) is a neoplasm with variable incidence depending on geographic location, with higher prevalence in underdeveloped countries when compared with developed countries (¹ 1 Montes Cardona CE, García-Perdomo HA. Incidence of penile cancer worldwide: systematic review and meta-analysis. Rev Panam Salud Publica. 2017;41:e117. ). Moreover, the poorest regions of Brazil have the highest incidence of PC, according to the literature (² 2 Coelho RWP, Pinho JD, Moreno JS, Garbis DVEO, do Nascimento AMT, Larges JS, et al. Penile cancer in Maranhão, Northeast Brazil: the highest incidence globally? BMC Urol. 2018;18:50. –⁴ 4 Favorito LA, Nardi AC, Ronalsa M, Zequi SC, Sampaio FJ, Glina S. Epidemiologic study on penile cancer in Brazil. Int Braz J Urol. 2008;34:587-91; discussion 591-3. ). Because PC mainly affects a socially disadvantaged population from underdeveloped countries, knowledge of its pathology, clinical management, and treatment is still limited. However, it has been revealed that the presence and extent of inguinal lymph node metastasis are the most important prognostic factors of PC (⁵ 5 Azevedo RA, Roxo AC, Alvares SHB, Baptista DP, Favorito LA. Use of flaps in inguinal lymphadenectomy in metastatic penile cancer. Int Braz J Urol. 2021;47:1108-19. –⁷ 7 Srinivas V, Morse MJ, Herr HW, Sogani PC, Whitmore WF Jr. Penile cancer: relation of extent of nodal metastasis to survival. J Urol. 1987;137:880-2. ).