What is the impact of national public expenditure and its allocation on neonatal and child mortality? A machine learning analysis.

BACKGROUND: Understanding the impact of national public expenditure and its allocation on child mortality may help governments move towards target 3.2 proposed in the 2030 Agenda. The objective of this study was to estimate the impacts of governmental expenditures, total, on health, and on other sectors, on neonatal mortality and mortality of children aged between 28 days and five years. METHODS: This study has an ecological design with a population of 147 countries, with data between 2012 and 2019. Two steps were used: first, the Generalized Propensity Score of public spending was calculated; afterward, the Generalized Propensity Score was used to estimate the expenditures' association with mortality rates. The primary outcomes were neonatal mortality rates (NeoRt) and mortality rates in children between 28 days and 5 years (NeoU5Rt). RESULTS: The 1% variation in Int$ Purchasing Power Parity (Int$ PPP) per capita in total public expenditures, expenditure in health, and in other sectors were associated with a variation of -0.635 (95% CI -1.176, -0.095), -2.17 (95% CI -3.051, -1.289) -0.632 (95% CI -1.169, -0.095) in NeoRt, respectively The same variation in public expenditures in sectors other than health, was associates with a variation of -1.772 (95% CI -6.219, -1.459) on NeoU5Rt. The results regarding the impact of total and health public spending on NeoU5Rt were not consistent. CONCLUSION: Public investments impact mortality in children under 5 years of age. Likely, the allocation of expenditures between the health sector and the other social sectors will have different impacts on mortality between the NeoRt and the NeoU5Rt.

Socioeconomic inequality in hospital case fatality rate and care among children and adolescents hospitalized for COVID-19 in Brazil.

OBJECTIVE: To analyze the association of hospital case fatality rate and care received by children and adolescents hospitalized for COVID-19 with the gross domestic product (GDP) per capita of Brazilian municipalities and regions of residence. METHODS: Data were collected from the Influenza Epidemiological Surveillance Information System and the Brazilian Institute of Geography and Statistics. The dichotomous outcomes analyzed were hospital case fatality rate of COVID-19, biological samples collected for COVID-19 diagnosis, X-rays, computed tomography (CT) scans, use of ventilatory support, and intensive care unit hospitalization. The covariates were municipal GDP per capita and the Brazilian region of residence. Poisson regression was used for the outcomes recorded in 2020 and 2021 in Brazil, covering the two COVID-19 waves in the country, adjusted for age and gender. RESULTS: The hospital case fatality rate was 7.6%. In municipalities with lower GDP per capita deciles, the case fatality rate was almost four times higher among children and twice as high in adolescents compared to cities with higher deciles. Additionally, residents of municipalities with lower GDP per capita had fewer biological samples collected for diagnosis, X-ray examinations, and CT scans. We found regional disparities associated with case fatality rate, with worse indicators in the North and Northeast regions. The findings remained consistent over the two COVID-19 waves. CONCLUSION: Municipalities with lower GDP per capita, as well as the North and Northeast regions, had worse indicators of hospital case fatality rate and care.

The burden of disease due to COVID-19 in Florianópolis, Santa Catarina, Brazil, over a one-year period. / A carga de doença por COVID-19 em Florianópolis, Santa Catarina, Brasil, no período de um ano.

COVID-19 has had a powerful impact on society with high rates of morbidity and mortality. The use of an epidemiological indicator that estimates the burden of a disease by aggregating early mortality and non-fatal cases in a single measure has the potential to assist in the planning of more appropriate actions at different levels of health care. The scope of this article is to estimate the burden of disease due to COVID-19 in Florianópolis/SC from April 2020 through March 2021. An ecological study was carried out with data from notification and deaths by COVID-19 in the period of 12 months. The burden indicator called Disability-Adjusted Life Years (DALY) was used, obtained by adding the Years of Life Lost (YLL) to the Years of healthy life lost due to disability (YLD). A total of 78,907 confirmed COVID-19 cases were included. Of these, 763 died during the period under study. Overall, 4,496.9 DALYs were estimated, namely a rate of 883.8 DALYs per 100,000 inhabitants. In males, there were 2,693.1 DALYs, a rate of 1,098.0 DALYs per 100,000 males. In women, there were 1,803.8 DALYs, a rate of 684.4 DALYs per100,000 women. The age group most affected in both sexes was 60 to 69 years. The burden of COVID-19 was high in the city studied. The highest rates were in females and in the 60-69 age group.

A COVID-19 gerou impacto na sociedade com elevados índices de morbidade e mortalidade. A utilização de indicador epidemiológico que estime a carga de doença, agregando em uma medida a mortalidade precoce e os casos não fatais, tem potencial de auxiliar no planejamento de ações adequadas em diferentes níveis de atenção à saúde. O objetivo deste artigo é estimar a carga de doença por COVID-19 em Florianópolis/SC de abril de 2020 a março de 2021. Foi realizado um estudo ecológico com dados de notificação e óbitos por COVID-19 no período de 12 meses. Utilizou-se o indicador de carga denominado Anos de Vida Perdidos Ajustados por Incapacidade (DALY), obtido pela soma dos Anos de Vida Perdidos (YLL) com os Anos Vividos com Incapacidade (YLD). Foram incluídos 78.907 casos de COVID-19 confirmados. Desses, 763 evoluíram a óbito no período estudado. No total, foram estimados 4.496,6 DALYs, taxa de 883,8 DALYs/100.000 habitantes. No sexo masculino, foram 2.693,1 DALYs, taxa de 1.098,0 DALYs/100.000 homens. Em mulheres, foram 1.803,8 DALYs, taxa de 684,4 DALYs/100.000 mulheres. A faixa etária mais acometida em ambos os sexos foi de 60 a 69 anos. Foi alta a carga de COVID-19 na cidade estudada. As maiores taxas foram encontradas no sexo feminino e na faixa-etária de 60-69 anos.

Impact assessment of emergency care units on hospitalizations for respiratory system diseases in Brazil.

Emergency Care Units (UPAs) are part of a national health policy implemented by the Brazilian Government. UPAs are fixed prehospital components of the Brazilian Unified Health System (SUS), whose purpose is to provide resolutive emergency care to patients suffering from acute clinical conditions, and to perform the first care in cases of surgical nature. According to the Ministry of Economy, 750 units are operational throughout the country since 2008, and 332 are under construction. Being a public policy in expansion, it is imperative to assess the impact of such units as part of SUS. However, we found few studies that assessed UPAs' impact, which have examined their specific impact on mortality rates. In our research, we aimed to evaluate the impact of UPAs on hospitalization rates for diseases of the respiratory system. To measure the impact, we used a strategy of Machine Learning through the Bayesian Additive Regression Trees (BART) algorithm. The results point to a decrease in the hospitalization rates by respiratory diseases due to Emergency Care Units. Therefore, these units generate a benefit for the Brazilian health system, being an important element for the care of patients with respiratory diseases.

Tobacco-related neoplasms: survival analysis and risk of death of population data from Florianópolis, SC.

OBJECTIVE: To estimate the probability of survival and prognostic factors for tobacco-related neoplasms in a population-based cohort. METHODS: This is a cohort with data from the Population-Based Cancer Registry of Florianópolis, southern Brazil, from 2008 to 2012. The Stata 16.0 software was used to estimate the probabilities of survival in five years after diagnosis, by the Kaplan Meier method, and the risk of death, by the Cox regression. RESULTS: A total of 2,829 cancer records related to smoking were included, more prevalent among males, over 70 years of age, nine years or more of schooling, white, with a partner and metastatic diagnosis. The most frequent groupings were colon and rectum (28.7%), trachea, bronchi and lungs (18.6%) and stomach (11.8%). At follow-up, 1,450 died. Pancreatic cancer had the worst probability of survival (14.3%), followed by liver cancer (19.4%). CONCLUSION: Risk factors for death and survival rates differ across the 13 types of tobacco-related cancers. Early diagnosis and primary prevention are strategies that must be improved to improve survival and decrease the burden related to these types of cancer.

Overall survival analyses of female malignancies in Southern Brazil during 2008-2017: A closer look at breast, cervical and ovarian cancer.

Background: The aim of this study was to report the overall survival and baseline factors associated with OS for breast, cervical and ovarian cancer in Florianópolis, Southern Brazil, a region with quality-of-life indicators comparable to high-income countries. Methods: Cohort study was performed from probabilistic record linkage of the Mortality Information System and the Population-based cancer registry of Florianópolis. It was included breasts, cervical and ovarian cancer diagnosis during the period of 2008-2012 with a follow up of 60 months. Cox regression and Kaplan-Meier method were used for associations with overall survival and risk factors. Findings: 1857 cases of the three malignancies were included in the analysis. We identified 202 deaths in breast cancer subjects, 53 for cervical cancer and 51 for ovarian cancer. Metastatic disease at diagnosis was present in 31%, 9.6%, and 55% of the cases, respectively. Overall survival was statistically correlated with age, educational level and stage for breast cancer; age and stage for cervical cancer; age and stage for ovarian cancer. Interpretation: Metastatic disease and age are the main prognostic factors for the malignancies studied, as they were associated with both overall survival and risk of death. Better screening and preventive tests for early diagnosis are needed. Funding: Support of Research and Innovation in the State of Santa Catarina, Research Program for the Unified Health System (FAPESC/MS-DECIT/CNPQ/SES-SC-PPSUS); the Brazilian National Research Council (CNPq); and the Coordination for the Improvement of Higher Education Personnel (CAPES).

Do family doctors refer less? Impact of FCM training on the rate of PHC referrals. / Médicos de família encaminham menos? Impacto da formação em MFC no percentual de encaminhamentos da Atenção Primária.

OBJECTIVE: To evaluate the impact of family medicine residence on the PHC referral rate. METHODS: This is a cross-sectional descriptive study on 375.645 visits and 34.776 referrals by 123 PHC physicians in 2016, linking the referral rate to the characteristics of doctors (gender, age, family medicine training), patients (gender and age) and service (general population and working population). RESULTS: Family and community medicine residency training had a significant reduction in PHC referral rate (2.86%), CI:(1.55;4.17), p < 0,0001. This reduction persisted in the multivariate analysis, after adjusting for all the possible confounding variables. No difference was found between the referral rates of doctors with and without family and community medicine (FCM) degree. Concerning referral to specialties, doctors with FCM residence training had lower rates of referral to gynecology, psychiatry and pediatrics and higher rates of referral to ophthalmology. CONCLUSION: The study showed that FCM residency significantly reduced PHC referral rates.

O objetivo deste artigo é medir o impacto da formação em medicina de família e comunidade no percentual de encaminhamentos a partir da atenção primária. Estudo transversal descritivo de 375.645 consultas e 34.776 encaminhamentos realizadas por 123 médicos da atenção primária no ano de 2016 relacionando o percentual de encaminhamentos com características dos médicos (sexo, idade, formação em MFC), dos pacientes (sexo e idade) e do serviço (população pelo IBGE e população ativa). A formação em MFC por meio de residência médica apresentou uma significativa redução no percentual de encaminhamentos a partir da atenção primária (2,86%), IC:(1,55;4,17), p < 0,0001. Essa redução manteve-se na análise multivariada mesmo ajustando-se para todas as possíveis variáveis confundidoras. Não houve diferença na comparação do percentual de encaminhamentos entre médicos sem formação em MFC e médicos com titulação em MFC. Na análise das especialidades para as quais foram realizados os encaminhamentos, os médicos com residência em MFC encaminharam menos para ginecologia, psiquiatria e pediatria e mais para oftalmologia. O estudo mostrou que a formação em MFC por meio de residência médica acarretou significativa redução no percentual de encaminhamentos a partir da atenção primária.

Estimating underdiagnosis of COVID-19 with nowcasting and machine learning.

OBJECTIVE: To analyze the underdiagnosis of COVID-19 through nowcasting with machine learning in a Southern Brazilian capital city. METHODS: Observational ecological design and data from 3916 notified cases of COVID-19 from April 14th to June 2nd, 2020 in Florianópolis, Brazil. A machine-learning algorithm was used to classify cases that had no diagnosis, producing the nowcast. To analyze the underdiagnosis, the difference between data without nowcasting and the median of the nowcasted projections for the entire period and for the six days from the date of onset of symptoms were compared. RESULTS: The number of new cases throughout the entire period without nowcasting was 389. With nowcasting, it was 694 (95%CI 496-897). During the six-day period, the number without nowcasting was 19 and 104 (95%CI 60-142) with nowcasting. The underdiagnosis was 37.29% in the entire period and 81.73% in the six-day period. The underdiagnosis was more critical in the six days from the date of onset of symptoms to diagnosis before the data collection than in the entire period. CONCLUSION: The use of nowcasting with machine learning techniques can help to estimate the number of new disease cases.

The potential spread of Covid-19 and government decision-making: a retrospective analysis in Florianópolis, Brazil. / O potencial de propagação da COVID-19 e a tomada de decisão governamental: uma análise retrospectiva em Florianópolis, Brasil.

OBJECTIVE: To analyze the association between the transmission potential of SARS-CoV-2 and the decisions made by the municipal government of Florianópolis (Brazil) regarding social distancing. METHODS: We analyzed new cases of COVID-19 identified in Florianópolis residents between February 1 and July 14, 2020, using a nowcasting approach. Decrees related to COVID-19 published in the Official Gazette of the Municipality between February 1 and July 14, 2020 were also analyzed. Based on the actions proposed in the decrees, whether they loosened social distancing measures, or increased or maintained existing restrictions, was analyzed, thus creating a Social Distancing Index. Time-dependent reproduction numbers (Rt) for a period of 14 days prior to each decree were calculated. A matrix was constructed associating the classification of each decree and the Rt values, analyzing the consonance or dissonance between the potential dissemination of SARS-CoV-2 and the actions of the decrees. RESULTS: A total of 5,374 cases of COVID-19 and 26 decrees were analyzed. Nine decrees increased social distancing measures, nine maintained them, and eight loosened them. Of the 26 actions, 9 were consonant and 17 dissonant with the tendency indicated by the Rt. Dissonance was observed in all of the decrees that maintained the distance measures or loosened them. The fastest expansion in the number of new cases and the greatest amount of dissonant decrees was found in the last two months analyzed. CONCLUSION: There was an important divergence between municipal measures of social distancing with epidemiological indicators at the time of each political decision.

OBJETIVO: Analisar a relação entre o potencial de propagação do SARS-CoV-2 e as tomadas de decisão do governo municipal de Florianópolis, Brasil, quanto ao distanciamento social. MÉTODOS: Foram analisados casos novos de COVID-19 com tratamento de nowcasting identificados em residentes de Florianópolis entre 1º de fevereiro e 14 de julho de 2020. Também foram examinados os decretos relacionados à COVID-19 publicados no Diário Oficial do Município entre 1º de fevereiro e 14 de julho de 2020. Com base nas ações dispostas nos decretos, analisou-se se elas promoviam o relaxamento, o aumento ou a manutenção das restrições vigentes, criando-se o Índice de Distanciamento Social. Para o período de 14 dias anteriores a cada decreto, calcularam-se os números de reprodução dependente do tempo (Rt). Construiu-se uma matriz entre a classificação de cada decreto e os valores de Rt, verificando-se a consonância ou a dissonância entre o potencial de disseminação do SARS-CoV-2 e as ações dos decretos. RESULTADOS: Foram analisados 5.374 casos de COVID-19 e 26 decretos. Nove decretos aumentaram as medidas de distanciamento social, nove as mantiveram e oito as flexibilizaram. Das 26 ações, nove eram consonantes e 17 dissonantes com a tendência indicada pelos Rt. Dissonâncias foram observadas com todos os decretos que mantiveram as medidas de distanciamento e os que as flexibilizaram. No segundo bimestre da análise houve a mais rápida expansão do número de casos novos e a maior quantidade de dissonâncias dos decretos. CONCLUSÃO: Observou-se importante divergência entre as medidas de distanciamento social com indicadores epidemiológicos no momento da decisão política.

Risk factors for neonatal death in the capital city with the lowest infant mortality rate in Brazil.

OBJECTIVES: To analyze the risk factors for neonatal death in Florianópolis, the Brazilian city capital with the lowest infant mortality rate. METHOD: Data were extracted from a historical cohort with 15,879 live births. A model was used that included socioeconomic, behavioral, and health service use risk factors, as well as the Apgar score and biological factors. Risk factors were analyzed by hierarchical logistic regression. RESULTS: Based on the multivariate analysis, socioeconomic factors showed no association with death. Insufficient prenatal consultations showed an OR of 3.25 (95% CI: 1.70-6.48) for death. Low birth weight (OR 8.42; 95% CI: 3.45-21.93); prematurity (OR 5.40; 95% CI: 2.22-13.88); malformations (OR 4.42; 95% CI: 1.37-12.43); and low Apgar score at the first (OR 6.65; 95% CI: 3.36-12.94) and at the fifth (OR 19.78; 95% CI: 9.12-44.50) minutes, were associated with death. CONCLUSION: Differing from other studies, socioeconomic conditions were not associated with neonatal death. Insufficient prenatal consultations, low Apgar score, prematurity, low birth weight, and malformations showed an association, reinforcing the importance of prenatal access universalization and its integration with medium and high-complexity neonatal care services.

Socioeconomic inequality in hospital case fatality rate and care among children and adolescents hospitalized for COVID-19 in Brazil / Desigualdade socioeconômica na letalidade e no cuidado hospitalar de crianças e adolescentes internados por COVID-19 no Brasil

ABSTRACT Objective: To analyze the association of hospital case fatality rate and care received by children and adolescents hospitalized for COVID-19 with the gross domestic product (GDP) per capita of Brazilian municipalities and regions of residence. Methods: Data were collected from the Influenza Epidemiological Surveillance Information System and the Brazilian Institute of Geography and Statistics. The dichotomous outcomes analyzed were hospital case fatality rate of COVID-19, biological samples collected for COVID-19 diagnosis, X-rays, computed tomography (CT) scans, use of ventilatory support, and intensive care unit hospitalization. The covariates were municipal GDP per capita and the Brazilian region of residence. Poisson regression was used for the outcomes recorded in 2020 and 2021 in Brazil, covering the two COVID-19 waves in the country, adjusted for age and gender. Results: The hospital case fatality rate was 7.6%. In municipalities with lower GDP per capita deciles, the case fatality rate was almost four times higher among children and twice as high in adolescents compared to cities with higher deciles. Additionally, residents of municipalities with lower GDP per capita had fewer biological samples collected for diagnosis, X-ray examinations, and CT scans. We found regional disparities associated with case fatality rate, with worse indicators in the North and Northeast regions. The findings remained consistent over the two COVID-19 waves. Conclusion: Municipalities with lower GDP per capita, as well as the North and Northeast regions, had worse indicators of hospital case fatality rate and care.

RESUMO Objetivo: Analisar a associação entre a letalidade e o cuidado hospitalar recebido por crianças e adolescentes internados por COVID-19 e o produto interno bruto (PIB) per capita dos municípios brasileiros e a região de residência. Métodos: Os dados foram extraídos do Sistema de Informação de Vigilância Epidemiológica da Gripe e do Instituto Brasileiro de Geografia e Estatística. Analisaram-se como desfechos dicotômicos a letalidade hospitalar por COVID-19, a coleta de amostra biológica para diagnóstico de COVID-19, a realização de exames raio X e tomografia, o uso de suporte ventilatório e a internação em unidade de terapia intensiva. As covariáveis foram o PIB municipal per capita e a região brasileira de residência. Foi realizada regressão de Poisson para os desfechos registrados em 2020 e 2021 no Brasil e segundo o período compreendido em duas ondas de COVID-19 no país, ajustando-a por idade e sexo. Resultados: A letalidade hospitalar foi de 7,6%. Nos municípios dos menores decis de PIB per capita a letalidade foi quase quatro vezes maior entre crianças e duas vezes mais elevada entre adolescentes quando comparada àquela dos maiores decis. Adicionalmente, os residentes de municípios com menor PIB per capita realizaram menos coleta de amostra biológica para diagnóstico, exames de raio X e tomografias. Foram encontradas disparidades regionais associadas à letalidade, com piores indicadores nas regiões Norte e Nordeste. Os achados mantiveram-se consistentes durante as duas ondas de COVID-19. Conclusão: Em municípios com menor PIB per capita e das regiões Norte e Nordeste houve piores indicadores de letalidade e cuidado hospitalar.

A carga de doença por COVID-19 em Florianópolis, Santa Catarina, Brasil, no período de um ano / The burden of disease due to COVID-19 in Florianópolis, Santa Catarina, Brazil, over a one-year period

Resumo A COVID-19 gerou impacto na sociedade com elevados índices de morbidade e mortalidade. A utilização de indicador epidemiológico que estime a carga de doença, agregando em uma medida a mortalidade precoce e os casos não fatais, tem potencial de auxiliar no planejamento de ações adequadas em diferentes níveis de atenção à saúde. O objetivo deste artigo é estimar a carga de doença por COVID-19 em Florianópolis/SC de abril de 2020 a março de 2021. Foi realizado um estudo ecológico com dados de notificação e óbitos por COVID-19 no período de 12 meses. Utilizou-se o indicador de carga denominado Anos de Vida Perdidos Ajustados por Incapacidade (DALY), obtido pela soma dos Anos de Vida Perdidos (YLL) com os Anos Vividos com Incapacidade (YLD). Foram incluídos 78.907 casos de COVID-19 confirmados. Desses, 763 evoluíram a óbito no período estudado. No total, foram estimados 4.496,6 DALYs, taxa de 883,8 DALYs/100.000 habitantes. No sexo masculino, foram 2.693,1 DALYs, taxa de 1.098,0 DALYs/100.000 homens. Em mulheres, foram 1.803,8 DALYs, taxa de 684,4 DALYs/100.000 mulheres. A faixa etária mais acometida em ambos os sexos foi de 60 a 69 anos. Foi alta a carga de COVID-19 na cidade estudada. As maiores taxas foram encontradas no sexo feminino e na faixa-etária de 60-69 anos.

Abstract COVID-19 has had a powerful impact on society with high rates of morbidity and mortality. The use of an epidemiological indicator that estimates the burden of a disease by aggregating early mortality and non-fatal cases in a single measure has the potential to assist in the planning of more appropriate actions at different levels of health care. The scope of this article is to estimate the burden of disease due to COVID-19 in Florianópolis/SC from April 2020 through March 2021. An ecological study was carried out with data from notification and deaths by COVID-19 in the period of 12 months. The burden indicator called Disability-Adjusted Life Years (DALY) was used, obtained by adding the Years of Life Lost (YLL) to the Years of healthy life lost due to disability (YLD). A total of 78,907 confirmed COVID-19 cases were included. Of these, 763 died during the period under study. Overall, 4,496.9 DALYs were estimated, namely a rate of 883.8 DALYs per 100,000 inhabitants. In males, there were 2,693.1 DALYs, a rate of 1,098.0 DALYs per 100,000 males. In women, there were 1,803.8 DALYs, a rate of 684.4 DALYs per100,000 women. The age group most affected in both sexes was 60 to 69 years. The burden of COVID-19 was high in the city studied. The highest rates were in females and in the 60-69 age group.

Impact assessment of emergency care units on hospitalizations for respiratory system diseases in Brazil / Avaliação do impacto das unidades de pronto atendimento sobre as internações por doenças do aparelho respiratório no Brasil

Abstract Emergency Care Units (UPAs) are part of a national health policy implemented by the Brazilian Government. UPAs are fixed prehospital components of the Brazilian Unified Health System (SUS), whose purpose is to provide resolutive emergency care to patients suffering from acute clinical conditions, and to perform the first care in cases of surgical nature. According to the Ministry of Economy, 750 units are operational throughout the country since 2008, and 332 are under construction. Being a public policy in expansion, it is imperative to assess the impact of such units as part of SUS. However, we found few studies that assessed UPAs' impact, which have examined their specific impact on mortality rates. In our research, we aimed to evaluate the impact of UPAs on hospitalization rates for diseases of the respiratory system. To measure the impact, we used a strategy of Machine Learning through the Bayesian Additive Regression Trees (BART) algorithm. The results point to a decrease in the hospitalization rates by respiratory diseases due to Emergency Care Units. Therefore, these units generate a benefit for the Brazilian health system, being an important element for the care of patients with respiratory diseases.

Resumo As Unidades de Pronto Atendimento 24h (UPAs) compõem a Política de Atenção a Urgências e Emergências (PNAU) implementada pelo Governo Federal. São componentes pré-hospitalares fixos do SUS, cujo objetivo é o atendimento resolutivo de urgência a pacientes que sofrem quadros clínicos agudos, e o primeiro atendimento em casos cirúrgicos. Desde 2008, funcionam 750 unidades no Brasil, e há 332 em construção, conforme dados de 2020 do Ministério da Economia. Diante de uma política em expansão, é indispensável avaliar seus efeitos como parte do SUS. No entanto, foram encontrados poucos trabalhos avaliando o impacto das UPAs, e esses mediram os efeitos sobre taxas de mortalidade. Este trabalho objetiva mensurar o efeito das UPAs nas taxas de internação por doenças do aparelho respiratório. Para isso, utilizou-se uma estratégia de Machine Learning por meio do algoritmo Bayesian Additive Regression Trees (BART). Os resultados apontam uma diminuição nas taxas de internações por doenças do aparelho respiratório devido às UPAs. Assim, as evidências são de que essas unidades geram benefício para o sistema de saúde, sendo uma peça importante na linha de cuidado dos pacientes com doenças respiratórias.

Médicos de família encaminham menos? Impacto da formação em MFC no percentual de encaminhamentos da Atenção Primária / Do family doctors refer less? Impact of FCM training on the rate of PHC referrals

Resumo O objetivo deste artigo é medir o impacto da formação em medicina de família e comunidade no percentual de encaminhamentos a partir da atenção primária. Estudo transversal descritivo de 375.645 consultas e 34.776 encaminhamentos realizadas por 123 médicos da atenção primária no ano de 2016 relacionando o percentual de encaminhamentos com características dos médicos (sexo, idade, formação em MFC), dos pacientes (sexo e idade) e do serviço (população pelo IBGE e população ativa). A formação em MFC por meio de residência médica apresentou uma significativa redução no percentual de encaminhamentos a partir da atenção primária (2,86%), IC:(1,55;4,17), p < 0,0001. Essa redução manteve-se na análise multivariada mesmo ajustando-se para todas as possíveis variáveis confundidoras. Não houve diferença na comparação do percentual de encaminhamentos entre médicos sem formação em MFC e médicos com titulação em MFC. Na análise das especialidades para as quais foram realizados os encaminhamentos, os médicos com residência em MFC encaminharam menos para ginecologia, psiquiatria e pediatria e mais para oftalmologia. O estudo mostrou que a formação em MFC por meio de residência médica acarretou significativa redução no percentual de encaminhamentos a partir da atenção primária.

Abstract Objective: To evaluate the impact of family medicine residence on the PHC referral rate. Methods: This is a cross-sectional descriptive study on 375.645 visits and 34.776 referrals by 123 PHC physicians in 2016, linking the referral rate to the characteristics of doctors (gender, age, family medicine training), patients (gender and age) and service (general population and working population). Results: Family and community medicine residency training had a significant reduction in PHC referral rate (2.86%), CI:(1.55;4.17), p < 0,0001. This reduction persisted in the multivariate analysis, after adjusting for all the possible confounding variables. No difference was found between the referral rates of doctors with and without family and community medicine (FCM) degree. Concerning referral to specialties, doctors with FCM residence training had lower rates of referral to gynecology, psychiatry and pediatrics and higher rates of referral to ophthalmology. Conclusion: The study showed that FCM residency significantly reduced PHC referral rates.

Estimating underdiagnosis of COVID-19 with nowcasting and machine learning / Estimativa do subdiagnóstico de COVID-19 utilizando machine learning e nowcasting

ABSTRACT: Objective: To analyze the underdiagnosis of COVID-19 through nowcasting with machine learning in a Southern Brazilian capital city. Methods: Observational ecological design and data from 3916 notified cases of COVID-19 from April 14th to June 2nd, 2020 in Florianópolis, Brazil. A machine-learning algorithm was used to classify cases that had no diagnosis, producing the nowcast. To analyze the underdiagnosis, the difference between data without nowcasting and the median of the nowcasted projections for the entire period and for the six days from the date of onset of symptoms were compared. Results: The number of new cases throughout the entire period without nowcasting was 389. With nowcasting, it was 694 (95%CI 496-897). During the six-day period, the number without nowcasting was 19 and 104 (95%CI 60-142) with nowcasting. The underdiagnosis was 37.29% in the entire period and 81.73% in the six-day period. The underdiagnosis was more critical in the six days from the date of onset of symptoms to diagnosis before the data collection than in the entire period. Conclusion: The use of nowcasting with machine learning techniques can help to estimate the number of new disease cases.

RESUMO: Objetivo: Analisar o subdiagnóstico da COVID-19 por meio de nowcasting com machine learning em uma capital do sul do Brasil. Métodos: Estudo ecológico observacional utilizando dados de 3.916 casos notificados de COVID-19 de 14 de abril a 2 de junho de 2020 em Florianópolis, Brasil. O algoritmo de machine learning foi usado para classificar os casos que ainda não tinham diagnóstico, produzindo o nowcasting. Para analisar o subdiagnóstico, foi comparada a diferença entre os dados sem nowcasting e a mediana das projeções com nowcasting para todo o período e para os seis dias a partir da data de início dos sintomas. Resultados: O número de novos casos sem nowcasting durante todo o período foi de 389, com nowcasting foi de 694 (IC95% 496-897). No período de seis dias, o número sem nowcasting foi de 19 e 104 (IC95% 60-142) com nowcasting. O subdiagnóstico foi de 37,29% em todo o período e 81,73% no período de seis dias. O subdiagnóstico foi mais crítico em seis dias, desde a data do início dos sintomas até o diagnóstico antes da coleta de dados, do que em todo o período. Conclusão: O uso de nowcasting com técnicas de machine learning pode ajudar a estimar o número de novos casos da doença.

O potencial de propagação da COVID-19 e a tomada de decisão governamental: uma análise retrospectiva em Florianópolis, Brasil / The potential spread of Covid-19 and government decision-making: a retrospective analysis in Florianópolis, Brazil

RESUMO: Objetivo: Analisar a relação entre o potencial de propagação do SARS-CoV-2 e as tomadas de decisão do governo municipal de Florianópolis, Brasil, quanto ao distanciamento social. Métodos: Foram analisados casos novos de COVID-19 com tratamento de nowcasting identificados em residentes de Florianópolis entre 1º de fevereiro e 14 de julho de 2020. Também foram examinados os decretos relacionados à COVID-19 publicados no Diário Oficial do Município entre 1º de fevereiro e 14 de julho de 2020. Com base nas ações dispostas nos decretos, analisou-se se elas promoviam o relaxamento, o aumento ou a manutenção das restrições vigentes, criando-se o Índice de Distanciamento Social. Para o período de 14 dias anteriores a cada decreto, calcularam-se os números de reprodução dependente do tempo (Rt). Construiu-se uma matriz entre a classificação de cada decreto e os valores de Rt, verificando-se a consonância ou a dissonância entre o potencial de disseminação do SARS-CoV-2 e as ações dos decretos. Resultados: Foram analisados 5.374 casos de COVID-19 e 26 decretos. Nove decretos aumentaram as medidas de distanciamento social, nove as mantiveram e oito as flexibilizaram. Das 26 ações, nove eram consonantes e 17 dissonantes com a tendência indicada pelos Rt. Dissonâncias foram observadas com todos os decretos que mantiveram as medidas de distanciamento e os que as flexibilizaram. No segundo bimestre da análise houve a mais rápida expansão do número de casos novos e a maior quantidade de dissonâncias dos decretos. Conclusão: Observou-se importante divergência entre as medidas de distanciamento social com indicadores epidemiológicos no momento da decisão política.

ABSTRACT: Objective: To analyze the association between the transmission potential of SARS-CoV-2 and the decisions made by the municipal government of Florianópolis (Brazil) regarding social distancing. Methods: We analyzed new cases of COVID-19 identified in Florianópolis residents between February 1 and July 14, 2020, using a nowcasting approach. Decrees related to COVID-19 published in the Official Gazette of the Municipality between February 1 and July 14, 2020 were also analyzed. Based on the actions proposed in the decrees, whether they loosened social distancing measures, or increased or maintained existing restrictions, was analyzed, thus creating a Social Distancing Index. Time-dependent reproduction numbers (Rt) for a period of 14 days prior to each decree were calculated. A matrix was constructed associating the classification of each decree and the Rt values, analyzing the consonance or dissonance between the potential dissemination of SARS-CoV-2 and the actions of the decrees. Results: A total of 5,374 cases of COVID-19 and 26 decrees were analyzed. Nine decrees increased social distancing measures, nine maintained them, and eight loosened them. Of the 26 actions, 9 were consonant and 17 dissonant with the tendency indicated by the Rt. Dissonance was observed in all of the decrees that maintained the distance measures or loosened them. The fastest expansion in the number of new cases and the greatest amount of dissonant decrees was found in the last two months analyzed. Conclusion: There was an important divergence between municipal measures of social distancing with epidemiological indicators at the time of each political decision.

Risk factors for neonatal death in the capital city with the lowest infant mortality rate in Brazil / Fatores de risco para o óbito neonatal na capital com menor taxa de mortalidade infantil do Brasil

Abstract Objectives: To analyze the risk factors for neonatal death in Florianópolis, the Brazilian city capital with the lowest infant mortality rate. Method: Data were extracted from a historical cohort with 15,879 live births. A model was used that included socioeconomic, behavioral, and health service use risk factors, as well as the Apgar score and biological factors. Risk factors were analyzed by hierarchical logistic regression. Results: Based on the multivariate analysis, socioeconomic factors showed no association with death. Insufficient prenatal consultations showed an OR of 3.25 (95% CI: 1.70-6.48) for death. Low birth weight (OR 8.42; 95% CI: 3.45-21.93); prematurity (OR 5.40; 95% CI: 2.22-13.88); malformations (OR 4.42; 95% CI: 1.37-12.43); and low Apgar score at the first (OR 6.65; 95% CI: 3.36-12.94) and at the fifth (OR 19.78; 95% CI: 9.12-44.50) minutes, were associated with death. Conclusion: Differing from other studies, socioeconomic conditions were not associated with neonatal death. Insufficient prenatal consultations, low Apgar score, prematurity, low birth weight, and malformations showed an association, reinforcing the importance of prenatal access universalization and its integration with medium and high-complexity neonatal care services.

Resumo Objetivos: Analisar os fatores de risco para o óbito neonatal em Florianópolis, capital brasileira com a menor taxa de mortalidade infantil. Método: Os dados foram extraídos de coorte histórica, contando com 15.879 nascidos vivos. Utilizou-se modelo ordenando fatores de risco socioeconômicos, comportamentais e de utilização dos serviços de saúde, além do escore de Apgar e de fatores biológicos. Os fatores de risco foram analisados por regressão logística hierarquizada. Resultados: Com base na análise multivariada, os fatores socioeconômicos não mostraram associação com o óbito. Consultas pré-natais insuficientes apresentaram um OR 3,25 (IC95% 1,70-6,48) para óbito. Baixo peso ao nascer (OR 8,42; IC95% 3,45-21,93); prematuridade (OR 5,40; IC95% 2,22-13,88); malformações (OR 4,42; IC95% 1,37-12,43); baixo escore de Apgar no 1o (OR 6,65; IC95% 3,36-12,94) e no 5o (OR 19,78; IC95% 9,12-44,50) minutos associaram-se ao óbito. Conclusão: Diferente de outros estudos, as condições socioeconômicas não se associaram ao óbito neonatal. Pré-natal insuficiente, baixo escore de Apgar, prematuridade, baixo peso e malformações mostraram associação, reforçando a importância da universalização do acesso ao pré-natal e da integração deste com serviços de atenção ao recém-nascido, de média e alta complexidade.