The Burden of Chagas Disease in the Contemporary World: The RAISE Study.

Chagas disease (ChD), a Neglected Tropical Disease, has witnessed a transformative epidemiological landscape characterized by a trend of reduction in prevalence, shifting modes of transmission, urbanization, and globalization. Historically a vector-borne disease in rural areas of Latin America, effective control measures have reduced the incidence in many countries, leading to a demographic shift where most affected individuals are now adults. However, challenges persist in regions like the Gran Chaco, and emerging oral transmission in the Amazon basin adds complexity. Urbanization and migration from rural to urban areas and to non-endemic countries, especially in Europe and the US, have redefined the disease's reach. These changing patterns contribute to uncertainties in estimating ChD prevalence, exacerbated by the lack of recent data, scarcity of surveys, and reliance on outdated models. Besides, ChD's lifelong natural history, marked by acute and chronic phases, introduces complexities in diagnosis, particularly in non-endemic regions where healthcare provider awareness is low. The temporal dissociation of infection and clinical manifestations, coupled with underreporting, has rendered ChD invisible in health statistics. Deaths attributed to ChD cardiomyopathy often go unrecognized, camouflaged under alternative causes. Understanding these challenges, the RAISE project aims to reassess the burden of ChD and ChD cardiomyopathy. The project is a collaborative effort of the World Heart Federation, Novartis Global Health, the University of Washington's Institute for Health Metrics and Evaluation, and a team of specialists coordinated by Brazil's Federal University of Minas Gerais. Employing a multidimensional strategy, the project seeks to refine estimates of ChD-related deaths, conduct systematic reviews on seroprevalence and prevalence of clinical forms, enhance existing modeling frameworks, and calculate the global economic burden, considering healthcare expenditures and service access. The RAISE project aspires to bridge knowledge gaps, raise awareness, and inform evidence-based health policies and research initiatives, positioning ChD prominently on the global health agenda.

Excess Mortality due to natural causes among whites and blacks during the COVID-19 pandemic in Brazil.

INTRODUCTION: Excess Mortality by all causes considers deaths directly related to COVID-19 and those attributed to conditions caused by the pandemic. When stratified by social dimensions, such as race/color, it allows for the evaluation of more vulnerable populations. The study estimated the excess mortality by natural causes, separating the white and black populations in 2020. METHODS: Public civil registration data on deaths observed in 2020, corrected for under registration, were used. The expected number of deaths was estimated based on the mortality rates observed in 2019, applied to the estimated population in 2020. The difference between the values expected and observed and the proportion of excess was considered the excess mortality. RESULTS: The present study found an excess of 270,321 deaths (22.2% above the expected) in 2020. Every state of Brazil reported deaths above the corresponding expected figure. The excess was higher for men (25.2%) than for women (19.0%). Blacks showed an excess of 27.8%, as compared to whites at 17.6%. In both sexes and all age groups, excess was higher in the black population, especially in the South, Southeast, and Midwest regions. São Paulo, the largest in population number, had twice as much excess death in the black population (25.1%) than in the white population (11.5%). CONCLUSIONS: The present study showed racial disparities in excess mortality during the COVID-19 pandemic in Brazil. The higher excess found for the black suggests an intrinsic relationship with the socioeconomic situation, further exposing the Brazilian reality, in which social and structural inequality is evident.

Measuring misclassification of Covid-19 as garbage codes: Results of investigating 1,365 deaths and implications for vital statistics in Brazil.

The purpose of this article is to quantify the amount of misclassification of the Coronavirus Disease-2019 (COVID-19) mortality occurring in hospitals and other health facilities in selected cities in Brazil, discuss potential factors contributing to this misclassification, and consider the implications for vital statistics. Hospital deaths assigned to causes classified as garbage code (GC) COVID-related cases (severe acute respiratory syndrome, pneumonia unspecified, sepsis, respiratory failure and ill-defined causes) were selected in three Brazilian state capitals. Data from medical charts and forensic reports were extracted from standard forms and analyzed by study physicians who re-assigned the underlying cause based on standardized criteria. Descriptive statistical analysis was performed and the potential impact in vital statistics in the country was also evaluated. Among 1,365 investigated deaths due to GC-COVID-related causes, COVID-19 was detected in 17.3% in the age group 0-59 years and 25.5% deaths in 60 years and over. These GCs rose substantially in 2020 in the country and were responsible for 211,611 registered deaths. Applying observed proportions by age, location and specific GC-COVID-related cause to national data, there would be an increase of 37,163 cases in the total of COVID-19 deaths, higher in the elderly. In conclusion, important undercount of deaths from COVID-19 among GC-COVID-related causes was detected in three selected capitals of Brazil. After extrapolating the study results for national GC-COVID-related deaths we infer that the burden of COVID-19 disease in Brazil in official vital statistics was probably under estimated by at least 18% in the country in 2020.

Excess Mortality due to natural causes among whites and blacks during the COVID-19 pandemic in Brazil

Abstract INTRODUCTION: Excess Mortality by all causes considers deaths directly related to COVID-19 and those attributed to conditions caused by the pandemic. When stratified by social dimensions, such as race/color, it allows for the evaluation of more vulnerable populations. The study estimated the excess mortality by natural causes, separating the white and black populations in 2020. METHODS Public civil registration data on deaths observed in 2020, corrected for under registration, were used. The expected number of deaths was estimated based on the mortality rates observed in 2019, applied to the estimated population in 2020. The difference between the values expected and observed and the proportion of excess was considered the excess mortality. RESULTS: The present study found an excess of 270,321 deaths (22.2% above the expected) in 2020. Every state of Brazil reported deaths above the corresponding expected figure. The excess was higher for men (25.2%) than for women (19.0%). Blacks showed an excess of 27.8%, as compared to whites at 17.6%. In both sexes and all age groups, excess was higher in the black population, especially in the South, Southeast, and Midwest regions. São Paulo, the largest in population number, had twice as much excess death in the black population (25.1%) than in the white population (11.5%). CONCLUSIONS: The present study showed racial disparities in excess mortality during the COVID-19 pandemic in Brazil. The higher excess found for the black suggests an intrinsic relationship with the socioeconomic situation, further exposing the Brazilian reality, in which social and structural inequality is evident.

Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017.

OBJECTIVE: To generate estimates of mortality rates due to garbage codes (GC) for Brazilian municipalities by comparing the direct and the Bayesian methods, based on deaths registered in the Mortality Information System (SIM) between 2015 and 2017. METHODS: Data from the SIM were used. The analysis was performed in groups of GC levels 1 and 2, levels 3 and 4, and total GC. Mortality rates were estimated directly and also according to the Bayesian method by applying the Empirical Bayesian Estimator. RESULTS: About 38% of GC were estimated and regional differences in mortality rates were observed, higher in the Northeast and Southeast and lower in the South and Midwest regions. The Southeast presented similar rates for the two analyzed groups of GC. The smallest differences between direct and Bayesian method estimates were observed in large cities with a population over 500 thousand inhabitants. Municipalities in the north of the state of Minas Gerais and those in the states of Rio de Janeiro, São Paulo, and Bahia presented high rates at levels 1 and 2. CONCLUSION: There are differences in the quality of the definition of the underlying causes of death, even with the use of Bayesian methodology, which assists in smoothing the rates. The quality of the definition of causes of death is important, as they are associated with the access to and quality of healthcare services and support health planning.

Methodological proposal for the redistribution of deaths due to garbage codes in mortality estimates for Noncommunicable Chronic Diseases.

OBJECTIVE: To propose a method for improving mortality estimates from noncommunicable diseases (NCD), including the redistribution of garbage codes in Brazilian municipalities. METHODS: Brazilian Mortality Information System (MIS) was used as a data source to estimate age standardized mortality rates, before and after correction, for NCD (cardiovascular, chronic respiratory, diabetes, and neoplasms). The treatment for the correction of data addressed missing data, under-registration, and redistribution of garbage codes (GCs). Three-year periods 2010-2012 and 2015-2017, and the Bayesian method were used to estimate mortality rates, reducing the effect of fluctuation caused by small numbers at the municipal level. RESULTS: GCs redistribution step showed greater weight in corrections, about 40% in 2000 and roughly 20% as from 2007, with stabilization starting in this year. Throughout the historical series, the quality of information on causes of death has improved in Brazil, with heterogeneous results being observed among municipalities. CONCLUSION: Methodological studies that propose correction and improvement of the MIS are essential for monitoring mortality rates due to NCD at regional levels. The methodological proposal applied, for the first time in real data from Brazilian municipalities, is challenging and deserves further improvements. Improving the quality of the data is essential in order to build more accurate estimates based on the raw data from the SIM.

Covid Adult Mortality in Brazil: An Analysis of Multiple Causes of Death.

Objective: This study aimed to analyze the chain of events and contributing causes associated with COVID-19 adult mortality (30-69 years old), based on qualified data on CoD from three Brazilian capitals cities, Belo Horizonte, Salvador, and Natal, in 2020. Methods: Data of all deaths among residents in the three capitals in 2020 were provided by these municipalities' routine Mortality Information System (SIM). Mentions B34.2 with the markers U07.1 and U07.2 in the death certificate identified COVID-19 deaths. We used a multiple-cause-of-death approach better to understand the complexity of the morbid process of COVID-19. Conditions that appeared more frequently in the same line or above the COVID-19 mentions in the death certificate were considered a chain-of-event. Conditions that occurred more often after the codes for COVID-19 were considered as contributing. Results: In 2020, 7,029 records from COVID-19 as the underlying cause of death were registered in SIM in the three capitals. Among these, 2,921 (41.6%) were deceased between 30 and 69 years old, representing 17.0% of deaths in this age group. As chain-of-events, the most frequent conditions mentioned were sepsis (33.4%), SARS (32.0%), acute respiratory failure (31.9%), unspecified lower respiratory infections (unspecified pneumonia) (20.1%), and other specified respiratory disorders (14.1%). Hypertension (33.3%), diabetes unspecified type (21.7%), renal failure (12.7%), obesity (9.8%), other chronic kidney diseases (4.9%), and diabetes mellitus type 2 (4.7%) were the most frequent contributing conditions. On average, 3.04 conditions were mentioned in the death certificate besides COVID-19. This average varied according to age, place of death, and capital. Conclusion: The multiple-cause analysis is a powerful tool to better understand the morbid process due to COVID-19 and highlight the importance of chronic non-communicable diseases as contributing conditions.

Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017 / Mortalidade por causas garbage nos municípios brasileiros: diferenças nas estimativas de taxas pelos métodos direto e Bayesiano de 2015 a 2017

ABSTRACT: Objective: To generate estimates of mortality rates due to garbage codes (GC) for Brazilian municipalities by comparing the direct and the Bayesian methods, based on deaths registered in the Mortality Information System (SIM) between 2015 and 2017. Methods: Data from the SIM were used. The analysis was performed in groups of GC levels 1 and 2, levels 3 and 4, and total GC. Mortality rates were estimated directly and also according to the Bayesian method by applying the Empirical Bayesian Estimator. Results: About 38% of GC were estimated and regional differences in mortality rates were observed, higher in the Northeast and Southeast and lower in the South and Midwest regions. The Southeast presented similar rates for the two analyzed groups of GC. The smallest differences between direct and Bayesian method estimates were observed in large cities with a population over 500 thousand inhabitants. Municipalities in the north of the state of Minas Gerais and those in the states of Rio de Janeiro, São Paulo, and Bahia presented high rates at levels 1 and 2. Conclusion: There are differences in the quality of the definition of the underlying causes of death, even with the use of Bayesian methodology, which assists in smoothing the rates. The quality of the definition of causes of death is important, as they are associated with the access to and quality of healthcare services and support health planning.

RESUMO: Objetivo: Gerar estimativas das taxas de mortalidade por causas garbage (CG) para os municípios do Brasil, fazendo a comparação entre o método direto e o Bayesiano, tendo como base os óbitos registrados no Sistema de Informações sobre Mortalidade (SIM) entre 2015 e 2017. Métodos: Os dados do SIM foram utilizados. A análise foi realizada com grupos de CG níveis 1 e 2, 3 e 4 e total de CG. As taxas de mortalidade foram estimadas de forma direta e bayesiana, aplicando o estimador Bayesianos Empírico Local. Resultados: Observaram-se 38% de CG e diferenças regionais nas taxas de mortalidade, maiores no Nordeste e Sudeste e menores no Sul e Centro-Oeste. O Sudeste apresentou taxas semelhantes para os dois grupos de CG analisados. As menores diferenças entre as estimativas diretas e bayesianas foram verificadas nas grandes cidades, acima de 500 mil habitantes. O norte de Minas Gerais e os estados do Rio de Janeiro, de São Paulo e da Bahia apresentaram municípios com altas taxas nos níveis 1 e 2. Conclusão: Existem diferenças na qualidade da definição das causas básicas de morte, mesmo com o uso de metodologia bayesiana, que auxilia na suavização das taxas. A qualidade da definição das causas de morte é importante, uma vez que se mostra associada ao acesso e à qualidade dos serviços de saúde e oferecem subsídios para o planejamento em saúde.

Methodological proposal for the redistribution of deaths due to garbage codes in mortality estimates for Noncommunicable Chronic Diseases / Proposta metodológica para redistribuição de óbitos por causas garbage nas estimativas de mortalidade para doenças crônicas não transmissíveis

ABSTRACT: Objective: To propose a method for improving mortality estimates from noncommunicable diseases (NCD), including the redistribution of garbage codes in Brazilian municipalities. Methods: Brazilian Mortality Information System (MIS) was used as a data source to estimate age standardized mortality rates, before and after correction, for NCD (cardiovascular, chronic respiratory, diabetes, and neoplasms). The treatment for the correction of data addressed missing data, under-registration, and redistribution of garbage codes (GCs). Three-year periods 2010-2012 and 2015-2017, and the Bayesian method were used to estimate mortality rates, reducing the effect of fluctuation caused by small numbers at the municipal level. Results: GCs redistribution step showed greater weight in corrections, about 40% in 2000 and roughly 20% as from 2007, with stabilization starting in this year. Throughout the historical series, the quality of information on causes of death has improved in Brazil, with heterogeneous results being observed among municipalities. Conclusion: Methodological studies that propose correction and improvement of the MIS are essential for monitoring mortality rates due to NCD at regional levels. The methodological proposal applied, for the first time in real data from Brazilian municipalities, is challenging and deserves further improvements. Improving the quality of the data is essential in order to build more accurate estimates based on the raw data from the SIM.

RESUMO: Objetivo: Propor método para melhoria das estimativas de mortalidade por doenças crônicas não transmissíveis, incluindo a redistribuição de causas garbage nos municípios brasileiros. Métodos: O Sistema de Informações sobre Mortalidade foi utilizado como fonte de dados para estimar as taxas padronizadas por idade, antes e depois da correção de dados, para as doenças crônicas não transmissíveis (cardiovasculares, respiratórias crônicas, diabetes e neoplasias). O tratamento para correção dos dados abordou dados faltantes, sub-registro e redistribuição de causas garbage. Foram utilizados os triênios 2010-2012 e 2015-2017 e o método bayesiano para estimar as taxas de mortalidade, diminuindo-se o efeito da flutuação provocada pelos pequenos números no nível municipal. Resultados: A etapa de redistribuição causas garbage mostrou maior peso nas correções: cerca de 40% em 2000 e aproximadamente 20% a partir de 2007, com estabilização neste ano. Ao longo da série histórica, a qualidade da informação sobre causas de morte melhorou no Brasil, sendo vistos resultados heterogêneos nos municípios. Observaram-se clusters com as maiores proporções de correção nas regiões Nordeste e Norte. O diabetes foi a causa com maior proporção de acréscimo (mais de 40%, em 2000). Conclusão: Estudos metodológicos que propõem correção e melhoria do Sistema de Informação sobre Mortalidade são essenciais para o monitoramento das taxas de mortalidade por doenças crônicas não transmissíveis em níveis regionais. A proposta metodológica aplicada, pela primeira vez em dados reais de municípios brasileiros, é desafiadora e merece aprimoramentos. Apesar da melhora nos dados, o método utilizado neste estudo para tratamento dos dados brutos mostrou grande impacto nas estimativas finais.

Changes in the quality of cause-of-death statistics in Brazil: garbage codes among registered deaths in 1996-2016.

BACKGROUND: Registered causes in vital statistics classified as garbage codes (GC) are considered indicators of quality of cause-of-death data. Our aim was to describe temporal changes in this quality in Brazil, and the leading GCs according to levels assembled for the Global Burden of Disease (GBD) study. We also assessed socioeconomic differences in the burden of different levels of GCs at a regional level. METHODS: We extracted data from the Brazilian Mortality Information System from 1996 to 2016. All three- and four-digit ICD-10 codes considered GC were selected and classified into four categories, according to the GBD study proposal. GC levels 1 and 2 are the most damaging unusable codes, or major GCs. Proportionate distribution of deaths by GC levels according selected variables were performed. Age-standardized mortality rates after correction of underreporting of deaths were calculated to investigate temporal relationships as was the linear association adjusted for completeness between GC rates in states and the Sociodemographic Index (SDI) from the GBD study, for 1996-2005 and 2006-2016. We classified Brazilian states into three classes of development by applying tertiles cutoffs in the SDI state-level estimates. RESULTS: Age-standardized mortality rates due to GCs in Brazil decreased from 1996 to 2016, particularly level 1 GCs. The most important GC groups were ill-defined causes (level 1) in 1996, and pneumonia unspecified (level 4) in 2016. At state level, there was a significant inverse association between SDI and the rate of level 1-2 GCs in 1996-2005, but both SDI and completeness had a non-expected significant direct association with levels 3-4. In 2006-2016, states with higher SDIs tended to have lower rates of all types of GCs. Mortality rates due to major GCs decreased in all three SDI classes in 1996-2016, but GC levels 3-4 decreased only in the high SDI category. States classified in the low or medium SDI groups were responsible for the most important decline of major GCs. CONCLUSION: Occurrence of major GCs are associated with socioeconomic determinants over time in Brazil. Their reduction with decreasing disparity in rates between socioeconomic groups indicates progress in reducing inequalities and strengthening cause-of-death statistics in the country.

The importance of surveillance in cases of and mortality from the COVID-19 epidemic in Belo Horizonte, Brazil, 2020. / A importância da vigilância de casos e óbitos e a epidemia da COVID-19 em Belo Horizonte, 2020.

OBJECTIVES: This study aims to describe the actions carried out by the epidemiological surveillance system in Belo Horizonte to address the COVID-19 epidemic and the timeless of the data for detecting transmission in 2020. METHODS: The sources of information used by the epidemiological surveillance of the municipality for COVID-19 were identified and the temporal distribution and interval for detection of confirmed cases of the disease were analyzed. RESULTS: The city's epidemiological surveillance uses outpatient, hospital, public and private laboratory notifications as data sources. For reporting COVID-19 cases in official information systems, there is also an active search of laboratory results linked to suspected deaths investigated. From January to April 2020, 1,449 hospitalized cases of COVID-19 were reported, the first case being detected in late February 2020. Of the total 1,025 laboratory samples of cases hospitalized after the 8th epidemiological week, 87 (8.5%) of COVID-19 cases were confirmed. The median time between the onset of symptoms and the release of laboratory results was 12 days for the analyzed period. CONCLUSION: Epidemiological surveillance uses several data sources to monitor and analyze the transmission of COVID-19. The timeliness of this system to detect cases of the disease is compromised by the delay in the release of laboratory results, which has been a considerable challenge for adequate surveillance.

The importance of surveillance in cases and mortality from COVID-19 epidemic in Belo Horizonte, 2020 / A importância da vigilância de casos e óbitos e a epidemia da COVID-19 em Belo Horizonte, 2020

Objectives: This study aims to describe the actions carried out by the epidemiological surveillance system in Belo Horizonte to address the COVID-19 epidemic and the timeless of the data for detecting transmission in 2020. Methods: The sources of information used by the epidemiological surveillance of the municipality for COVID-19 were identified and the temporal distribution and interval for detection of confirmed cases of the disease were analyzed. Results: The city's epidemiological surveillance uses outpatient, hospital, public and private laboratory notifications as data sources. For reporting COVID-19 cases in official information systems, there is also an active search of laboratory results linked to suspected deaths investigated. From January to April 2020, 1,449 hospitalized cases of COVID-19 were reported, the first case being detected in late February 2020. Of the total 1,025 laboratory samples of cases hospitalized after the 8th epidemiological week, 87 (8.5%) of COVID-19 cases were confirmed. The median time between the onset of symptoms and the release of laboratory results was 12 days for the analyzed period. Conclusion: Epidemiological surveillance uses several data sources to monitor and analyze the transmission of COVID-19. The timeliness of this system to detect cases of the disease is compromised by the delay in the release of laboratory results, which has been a considerable challenge for adequate surveillance.

Objetivos: Descrever as ações realizadas pela vigilância epidemiológica da Secretaria Municipal de Saúde de Belo Horizonte para enfrentamento da epidemia de COVID-19 e avaliar a oportunidade para detecção precoce da transmissão da doença durante o período compreendido entre 1 de janeiro a 24 de abril de 2020. Métodos: Foram identificadas as fontes de informação utilizadas pela vigilância epidemiológica do município para a COVID-19 e analisadas a distribuição temporal e oportunidade para detecção dos casos confirmados da doença. Resultados: A vigilância epidemiológica do município utiliza fontes de notificações ambulatoriais, hospitalares, de laboratórios públicos e privados, além de busca ativa com cruzamento de dados laboratoriais na investigação de óbitos suspeitos, sendo os casos confirmados de COVID-19 informados em sistemas de informação oficiais. Foram notificados 1.449 casos internados, sendo o primeiro caso detectado no final de fevereiro de 2020. Do total de 1.025 amostras laboratoriais de casos internados após a semana epidemiológica 8, foram confirmados 87 casos (8,5%) por COVID-19. A mediana de tempo entre o início dos sintomas e liberação dos resultados laboratoriais foi de 12 dias. Conclusão: A vigilância epidemiológica utiliza várias fontes de dados para monitoramento e análise da transmissão da COVID-19. A oportunidade para detecção de casos da doença está comprometida pela demora na liberação dos resultados laboratoriais, sendo um desafio para a vigilância.

Improving the usefulness of mortality data: reclassification of ill-defined causes based on medical records and home interviews in Brazil.

INTRODUCTION: Brazil presented a high proportion of ill-defined causes of death (IDCD) in 2000, compromising accurate cause-of-death analysis. OBJECTIVE: To analyze specific underlying causes for deaths originally assigned as IDCD in the Mortality Information System (SIM - Sistema de Informação sobre Mortalidade), after investigation activities implemented in country between 2006 and 2017. METHOD: For all IDCD identified in the SIM, municipal health professionals collected information about the final disease obtained from hospital records, autopsies, forms of family health teams, and home investigation. Specific causes among reclassified IDCD after investigation were evaluated according to age groups and four calendar periods. RESULTS: Proportions of IDCD reassigned to other causes after review increased over time, reaching 30.1% in 2017. From a total of 257,367 IDCD reclassified in 2006-2017, neonatal-related conditions, injury, ischemic heart disease and stroke were the leading causes detected in the age groups 0-9 years, 10-29 years, 30-69 years, 70 years and over, respectively. DISCUSSION: The similarity and plausibility of cause-specific proportions derived from the reclassification of IDCD by age group over time indicate the accuracy of the investigation data. CONCLUSION: High proportions of IDCD reassigned to more informative causes after review indicate the success of this approach to correct misclassification in the SIM, an initiative that should be maintained. Training physicians on death certification along with better quality of medical care and access to health services would lead to further improvement.

Improvement of the unspecified external causes classification based on the investigation of death in Brazil in 2017. / Melhoria da classificação das causas externas inespecíficas de mortalidade baseada na investigação do óbito no Brasil em 2017.

BACKGROUND: Unspecified causes of death are among the traditional indicators of quality of information. OBJECTIVE: To verify the performance of the 60 cities in the Data for Health Initiative project and to analyze the reclassification of unspecified external causes of death (UEC). METHODS: Using the 2017 records from the Mortality Information System, the proportion and percent change in UEC were compared after investigation between project cities and other cities, and the percent of reclassification to specific external causes was calculated. RESULTS: The project cities comprised 52% (n = 11,759) of the total UEC in Brazil, of which 64.5% were reclassified after investigation, whereas the other cities reclassified 31% of UEC. Results were similar for men, youth, blacks, metropolitan cities, the Southeast region, and deaths attested by forensic institutes. In the project cities, pedestrian traffic accidents were external causes with greater reclassification. In men, the UEC was reclassified to homicides (23.8%) and accident of terrestrial transportation (ATT) (11.1%), with motorcyclists (4.4%) and pedestrians (4.3%) being the most prominent. In women, these causes were changed to other accident causes (20.8%), ATT (10.6%) and homicides (7.9%). UEC changed to ATT (18.3%) in the age groups of 0-14 years old and to homicides (32.5%) in the age groups of 15-44 years. CONCLUSION: The project cities obtained better results after investigation of UEC, enabling analysis of the reclassification to specific causes by sex and age groups.

INTRODUÇÃO: Causas inespecíficas de mortalidade estão entre os indicadores tradicionais de qualidade da informação. OBJETIVO: Verificar o desempenho das 60 cidades do projeto Dados para a Saúde e analisar a reclassificação das causas externas inespecíficas de mortalidade (CEI). MÉTODOS: A partir de registros de 2017 do Sistema de Informações sobre Mortalidade, comparou-se proporções e variações percentuais após investigação das CEI, entre cidades do projeto e demais cidades, e calculou-se percentual de reclassificação para causas específicas. RESULTADOS: As cidades do projeto concentraram 52% (n = 11.759) das CEI do Brasil, das quais 64,5% foram reclassificadas após investigação, enquanto as demais cidades reclassificaram 31%. Resultados foram semelhantes para homens, jovens, negros, cidades metropolitanas, região Sudeste, e em eventos atestados por institutos forenses. Nas cidades do projeto, acidentes de pedestres foram causas com maior reclassificação. Em homens, as CEI migraram para homicídios (23,8%) e acidentes de transporte terrestre (ATT) (11,1%), com destaque para motociclistas (4,4%) e pedestres (4,3%). Em mulheres, essas causas foram alteradas para outras causas acidentais (20,8%), ATT (10,6%) e homicídios (7,9%). CEI migraram para ATT (18,3%) no grupo de idade de 0 a 14 anos, e homicídios (32,5%) no grupo de 15 a 44 anos. CONCLUSÃO: As cidades do projeto obtiveram melhores resultados após investigação de CEI, possibilitando analisar a reclassificação para causas específicas, por sexo e faixas etárias.

Deaths from sepsis: underlying causes of death after investigation in 60 Brazilian municipalities in 2017. / Mortes por sepse: causas básicas do óbito após investigação em 60 municípios do Brasil em 2017.

INTRODUCTION: Sepsis represents the occurrence of systemic inflammatory response syndrome triggered by the initial infection of an organ or system. When sepsis is certified as the cause of death, the first diagnosis is lost, leading to inaccurate information as to its origin. OBJECTIVE: To analyze the underlying causes of death from sepsis after investigation in 60 Brazilian municipalities in 2017. METHODOLOGY: All deaths recorded in the Mortality Information System (SIM) as sepsis in 2017 were selected, and the proportions of reclassified deaths were calculated based on the results of research conducted in hospitals and other health services. RESULTS: Of the 6,486 deaths from sepsis that occurred in the 60 municipalities, 1,584 (24.4%) were investigated, and of these, 1,308 (82.6%) were reclassified with other underlying causes. Individuals aged from 70 to 89 years old showed the highest concentration in the records, with 49.3% of cases. More than 60% of the deaths from sepsis reclassified after the investigation had chronic non-communicable diseases as underlying causes (65.6%), with diabetes being the most common specific cause in this group. Communicable diseases (9.6%) and external causes (5.6%) such as falls were also detected as underlying causes. CONCLUSION: The investigation of deaths from sepsis made it possible to identify the true causes of death and the proportions of reclassification. This information will improve the quality of mortality data and support the planning of public health actions in Brazil.

INTRODUÇÃO: A sepse representa a ocorrência de síndrome de resposta inflamatória sistêmica desencadeada por infecção inicial de um órgão ou sistema. Quando a sepse é atestada como causa do óbito, perde-se o primo diagnóstico, condicionando perda de informação quanto à sua origem. OBJETIVO: Analisar as causas básicas após investigação de óbitos por sepse em 60 municípios do Brasil em 2017. METODOLOGIA: Foram selecionados todos os óbitos registrados em 2017 no Sistema de Informação sobre Mortalidade como sepse, e analisadas as proporções dos óbitos reclassificados após investigação em hospitais e outros serviços de saúde. RESULTADOS: Entre os 6.486 óbitos por sepse ocorridos nos 60 municípios foram investigados 1.584 (24,4%) e, destes, 1.308 (82,6%) foram reclassificados com outras causas básicas. A faixa etária de 70 a 89 anos obteve a maior concentração de registros, com 49,3% dos casos. Mais de 60% dos óbitos por sepse reclassificados após investigação tiveram doenças crônicas não transmissíveis como causa básica (65,6%), sendo a diabetes a causa específica mais comum neste grupamento. Doenças transmissíveis (9,6%) e causas externas (5,6%) como quedas foram também detectadas como causas básicas. CONCLUSÃO: A partir das investigações dos óbitos por sepses foi possível conhecer a verdadeira causa de morte e as proporções de reclassificação. Essas informações contribuirão para melhorar a qualidade dos dados de mortalidade e para subsidiar o planejamento de ações em saúde pública no Brasil.

Profile of deaths from unspecified stroke after investigation of garbage codes in 60 cities in Brazil, 2017. / Perfil dos óbitos por acidente vascular cerebral não especificado após investigação de códigos garbage em 60 cidades do Brasil, 2017.

INTRODUCTION: Unspecified stroke (UnST) is of great importance in mortality statistics, as it is the fourth leading cause of death in Brazil. The objective of this study was to identify the profile of reclassified causes of death after investigation of deaths caused by UnST in Brazil. METHODS: All deaths registered as UnST in 2017 in the Mortality Information System (SIM) were considered as garbage codes. The specific causes, detected after investigation in 60 selected cities, were analyzed by age and sex. RESULTS: Of the total deaths due to UnST identified in these 60 cities (n = 11,289), 25.8% were investigated. Of these, 56.3% were reclassified to ischemic stroke, 12.7% to hemorrhagic stroke, and 23.3% to other specific causes, such as diabetes and chronic kidney disease, in both sexes. DISCUSSION: The higher proportion of deaths due to ischemic stroke in comparison to hemorrhagic stroke was expected. However, the detection of other specific causes outside the stroke group indicates possible quality problems in the filling of death certificate (DC). CONCLUSION: The investigations allowed the identification of subgroups of deaths due to stroke. In addition to the research, however, it is important to conduct physician training in the adequate filling in of the DC, in order to improve estimates of specific stroke mortality, and to enable appropriate targeting of health actions and services.

INTRODUÇÃO: O acidente vascular cerebral não especificado (AVC-NE) é de grande relevância nas estatísticas de mortalidade, sendo a quarta maior causa de morte no Brasil. O objetivo deste estudo foi identificar o perfil de causas reclassificadas após investigação de óbitos por AVC-NE no Brasil. MÉTODOS: Foram selecionados todos os óbitos registrados em 2017 no Sistema de Informação sobre Mortalidade (SIM) como AVC-NE, considerados códigos garbage. As causas específicas, detectadas após investigação em 60 cidades selecionadas, foram analisadas segundo idade e sexo. RESULTADOS: Do total de óbitos por AVC-NE das 60 cidades (n = 11.289), foram investigados 25,8%, dos quais 56,3% foram reclassificados para AVC isquêmico, 12,7% para AVC hemorrágico, e 23,3% migraram para outras causas específicas, como diabetes e doença renal crônica, em ambos os sexos. DISCUSSÃO: A maior proporção de reclassificação dos óbitos por AVC-NE para AVC isquêmico em relação ao hemorrágico era esperada. No entanto, a detecção de outras causas específicas fora do grupo de AVC indica possíveis problemas de qualidade do preenchimento das causas na declaração de óbito (DO). CONCLUSÃO: As investigações realizadas permitiram identificação de subgrupos de AVC. Além da investigação, entretanto, é importante realizar capacitação com médicos para o preenchimento adequado da DO, a fim de melhorar as estimativas da mortalidade por AVC específico e possibilitar direcionamento adequado das ações e dos serviços de saúde.

Evaluation of a smartphone application to improve medical certification of the cause of death. / Avaliação de um aplicativo para smartphone para aprimoramento da certificação médica da causa da morte.

INTRODUCTION: A smartphone application named AtestaDO was developed to support physicians with medical certification of the cause of death. The objective of this study is to evaluate the acceptability of the app. METHODS: Physicians were invited to attend meetings on the proper certification of cause of death, and to evaluate the application in a national workshop in Natal (first stage) and in two large hospitals in Belo Horizonte (second and third stages). RESULTS: In Natal, 82% of 38 physicians had more than 20 years of experience and in Belo Horizonte, more than 67% of 58 physicians had less than 5 years of experience. The sections "Application interface", "How to certify the causes of death", "Practice with exercises" and "Other information for physicians" were positively evaluated by more than 50% of physicians in Belo Horizonte. In Natal, all sections were positively evaluated by at least 80% of participants. More than 70% of the participants in both Natal and the second stage of Belo Horizonte indicated they would possibly use AtestaDO to guide filling of a death certificate. The probability of using AtestaDO to teach classes on filling death certificates was 83.3% for Natal's physicians but less than 60% in Belo Horizonte. In the three stages, most physicians would recommend using the application to other colleagues. CONCLUSION: The evaluation of AtestaDO showed good acceptability. We expect that the use of this tool enables improvements in medical certification of causes of death.

INTRODUÇÃO: O aplicativo para smartphone AtestaDO foi desenvolvido para auxiliar o médico na certificação da causa de morte. Neste estudo se propõe avaliar a aceitabilidade desse aplicativo. MÉTODOS: Médicos foram convidados para participar de reuniões sobre certificação correta da causa da morte e avaliar o aplicativo em três etapas dessas reuniões, realizadas em Natal e em dois grandes hospitais de Belo Horizonte. RESULTADOS: Em Natal, 82% dos 38 médicos participantes tinham mais de 20 anos de graduação, e em Belo Horizonte, mais de 67% dos 58 médicos tinham menos de 5 anos de graduação. As seções "Interface do aplicativo", "Como atestar as causas de morte", "Prática com exercícios" e "Outras informações para o médico" foram bem avaliadas por mais de 50% dos médicos de Belo Horizonte. Em Natal, todas as seções foram bem avaliadas por pelo menos 80% dos médicos. Mais de 70% dos participantes de Natal e da segunda etapa de Belo Horizonte usariam o aplicativo para preencher a causa de morte. A probabilidade de usar o AtestaDO para dar aulas sobre preenchimento da Declaração de Óbito foi de 83% para médicos de Natal, mas inferior a 60% em Belo Horizonte. Nas três etapas, a maioria dos médicos recomendaria o uso do aplicativo para outros colegas. CONCLUSÃO: A avaliação do aplicativo AtestaDO mostrou boa aceitabilidade. Espera-se que o uso dessa ferramenta permita alcançar melhorias na certificação médica da causa do óbito.

Quality of cause-of-death data in Brazil: Garbage codes among registered deaths in 2000 and 2015.

INTRODUCTION: reliability of mortality data is essential for health assessment and planning. In Brazil, a high proportion of deaths is attributed to causes that should not be considered as underlying causes of deaths, named garbage codes (GC). To tackle this issue, in 2005, the Brazilian Ministry of Health (MoH) implements the investigation of GC-R codes (codes from chapter 18 "Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified, ICD-10") to improve the quality of cause-of-death data. This study analyzes the GC cause of death, considered as the indicator of data quality, in Brazil, regions, states and municipalities in 2000 and 2015. METHODS: death records from the Brazilian Mortality Information System (SIM) were used. Analysis was performed for two GC groups: R codes and non-R codes, such as J18.0-J18.9 (Pneumonia unspecified). Crude and age-standardized rates, number of deaths and proportions were considered. RESULTS: an overall improvement in the quality of mortality data in 2015 was detected, with variations among regions, age groups and size of municipalities. The improvement in the quality of mortality data in the Northeastern and Northern regions for GC-R codes is emphasized. Higher GC rates were observed among the older adults (60+ years old). The differences among the areas observed in 2015 were smaller. CONCLUSION: the efforts of the MoH in implementing the investigation of GC-R codes have contributed to the progress of data quality. Investment is still necessary to improve the quality of cause-of-death statistics.