Série temporal da dinâmica do sistema de saúde para o diagnóstico de tuberculose em uma região metropolitana do nordeste brasileiro (2010-2020)

Objetivo: Analisar a dinâmica do sistema de saúde para o diagnóstico de tuberculose em região metropolitana de um estado do nordeste brasileiro. Métodos: Estudo ecológico de série temporal realizado em São Luís, no Estado do Maranhão, região Nordeste do Brasil. A população do estudo foi composta casos de tuberculose notificados noSistema de Informação de Agravos de Notificação (SINAN) no período de 2010 a 2020. A estatística descritiva dos casos foi realizada utilizando medidas de frequência absoluta e relativa e o teste Qui–quadrado de Pearson foi utilizado para comparar as frequências entre os casos notificados em unidades de Atenção Primária a Saúde (APS) e hospitalares e a caracterização sociodemográfica e clínica. Para análise da série temporal, recorreu-se ao modelo deautorregressão Prais–Winsten, seguido do método de decomposição denominado Seasonal–Trend using Loess (STL), finalizando com a previsão da tendência temporal para os próximos anos. Os dados foram analisados utilizando os recursos do software Stata versão 17 (StataCorp, College Station, TX, USA) e R versão 3.5.2 (R Core Team, 2020). Resultados: Foram notificados 7.948 casos com diagnóstico de tuberculose, sendo 1.608 notificados em unidadesde Atenção Primária e 6.340 em unidades Hospitalares. O teste Qui–quadrado resultou na frequência relativa calculada considerando o total de paciente que possuíam resultados de cada exame com diferenças estatisticamente significantes (p < 0,05). Conclusão: Foi possível observar tendência temporal diferenciada entre o diagnóstico realizado pela APS e hospitais. Na análise e modelagem temporal houve aumento nos casos notificados na APS e estacionário nos hospitais, entretanto, na modelagem temporal houve redução do número de casos nos hospitais.Objective: To analyze the dynamics of the health system for the diagnosis of tuberculosis in a metropolitan region of a Northeast Brazilian state. Methods: Ecological time series study conducted in São Luís, Maranhão State, Northeast region of Brazil. The study population was composed of tuberculosis cases notified in the Notifiable Diseases Information System (SINAN) in the period from 2010 to 2020. The descriptive statistics of the cases was performed using absolute and relative frequency measures, and Pearson’s Chi-square test was used to compare thefrequencies between the cases notified in Primary Health Care (PHC) and hospital units and the sociodemographic and clinical characterization. For time series analysis, the Prais-Winsten autoregression model was used, followed by the decomposition method called Seasonal-Trend decomposition using LOESS (STL), ending with the time trend prediction for the next years. The data were analyzed using the resources of the computer programs named Stata, version 17 (StataCorp, College Station, TX, USA) and R, version 3.5.2 (R Core Team, 2020). Results: A total of 7,948 cases diagnosed with tuberculosis were notified, of which 1,608 were notified in Primary Care units and 6,340 in hospital units. The Chi-square test resulted in a relative frequency calculated considering the totalnumber of patients who had results from each examination with statistically significant differences (p < 0.05). Conclusion: It was possible to observe different time trends between diagnoses performed by PHC and hospitals. In the time analysis and modeling, there was an increase in cases notified in PHC and stationary in hospitals; however, in the time modeling, there was a reduction in the number of cases in hospitals

Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil

Background: A diagnosis of tuberculosis (TB) does not mean that the disease will be treated successfully, since death may occur even among those who are known to the health services. Here, we aimed to analyze patient survival time from the diagnosis of TB to death, precocious deaths, and associated factors in southern Brazil. Methods: We conducted a longitudinal study with patients who were diagnosed with TB and who died due to the disease between 2008 and 2015 in southern Brazil. The starting point for measuring survival time was the patient’s diagnosis date. Techniques for survival analysis were employed, including the Kaplan-Meier test and Cox’s regression. A mixed-effect model was applied for identifying the associated factors to precocious deaths. Hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (95% CI) were estimated. We defined p value <0.05 as statistically significant for all statistics applied. Results: One hundred forty-six patients were included in the survival analysis, observing a median survival time of 23.5 days. We observed that alcoholism (HR=1.55, 95% CI=1.04-2.30) and being male (HR=6.49, 95% CI=1.03-2.68) were associated with death. The chance of precocious death within 60 days was 10.48 times greater than the chance of early death within 30 days. Conclusion: Most of the deaths occurred within 2 months after the diagnosis, during the intensive phase of the treatment. The use of alcohol and gender were associated with death, revealing inequality between men and women. This study advanced knowledge regarding the vulnerability associated with mortality. These findings must be addressed to fill a gap in the care cascades for active TB and ensure equity in health.publishersversionpublishe

Modelo preditivo dos desfechos desfavoráveis da tuberculose multidroga-resistente

OBJETIVO: Analisar a tendência temporal, identificar os fatores relacionados e elaborar um modelo preditivo para os desfechos desfavoráveis do tratamento da tuberculose multidroga-resistente. MÉTODOS: Estudo de coorte retrospectiva com todos os casos diagnosticados com tuberculose multidroga-resistente entre os anos de 2006 e 2015 no estado de São Paulo. Os dados secundários foram provenientes do sistema estadual de notificações de casos de tuberculose, o TBWeb. Foi realizada a análise de tendência temporal dos desfechos de tratamento por meio da regressão de Prais-Winsten. Para verificar os fatores relacionados com os desfechos desfavoráveis (óbito com tuberculose como causa básica, abandono e falência do tratamento), foi empregada a regressão logística binária. Representações pictóricas dos fatores relacionados ao desfecho do tratamento e sua capacidade prognóstica foram elaboradas por meio de nomogramas. RESULTADOS: Tanto o abandono como o óbito tiveram tendência temporal estacionária, enquanto a falência apresentou tendência decrescente. Em relação aos fatores de risco para tais desfechos, utilizar drogas ilícitas dobrou as chances de abandono e óbito. Além disso, ser diagnosticado em unidades de urgência ou emergência ou durante internações hospitalares foi um fator de risco para o óbito. Ao contrário, ter feito tratamentos prévios da multidroga-resistência reduziu as chances dos desfechos analisados. O nomograma apresentou um modelo preditivo com precisão de 65% para os abandonos, 70% para os óbitos e 80% para a falência. CONCLUSÕES: A prevenção de desfechos desfavoráveis no tratamento da tuberculose multidroga-resistente implica a modificação do modelo de atenção vigente. Utilizando modelos preditivos, como o apresentado neste estudo, torna-se possível elaborar ações centradas nos pacientes, considerando seus fatores de risco e aumentando as chances de cura.OBJECTIVE: to analyze the temporal trend, identify the factors related and elaborate a predictive model for unfavorable treatment outcomes for multidrug-resistant tuberculosis (MDR-TB). METHODS: Retrospective cohort study with all cases diagnosed with MDR-TB between the years 2006 and 2015 in the state of São Paulo. The data were collected from the state system of TB cases notifications (TB-WEB). The temporal trend analyzes of treatment outcomes was performed through the Prais-Winsten analysis. In order to verify the factors related to the unfavorable outcomes, abandonment, death with basic cause TB and treatment failure, the binary logistic regression was used. Pictorial representations of the factors related to treatment outcome and their prognostic capacity through the nomogram were elaborated. RESULTS: Both abandonment and death have a constant temporal tendency, whereas the failure showed it as decreasing. Regarding the risk factors for such outcomes, using illicit drugs doubled the odds for abandonment and death. Besides that, being diagnosed in emergency units or during hospitalizations was a risk factor for death. On the contrary, having previous multidrug-resistant treatments reduced the odds for the analyzed outcomes by 33%. The nomogram presented a predictive model with 65% accuracy for dropouts, 70% for deaths and 80% for failure. CONCLUSIONS: The modification of the current model of care is an essential factor for the prevention of unfavorable outcomes. Through predictive models, as presented in this study, it is possible to develop patient-centered actions, considering their risk factors and increasing the chances for cure

Integrated health service delivery networks and tuberculosis avoidable hospitalizations: is there a relation between them in Brazil?

Abstract\ud \ud Background\ud The early identification of the Breathing Symptoms within the scope of Primary Health Care is recommended, and is also one of the strategies of national sanitary authorities for reaching the elimination of tuberculosis. The purpose of this study is to consider which attributes and which territories have shown the most significant progress in Primary Health Care, in terms of coordination of Health Care Networks, and also check if those areas of Primary Health Care that are most critical regarding coordination, there were more or less cases of avoidable hospitalizations for tuberculosis.\ud \ud \ud Methods\ud This is an ecological study that uses primary and secondary data. For analysis, coropletic maps were developed through the ArcGIS software, version 10.2. There was also the calculation of gross annual and Bayesian rates for hospitalizations for tuberculosis, for each Primary Health Care territory.\ud \ud \ud Results\ud There were satisfactory results for attributes such as Population (n = 37; 80.4 %), Primary Health Care (n = 43; 93.5 %), Support System (n = 45; 97.8 %); the exceptions were Logistics System (n = 32; 76.0 %) and Governance System, with fewer units in good condition (n = 31; 67.3 %). There is no evidence of any connection between networks’ coordination by Primary Health Care and tuberculosis avoidable admissions.\ud \ud \ud Conclusion\ud The results show that progress has been made regarding the coordination of the Health Care Networks, and a positive trend has been shown, even though the levels are not excellent. It was found no relationship between the critical areas of Primary Health Care and tuberculosis avoidable hospitalizations, possibly because other variables necessary to comprehend the phenomena.We are grateful to the Municipal Secretariat for Health, for the partnership\ud and support they have provided in the materialization of the study. We also\ud thank the coordinators of the Health Districts, for the articulation with the\ud managers of the Units and also as they have made it possible for us to\ud participate in the Ordinary General Meeting for the presentation of the\ud study. We thank the managers of the Health Units who have so kindly\ud opened the doors of their Units to our team, also encouraging the\ud participation of their employees. We thank the health workers for having\ud agreed to participate in the study, essentially as they have believed in the\ud potential of Primary Health Care for a change in model. Last but not least, to\ud the team from the Reference Hospital for making available the secondary\ud data. The Foundation of Support for Research of the State of São Paulo\ud (Fundação de Amparo e Apoio à Pesquisa do Estado de São Paulo - FAPESP)\ud (Processes No. 2012/51235-5 and No. 2013/22486-2)

Areas of Risk of Tuberculosis Deaths and their Relationship with Social Vulnerability in a Municipality of Northeastern Brazil

Introdução: A Tuberculose é a primeira causa de morte por doença infecciosa no mundo e sua relação direta com a pobreza somada a exclusão social além de outros fatores, fazem com que a doença perpetue como um problema de saúde pública existente há muito tempo. Portanto, objetivou-se investigar as áreas de risco para a mortalidade por TB e sua relação com a vulnerabilidade social em Natal - RN. Métodos: Estudo ecológico cujas unidades de análise foram os setores censitários. A população do estudo foi composta pelos casos de óbito por TB como causa básica registrados no Sistema de Informações sobre Mortalidade no período de 2008 a 2014. A análise das variáveis sociodemográficas foram realizadas software IBM SPSS Statistics 23.0, por meio de estatística descritiva dos parâmetros quantitativos com cálculo de frequências absolutas e relativas. A geocodificação dos endereços dos casos e das unidades de saúde foram realizadas através do software TerraView 4.2.2. Para identificar as áreas de alto ou baixo risco para a mortalidade por TB foi utilizada a técnica de estatística de varredura realizada através do software SaTScan 9.2. Com a finalidade de comparar as áreas de alto e baixo risco espacial, utilizou-se o Índice de Vulnerabilidade Social construído por Medeiros e, posteriormente, o Índice Moran Bivariado foi aplicado para verificar a relação do risco espacial de morrer por TB com o Índice de Vulnerabilidade Social. Todos os mapas temáticos foram construídos através do software ArcGis versão 10.5. Resultados: foram identificados 154 óbitos por TB sendo em sua maioria pessoas do sexo masculino, com idade entre 15 e 59 anos, raça/cor parda e estado civil solteiro. Foram geocodificados 96,6% dos casos de óbitos e dentre as unidades de saúde geocodificadas, a maioria deu-se no distrito Oeste. A técnica de análise de varredura espacial identificou três aglomerados estatisticamente significativos, sendo dois de alto risco (RR=5,77 IC95% = 5,19 - 6,34; RR= 3,82 IC95% = 3,38 - 4,24) e um de baixo risco (RR = 0,34 IC95% = 0,08 - 0,76). As áreas de alto risco para mortalidade por TB apresentaram predominantemente setores censitários classificados como vulnerabilidade social moderada. Quando analisada a associação das áreas de alto risco para a mortalidade por TB com domínios do IVS, o domínio estatisticamente significativo foi \"característica do entorno dos domicílios\" (I = 0,010; p = 0,001). Conclusão: A identificação de áreas de risco para a mortalidade por TB e compreender sua relação com a vulnerabilidade social permitem o direcionamento das ações intersetoriais de controle da doença às populações conhecidamente mais afetadasIntroduction: Tuberculosis is the leading cause of death due to infectious disease in the world and its direct relationship with poverty and social exclusion, as well as other factors, has perpetuated the disease as a longstanding public health problem. Therefore, the objective was to investigate the risk areas for TB mortality and its relationship with social vulnerability in Natal - RN. Methods: An ecological study whose units of analysis were the census tracts. The study population was composed of cases of death due to TB as a basic cause registered in the Mortality Information System from 2008 to 2014. The analysis of the sociodemographic variables was performed by IBM SPSS Statistics 23.0 software, using descriptive statistics of the quantitative parameters with calculation of absolute and relative frequencies. The geocoding of the addresses of the cases and the health units were performed using the TerraView 4.2.2 software. In order to identify areas of high or low risk for TB mortality, the scan statistic technique performed using the SaTScan 9.2 software was used. In order to compare areas of high and low spatial risk, the Social Vulnerability Index constructed by Medeiros was used and, later, the Moran Bivariate Index was applied to verify the spatial risk ratio of dying from TB with the Index of Social vulnerability. All thematic maps were built using ArcGis software version 10.5. Results: 154 deaths from TB were identified, mostly male, aged 15-59 years, race / color and single marital status. 96.6% of the cases of deaths were geocoded and of the geocoded health units, most of them occurred in the western district. The spatial sweep analysis technique identified three statistically significant clusters, two of which were high risk (RR = 5.77, 95% CI = 5.19 - 6.34, RR = 3.82, 95% CI = 3.38, 4.24 ) and one of low risk (RR = 0.34 95% CI = 0.08-0.76). The high risk areas for TB mortality presented predominantly census tracts classified as moderate social vulnerability. When the association of high-risk areas with TB mortality with IVS domains was analyzed, the statistically significant domain was \"characteristic of the household environment\" (I = 0.010, p = 0.001). Conclusion: The identification of risk areas for TB mortality and understanding their relationship with social vulnerability allows the targeting of intersectoral disease control actions to populations that are known to be most affecte

Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

Abstract Introduction The objective of this systematic review is to identify tuberculosis (TB) high-risk among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis. Methods The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar. Results A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot’s location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%). Conclusion There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB

Additional file 1 of Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

Additional file 1

Magnitude of social determinants in the risk of death from tuberculosis in Central-west Brazil

Objective: To evaluate the magnitude of social determinants in areas of risk of mortality due to tuberculosis in a high incidence city. Method: Ecological study, which recruited the cases of tuberculosis deaths registered between 2006 and 2016 in the capital of Mato Grosso-Brazil. The social determinants were obtained from the Human Development Units. Sweep statistics were used to identify areas of risk of mortality due to tuberculosis. Principal component analysis was carried out to identify dimensions of social determinants. Multiple logistic regression was applied to verify associations between the dimensions of social determinants and the risk of mortality from tuberculosis. A 5% error was fixed. The standard error was established at 5% for all statistical tests. Results: A total of 225 deaths due to tuberculosis were registered in the period, distributed heterogeneously in the space. A cluster of risk for tuberculosis mortality was identified, with RR = 2.09 (95%CI: 1.48-2.94; p = 0.04). Social determinants, low educational level and poverty were associated with the risk of mortality due to tuberculosis (OR: 2.92; 95%CI: 1.17-7.28). Income had a negative association with the risk of mortality due to tuberculosis (OR: 0.05; 95%CI: 0.00-0.70). The value of the ROC curve of the model was 92.1%. Conclusions: The results confirmed that the risk of mortality due to tuberculosis is a problem associated with social determinants. Health policies and social protection programmes can collaborate to address this problem.publishersversionpublishe

How do social-economic differences in urban areas affect tuberculosis mortality in a city in the tri-border region of Brazil, Paraguay and Argentina

Abstract Background The World Health Organization (WHO) launched the “End TB Strategy”, which aims to reduce tuberculosis (TB) mortality by 95% by 2035, Brazil has made a commitment to this, however, one challenge is achieving the goal in the border region, where the TB situation is more critical. The proposal was to analyse the spatial mortality due to TB and its socio-economic determinants in the general population, around the border areas of Brazil, Paraguay and Argentina, as well as the temporal trend in this region. Method This ecological study considered the cases of TB deaths of residents of Foz do Iguaçu (BR), with its units of analysis being the census sectors. The standardized mortality rate was calculated for each area. Socioeconomic variables data were obtained from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics (IBGE). The scan statistic was applied to calculate the spatial relative risk (RR), considering a 95% confidence interval (CI). Spatial dependence was analysed using the Global Bivariate Moran I and Local Bivariate Moran I (LISA) to test the relationship between the socioeconomic conditions of the urban areas and mortality from TB. Analysis of the temporal trend was also performed using the Prais-Winsten test. Results A total of 74 cases of TB death were identified, of which 53 (71.6%) were male and 51 (68.9%) people of white skin colour. The mortality rate ranged from 0.28 to 22.75 cases per 100,000 inhabitants. A spatial relative risk area was identified, RR = 5.07 (95% CI 1.79–14.30). Mortality was associated with: proportion of people of brown skin colour (I: 0.0440, p = 0.033), income (low income I: − 0.0611, p = 0.002; high income I: − 0.0449, p = 0.026) and density of residents (3 and 4 residents, I: 0.0537, p = 0.007; 10 or more residents, I: − 0.0390, p = 0.035). There was an increase in the mortality rate in people of brown skin colour (6.1%; 95% CI = 0.029, 0.093). Conclusion Death due to TB was associated with income, race resident density and social conditions. Although the TB mortality rate is stationary in the general population, it is increasing among people of brown skin colour