International Migration, Refugees, and Spread of Tuberculosis in Brazil: Analysis of Clusters, Trends, and Associated Factors (2010-2021).

BACKGROUND: International migration is a global phenomenon with significant implications on the health-disease process due to exposures along transit routes and local/destination epidemiological indicators. We aimed to analyze the transmission and spread of tuberculosis among international migrants and refugees from a spatiotemporal perspective and the associated factors. METHOD: This was an ecological study of cases of tuberculosis in international migrants in Brazil, between 2010 and 2021. Annual incidence rates were calculated and spatiotemporal scan techniques were used to identify municipalities at risk. Multiple logistic regression was used to identify factors associated with tuberculosis in international migrants. RESULTS: A total of 4037 cases of tuberculosis were reported in Brazil in international migrants. Municipalities at risk for this event were identified using the spatiotemporal scan technique, and a cluster was identified with ITT: +52.01% and ETT: +25.60%. A higher probability of TB infection was identified in municipalities with a TB incidence rate >14.40 cases/100 inhabitants, population >11,042 inhabitants, Gini index >0.49, and illiteracy rate >13.12%. A lower probability was found in municipalities with average per capita household income >BRL 456.43. CONCLUSIONS: It is recommended that health authorities implement monitoring and rigorous follow-up in affected areas to ensure proper diagnosis and treatment completion for international migrants, preventing disease spread to other communities.

Unsuccessful tuberculosis treatment outcomes across Brazil's geographical landscape before and during the COVID-19 pandemic: are we truly advancing toward the sustainable development/end TB goal?

BACKGROUND: Tuberculosis is one of the most significant infectious diseases for global public health. The reallocation of healthcare resources and the restrictions imposed by the COVID-19 pandemic have hindered access to TB diagnosis and treatment. Increases in unfavorable outcomes of the disease have been observed in Brazil. The objective of this study was to analyze the spatial distribution of unfavorable TB treatment outcomes in Brazil before and during the pandemic. METHODS: An ecological study with spatial analysis was conducted with all 5569 municipalities in Brazil. All reported cases of tuberculosis between January 2010 and December 2021, as well as reported cases of COVID-19 from February 2020 to December 2021, were included. The outcomes studied encompass loss to follow-up, drug-resistant tuberculosis, and death. The Getis Ord GI* technique was employed to assess spatial association, and the Kernel density estimator was used to identify areas with concentrated increases or decreases in outcomes. Bivariate Local Moran's I was used to examine the spatial association between outcomes and COVID-19 incidence. The study was approved by the Research Ethics Committee of Ribeirão Preto Nursing School, University of São Paulo. RESULTS: There were 134,394 cases of loss to follow-up, 10,270 cases of drug resistance, and 37,863 deaths. Clusters of high and low values were identified for all three outcomes, indicating significant changes in the spatial distribution patterns. Increases in concentrations were observed for lost to follow-up cases in the Southeast, while reductions occurred in the Northeast, South, and Midwest. Drug-resistant tuberculosis experienced an increase in the Southern and Southeastern regions and a decrease in the Northeast and South. TB-related deaths showed notable concentrations in the Midwest, Northeast, South, and Southeast. There was an increase in high occurrence clusters for deaths after 2020 and 2021 in the Northeast. CONCLUSIONS: The pandemic has brought additional challenges, emphasizing the importance of enhancing efforts and disease control strategies, prioritizing early identification, treatment adherence, and follow-up. This commitment is vital for achieving the goal of tuberculosis elimination.

Os determinantes das internações por tuberculose em Ribeirão Preto: uma abordagem geoecológica / Determinants of hospitalizations by tuberculosis in Ribeirão Preto: a geoecological approach

A tuberculose (TB) ainda se destaca como uma emergência global, apresentando elevada magnitude, transcendência e vulnerabilidade. Assim, objetivou-se investigar os determinantes das internações por tuberculose e sua distribuição espacial e tendência temporal. Estudo ecológico, cujos dados primários foram obtidos a partir de entrevistas com os profissionais da saúde da Atenção Primária à Saúde (APS) no ano de 2014 e os dados secundários das internações por TB entre 2006 e 2015 registrados no Sistema de Informação Hospitalar do Sistema Único de Saúde (SIH/SUS). Além disso, recorreu-se ao Índice Paulista de Vulnerabilidade Social - versão 2010 para mensurar a vulnerabilidade social nos territórios. Procedeu-se inicialmente às análises dos dados por meio da estatística descritiva, realizadas no Statistica 12.0. Para análise espacial realizou-se a geocodificação das internações no TerraView versão 4.2.2. Considerou-se como unidades de análise as 46 áreas de abrangência da APS, classificadas segundo suas modalidades. Estimou-se a taxa bruta e bayesiana empírica das internações evitáveis por TB, sendo suavizada pelo Método Bayesiano Empírico. Recorreu-se, ainda, à regressão linear múltipla pelo método dos mínimos quadrados e à regressão espacial para verificar a relação de dependência espacial das internações evitáveis por TB com a capacidade da APS de coordenar as Redes de Atenção à Saúde (RAS) e ao Índice de Vulnerabilidade Social. Mapas coropléticos foram construídos no ArcGis 10.2. Das 46 unidades de APS, apenas cinco foram classificadas na condição regular para coordenar as RAS. Em relação aos atributos, nenhuma das áreas foi classificada na condição insatisfatória e apenas uma, na condição ótima. Na modelagem espacial, não se observaram atributos que fossem significativamente relacionados às internações evitáveis por TB. Foram identificados 265 casos de internações evitáveis por TB. As taxas variaram de 1,24 a 10,66 internações por TB por 100.000 habitantes/ano. O Distrito Norte apresentou as taxas mais altas (> 6,57); os Distritos Sul, Oeste e Norte apresentaram taxas moderadas (3,70 - 6,56); os Distritos Leste e Central apresentaram as taxas mais baixas (< 3,69). Houve uma maior concentração de internações em regiões mais densas e entre os anos de 2008 a 2009 e 2014 a 2015. Referente ao IVS, os Distritos Sul, Leste, Oeste e Central foram classificados em sua maioria no Grupo 2 (vulnerabilidade muito baixa); os Distritos Norte e Oeste, no Grupo 3 (vulnerabilidade baixa) e uma área foi classificada com vulnerabilidade muito alta (Distrito Norte). Na modelagem espacial também não se observou relação estatisticamente significativa do IVS com as internações evitáveis por TB. O estudo, identificou as áreas da APS mais deficientes quanto à coordenação das RAS e cartografou as áreas mais vulneráveis às internações por TB, possibilitando à gestão local um planejamento em saúde mais direcionado àqueles grupos mais vulneráveis, a fim de diminuir o número de internações evitáveis e injustas e avançar na melhoria da qualidade e fortalecimento de um sistema de saúde orientado pela APS sob a conformação de Redes

Tuberculosis (TB) still stands as a global emergency and presents high magnitude, transcendence and vulnerability. Thus, the aim was to investigate determinants of tuberculosis hospitalizations, their spatial distribution and temporal trend. An ecological study whose primary data were obtained from interviews with Primary Health Care (PHC) professionals in the year 2014 and secondary data of hospitalizations for TB were collected between 2006 and 2015 and recorded in the Hospital Information System of the Health Unique System (SIH/SUS). Also, it was possible to use the Paulista Social Vulnerability Index, 2010 version, to measure social vulnerability in the territories. Initially, data analyses were carried out through descriptive statistics and performed by Statistica 12.0. For spatial analysis, it was carried out hospitalizations geocoding through TerraView, version 4.2.2. The 46 areas covered by the APS were considered as analyses units and classified according to their modalities. It was possible to estimate the gross and empirical Bayesian rate of avoidable hospitalizations by TB and smoothed by the Bayesian Empiric Method. It was also used the multiple linear regression through the method of least squares and spatial regression to verify the spatial dependence relation of avoidable hospitalizations by TB, with the APS capacity to coordinate the Health Care Networks (RAS) and Index of Social vulnerability. Coropletic maps were constructed in the ArcGis 10.2. Of a total of 46 APS, only five were classified in the regular condition to coordinate the RAS. Regarding the attributes, none of the areas was classified as unsatisfactory condition and only one of them was categorized in the optimal condition. In the spatial modeling, there were no attributes significantly related to avoidable hospitalizations for TB. A total of 265 cases of preventable hospitalizations for TB were identified. Rates ranged from 1.24 to 10.66 hospitalizations for TB per 100,000 inhabitants a year. The Northern District had the highest rates (> 6.57); The South, West and North Districts presented reasonable rates (3.70 - 6.56); The Eastern and Central Districts had the lowest rates (<3.69). There was a greater concentration of hospitalizations in denser regions between the years 2008-2009 and 2014-2015. Regarding the IVS, South, East, West and Central Districts were classified mostly in the Group 2 (very low vulnerability). North and West Districts in Group 3 (low vulnerability) and one area was ranked with very high vulnerability (Northern District). In the spatial modeling, there was no statistically significant relationship between the IVS and avoidable hospitalizations for TB. The study identified the most deficient areas of APS in the coordination of RAS and mapped the most vulnerable areas to hospitalizations for TB. Thus, it was possible for the local management to plan a health care more targeted to the most vulnerable groups to reduce the number of avoidable and unjust hospitalizations and advance in quality and strengthening improvement of a health system oriented to the APS, under the formation of Networks

Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012).

OBJECTIVE: To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS: This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScan™ were used in the analysis. RESULTS: We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7-4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4-36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2-0.3). We did not identify any space-time clusters. CONCLUSIONS: The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care.

Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012) / Análise espacial das internações evitáveis por tuberculose em Ribeirão Preto, SP (2006-2012)

ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7-4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4-36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2-0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care.

RESUMO OBJETIVO Descrever a distribuição espacial dos casos de internações evitáveis por tuberculose no município de Ribeirão Preto, SP, e identificar aglomerados espaciais e espaço-temporais de risco para a ocorrência desses eventos. MÉTODOS Estudo descritivo e ecológico que considerou os registros de internações no Sistema de Informação Hospitalar dos residentes de Ribeirão Preto, SP, no período de 2006 a 2012. Para as análises espaciais foram considerados somente os casos com endereços registrados, sendo os mesmos geocodificados. Recorreu-se à estatística de densidade Kernel para identificar as áreas de maior densidade, taxa bayesiana empírica local como método de suavização das taxas de incidência de internações e estatística de varredura para identificação de aglomerados de risco. Para as análises foram utilizados os softwares ArcGis 10.2, TerraView 4.2.2 e SaTScanTM. RESULTADOS Foram identificadas 169 internações por tuberculose. A maioria das internações ocorreu com pessoas do sexo masculino (n = 134; 79,2%) com idade mediana de 48 anos (DP = 16,2). A forma clínica predominante foi a pulmonar, com confirmação por exame microscópico da expectoração (n = 66; 39,0%). Foram geocodificados 159 (94,0%) casos. Observou-se distribuição espacial não aleatória de internações evitáveis por tuberculose, concentradas nas regiões norte e oeste do município. Por meio da estatística de varredura, identificaram-se três aglomerados espaciais de risco para internações por tuberculose, um na região norte do município (risco relativo [RR] = 3,4; IC95% 2,7-4,4); o segundo, na região central, onde há uma unidade prisional (RR = 28,6; IC95% 22,4-36,6); e o último, na região sul, área de proteção para as internações (RR = 0,2; IC95% 0,2-0,3). Não foram identificados aglomerados espaço-temporais. CONCLUSÕES A investigação mostrou áreas prioritárias para o controle e vigilância da tuberculose e um perfil de população atingida, evidenciando aspectos importantes a serem considerados em termos de gestão e organização dos serviços de saúde com vistas à efetividade da Atenção Primária à Saúde.