Conflito de interesses: Não Contribuição dos autores: JSI e RASF coleta, tabulação, delineamento do estudo e redação do manuscrito. DCA delineamento do estudo, discussão dos achados, etapas de execução e redação do manuscrito. FGMSP discussão dos achados e redação do manuscrito. ACV orientação do projeto, delineamento do estudo e elaboração do manuscrito.

Background Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis . It is a disease known worldwide for its vulnerability factors, magnitude and mortality. The objective of the study was to analyze the spatial and temporal dynamics of TB in the area of social inequality in northeast Brazil between the years 2001 and 2016. Methods An ecological time series study with the use of spatial analysis techniques was carried out from 2001 to 2016. The units of analysis were the 75 municipalities in the state of Sergipe. Data from the Notification of Injury Information System were used. For the construction of the maps, the cartographic base of the state of Sergipe, obtained at the Instituto Brasileiro de Geografia e Estatística, was used. Georeferenced data were analysed using TerraView 4.2.2 software (Instituto Nacional de Pesquisas Espaciais) and QGis 2.18.2 (Open Source Geospatial Foundation). Spatial analyses included the empirical Bayesian model and the global and local Moran indices. The time trend analyses were performed by the software Joinpoint Regression, Version 4.5.0.1, with the variables of sex, age, cure and abandonment . Results There was an increasing trend of tuberculosis cases in patients under 20 years old and 20–39 years old, especially in males. Cured cases showed a decreasing trend, and cases of treatment withdrawal were stationary. A spatial dependence was observed in almost all analysed territories but with different concentrations. Significant spatial correlations with the formation of clusters in the southeast and northeast of the state were observed. The probability of illness among municipalities was determined not to occur in a random way. Conclusion The identification of risk areas and priority groups can help health planning by refining the focus of attention to tuberculosis control. Understanding the epidemiological, spatial and temporal dynamics of tuberculosis can allow for improved targeting of strategies for disease prevention and control.

objective To analyse spatial patterns and the temporal tendency of mortality related to Chagas disease, in order to identify priority control areas in the state of Sergipe, Northeast Brazil. methods We conducted an ecological and time-series study with spatial analysis techniques on deaths from Chagas disease in the state of Sergipe (1996-2016). We used data from the Mortality Information System (SIM). The temporal analysis was performed using a statistical technique capable of describing changes in the trend pattern for the period. Thematic maps were elaborated from point and polygonal analyses. results There were 247 deaths related to Chagas disease, with a mean of 11.7 deaths/year, most of them male (64%), and aged 50-59 years (21%) and 60-69 years (26%). Two segments with increasing, non-constant and significant trends were identified: 1996-2005 (APC = 21.6%; P = 0.01) and 2005-2016 (APC = 4.4%; P = 0.01), with APPC = 11.8% (P = 0.01). A positive and significant spatial autocorrelation with areas of higher risk of death was found in the southern region of the state. conclusions The trend of mortality related to Chagas disease in the state of Sergipe was increasing during the period analysed, with a heterogeneous distribution of cases. A main risk area was identified in the southern region of the state.

Os acidentes de trânsito representam um importante problema de saúde pública mundial, em virtude do impacto morbimortalidade e qualidade de vida das vítimas, o presente artigo teve como objetivo avaliar os fatores preditores e a qualidade de vida das vítimas de trauma por acidentes de trânsito. Trata-se de um estudo observacional do tipo transversal com abordagem descritiva. A amostra foi não probabilística por conveniência, composta por 73 vítimas de trauma por acidentes de trânsito. A coleta de dados ocorreu em dois momentos: (1) durante a internação hospitalar; e (2) após 90 dias decorridos do evento traumático. Os instrumentos utilizados para o levantamento dos dados foi o de caracterização do perfil sociodemográfico e do acidente de trânsito, e o World Health Organization Quality of Life (WHOQOL) Bref. Os dados foram armazenados em planilhas eletrônicas do microsof excel 2013 e analisados com o programa BioEstat 5.0. Os fatores preditores que revelaram ter influência nos acidentes de trânsito, foram o sexo masculino (OR: 39.6), uso do álcool (OR: 31.7), ausência dos equipamentos de proteção individual (OR: 3.00) e uso de veículo automotor nos finais de semana (OR: 3,68). Na avaliação da qualidade de vida, os achados evidenciam que no trauma o domínio físico (35.1±14.8) foi o mais alterado quando comparado com os valores antes (80.5±11.2) e após 90 dias do trauma (54.0±14.5). Os acidentes de trânsito estavam associados ao sexo masculino na condução do veículo, com o consumo de álcool e o não uso dos equipamentos de proteção individual. Além disso, o trauma estar relacionado ao impacto negativo na qualidade de vida das vítimas.

Dengue is a global public health problem. The Dengue Virus (DENV) serotypes are transmitted by an Aedes aegypti mosquito. Vector control is among the primary methods to prevent the disease, especially in tropical countries. This study aimed to analyze the spatial distribution of dengue and its relationship with social inequalities using spatial modelling. An ecological study with temporal and spatial analysis was conducted in the state of Sergipe, Northeast Brazil, over a period of 18 years. Spatial modelling was used to determine the influence of space on dengue incidence and social inequalities. The epidemic rates in 2008, 2012, and 2015 were identified. Spatial modelling explained 40% of the influence of social inequalities on dengue incidence in the state. The main social inequalities related to the occurrence of dengue were the percentage of people living in extreme poverty and inadequate sanitation. The epidemic situation even increased the risk of dengue in the population of the state of Sergipe. These results demonstrate the potential of spatial modelling in determining the factors associated with dengue epidemics and are useful in planning the intersectoral public health policies.

A pesquisa teve como objetivo analisar a qualidade de vida das vítimas de traumatismo raquimedular (TRM), atendidas em dois centros de reabilitação da cidade Aracaju-Se. Trata-se de um estudo descritivo com abordagem quantitativa, realizado após aprovação do CEP da UNIT, sob protocolo nº 160911. A coleta foi realizada no mês de novembro de 2011, com sete indivíduos com diagnóstico de TRM, de dois centros de reabilitação, por meio da aplicação de um questionário de caracterização e do WHOQOL-Bref. Evidenciou-se que a maioria vítimas era do sexo masculino, com idade média de 35,6 anos, casados, vítimas de acidentes de trânsito e arma de fogo, com lesão medular completa em nível cervical. As vítimas tiveram alterações nos domínios físico, psicológico, relação social e meio ambiente do WHOQOL-bref e classificaram a qualidade de vida como “boa” e “muito boa” (71,5%), sentiam-se “satisfeitos” (57,1%) com a sua saúde. A compreensão do impacto na qualidade vida das vítimas com TRM é essencial no processo de reabilitação e reinserção do indivíduo no ambiente social e familiar.

Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space–time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19–related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2; P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.

Objective: to analyze the quality of a tuberculosis notification information system after record linkage and spatial and temporal distribution of tuberculosis in a Brazilian state. Method: an ecological study carried between 2006 and 2016 in Sergipe, Brazil. A deterministic linkage was performed with Notifiable Diseases Information System and Mortality Information System, recording 7,873 cases and 483 deaths. The temporal trend of tuberculosis incidence was calculated. Results: there was an increase among men (2.75%), > 60 years (6.29%), higher education (4.34%) and indigenous (4.76%). A total of 190 new cases (2.9%) was found. There was an increasing trend in tuberculosis incidence with a concentration of deaths in the metropolitan region. Conclusion: the quality of the information system showed fragility in identifying cases and deaths in Sergipe. Temporal distribution showed an increasing trend in tuberculosis incidence, and spatial distribution identified higher incidences in southeastern Brazil.