Spatial regression showed that socioeconomic vulnerability indicators influence the outcome, positively or negatively, depending on the region, which calls for intensified prevention and control efforts in those areas.
Abstract
ABSTRACT Objective: To analyze the spatial and temporal patterns and factors associated with tuberculosis treatment interruption in Brazil from 2010 to 2020. Method: Ecological study using geoprocessing. The Joinpoint method was used for temporal analysis. Spatial autocorrelation and scan statistics identified clusters. Spatial and non-spatial regression models, considering p < .05, detected factors associated with the outcome. Results: A stationary trend in tuberculosis treatment interruption was observed across the country, with increases in the Central-West and North regions. Associated socioeconomic indicators included the Gini index, household density > 2, retreatment rate, social vulnerability index, illiteracy rate, percentage of individuals in extreme poverty, and Family Health Strategy coverage. Conclusion: Treatment interruption showed a stationary trend. Spatial regression showed that socioeconomic vulnerability indicators influence the outcome, positively or negatively, depending on the region, which calls for intensified prevention and control efforts in those areas.
The results emphasize the need for geographically targeted, municipality-focused interventions to advance Nepal’s progress toward the End TB Strategy and Sustainable Development Goal 3.
Tuberculosis incidence in Semarang City exhibited a clustered spatial pattern, particularly in densely populated areas, which support geographically targeted TB control strategies.
Muhammad Auliya Rahman, Muhammad Ashraff Zurkarnain, S. Sulistiyani et al.· Liaquat National Journal of...· 0 citations
ABSTRACT Background: Dengue remains a public health challenge, driven by Aedes aegypti proliferation within complex socio-environmental conditions. Methods: This study investigated the spatiotemporal distribution of dengue in Manaus from 2016 to 2022. Temporal analysis used negative binomial regression adjusted for seasonality. Seasonal and spatial clusters were identified using scan statistics (p < 0.05, 95% CI). A Bayesian spatial model assessed sociodemographic and environmental determinants. Results: Lagged temperature and wind speed showed protective effects. The Bayesian model identified significant associations with population density, vegetation indices (NDVI), sewage infrastructure, and housing types. Conclusions: Integrating climatic and socioeconomic data is essential for intersectoral dengue control strategies.
Mirelia Rodrigues de Araújo, F. Chiaravalloti-Neto, Gerusa Maria Figueiredo· Revista da Sociedade Brasile...· 0 citations
Summary Background Tuberculosis remains a major cause of preventable mortality in Brazil, marked by pronounced social and territorial inequalities. Evidence remains limited on how socioeconomic conditions and health system characteristics are associated with tuberculosis mortality across age groups in high-burden settings such as São Paulo state. This study aimed to examine the spatial and temporal associations of these factors with tuberculosis mortality across municipalities in the State of São Paulo, Brazil. Methods We conducted a population-based ecological study in São Paulo, Brazil. All TB deaths reported to the Mortality Information System from 2020 to 2024 were included. Socioeconomic, demographic and health system factors were selected based on a conceptual framework. Variables associated with TB mortality were assessed using Generalized Additive Models for Location, Scale, and Shape, with spatial smoothing. Findings The analysis included 38,700 municipality-month observations. In the final spatial GAMLSS model, proportions of household crowding (>2 residents/bedroom) and elderly population (>59 years) were associated with 3.25% and 5.92% increases in expected TB mortality for each one percentage-point increase, respectively. In contrast, each one percentage-point increase in primary health care coverage was associated with a 0.30% decrease in expected TB mortality. The fitted spatial effect indicated higher expected TB mortality along coastal and central regions, and lower expected mortality in the northwestern region. Interpretation Tuberculosis mortality in São Paulo is shaped by persistent socioeconomic and territorial inequalities, with distinct patterns across age groups. These findings highlight the need for strategies that address structural vulnerability and strengthen primary health care to reduce avoidable tuberculosis-related deaths. Funding This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brasil and São Paulo State Research Foundation (FAPESP).
Y. M. Alves, Reginaldo Bazon Vaz Tavares, Nathália Zini et al.· The Lancet Regional Health -...· 0 citations
This study employed geospatial approaches to assess the risk and spatial distribution of Dengue Fever (DF) and Dengue Hemorrhagic Fever (DHF) in Phayao Province, Thailand. Epidemiological data from 2016 to 2024, comprising 3,600 reported cases, were analysed alongside demographic and climatic variables. Temporal analysis revealed a major epidemic in 2023 lasting 20 weeks, coinciding with peak rainfall, with adolescents and young adults (13-24 years old) being the most affected group. Spatial autocorrelation (Moran's I) indicated significant clustering of dengue morbidity rates, with hotspots concentrated in urbanised districts such as Mueang Phayao, Dok Khamtai and Chiang Kham, while Kernel Density Estimation (KDE) highlighted shifts of hotspots toward eastern districts in later years. Local Indicators of Spatial Association (LISA) identified 24 high-high clusters in 2019, predominantly in Mae Chai District. Case-control analysis further revealed that socio-economic conditions, housing environments and inconsistent preventive behaviours influenced dengue incidence, with strong community participation linked to more effective prevention. These findings underscore the spatial heterogeneity of dengue transmission and provide geospatial evidence to guide targeted vector control, strengthen community-based interventions, and support evidence-based public health strategies in northern Thailand.
Phaisarn Jeefoo, Watcharaporn Preedapirom Jeefoo, S. Mekruksavanich et al.· Geospatial Health· 0 citations
ABSTRACT Objective: To analyze time trends and spatial patterns corresponding to gestational and congenital syphilis in the Brazilian North region between 2014 and 2023. Method: A time-based ecological study conducted with secondary data from the National Live Births System and from the national panel of syphilis indicators. The gestational and congenital syphilis rates were analyzed by means of log-linear regression and “joinpoint” models to estimate the Annual Percent Change. The associations were estimated via fixed-effects count and population-based offset methods, in turn, spatial dependence was estimated through spatial autoregressive regressions. Results: Gestational Syphilis presented continuous growth in the historical series. Congenital Syphilis showed heterogeneity across the states, with an 80.5% annual increase in Amazonas until 2017, followed by a reverse trend after 2018; in turn, the increasing trend remained in Pará during the entire period. Conclusion: Social and territorial inequalities remain as core determinants of persistent mother-to-child syphilis transmission in the Brazilian Amazon.
Maria Karoliny da Silva Torres, Laís Gabriela da Silva Neves, A. T. Parente et al.· Cogitare Enfermagem· 0 citations
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