Factores asociados a la ocurrencia de tuberculosis y su distribución espacial en una ciudad brasileña, 1991-2010

Silva, Amanda Priscila de Santana Cabral; Souza, Wayner Vieira de; Albuquerque, Maria de Fátima Pessoa Militão de

doi:10.18294/sc.2018.1195

Cited by 3 publications

(2 citation statements)

References 32 publications

(34 reference statements)

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“…However, there is a need to quantify these differences using appropriate statistical methods, and to detect similar clusters for special implementation of disease control. In addition, some ecological and environmental factors have been reported as being associated with disease occurrence [11–13]. Diversity of ecological environment in Guangxi indicates that there are possibly some independent variables influencing the spread of the disease [14].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China

et al. 2019

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Background Guangxi is one of the provinces having the highest notification rate of tuberculosis in China. However, spatial and temporal patterns and the association between environmental diversity and tuberculosis notification are still unclear. Objective To detect the spatiotemporal pattern of tuberculosis notification rates from 2010 to 2016 and its potential association with ecological environmental factors in Guangxi Zhuang autonomous region, China. Methods We performed a spatiotemporal analysis with prediction using time series analysis, Moran’s I global and local spatial autocorrelation statistics, and space-time scan statistics to detect temporal and spatial clusters of tuberculosis notifications in Guangxi between 2010 and 2016. Spatial panel models were employed to identify potential associating factors. Results The number of reported cases peaked in spring and summer and decreased in autumn and winter. The predicted number of reported cases was 49,946 in 2017. Moran's I global statistics were greater than 0 (0.363–0.536) during the study period. The most significant hot spots were mainly located in the central area. The eastern area exhibited a low-low relation. By the space-time scanning, the clusters identified were similar to those of the local autocorrelation statistics, and were clustered toward the early part of 2016. Duration of sunshine, per capita gross domestic product, the treatment success rate of tuberculosis and participation rate of the new cooperative medical care insurance scheme in rural areas had a significant negative association with tuberculosis notification rates. Conclusion The notification rate of tuberculosis in Guangxi remains high, with the highest notification cluster located in the central region. The notification rate is associated with economic level, treatment success rate and participation in the new cooperative medical care insurance scheme.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China

et al. 2019

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“…El análisis geoespacial de los eventos de interés en salud pública es una estrategia que permite identificar la dinámica de las enfermedades, las áreas geográficas más susceptibles, las características locales, sociales y ambientales que generan mayores riesgos para el grupo poblacional de adquirir o presentar una enfermedad en un determinado periodo (4) ; aspectos fundamentales en enfermedades como la TB, donde el establecimiento de esta dinámica puede favorecer las estrategias de control y mitigación de su propagación (5) .…”

Section: Mensaje Claveunclassified

Tuberculosis en la frontera colombo-venezolana: distribución geoespacial

Ruiz-Roa

Rojas

Galeano

2022

Rev Peru Med Exp Salud Publica

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La distribución geoespacial de la morbilidad por tuberculosis (TB) pulmonar y extrapulmonar en el municipio de Cúcuta en los años 2019 y 2020 se describió utilizando el método de Kulldorff usando la ubicación geográfica y la fecha de reporte de los casos incidentes de TB. La unidad de análisis fue el evento reportado al Sistema Nacional de Vigilancia Epidemiológica (SIVIGILA). Se identificaron 392 barrios distribuidos en diez comunas, donde se ubicaron 607 casos. En la distribución de la TB pulmonar, la comuna norte fue la que más casos reportó, siendo el barrio El Salado el más afectado de manera repetitiva. Los casos incidentes de TB extrapulmonar no mostraron patrones de repetición en la distribución entre las unidades espaciales y temporales. Se debe priorizar la región occidental dentro de las estrategias de mitigación y control de la propagación de la infección pulmonar del territorio.

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

Teibo,

Andrade,

Rosa

et al. 2023

BMC Public Health

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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.

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Factores asociados a la ocurrencia de tuberculosis y su distribución espacial en una ciudad brasileña, 1991-2010

Cited by 3 publications

References 32 publications

Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China

Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China

Tuberculosis en la frontera colombo-venezolana: distribución geoespacial

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

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