Genotypic and Spatial Analysis of<i>Mycobacterium tuberculosis</i>Transmission in a High-Incidence Urban Setting

Ribeiro, Fabíola Karla; Pan, William; Bertolde, Adelmo Inácio; Vinhas, Solange Alves; Peres, Renata Lyrio; Riley, Lee W.; Palaci, Moisés; Maciel, Ethel Leonor Nóia

doi:10.1093/cid/civ365

Cited by 35 publications

(27 citation statements)

References 27 publications

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“…Several studies showed that TB is associated with conditions that express vulnerability to social determinants, such as, HIV co-infection, drug abuse, immigration, unemployment, low educational level, poor housing quality and crowded living conditions 3,4,6 . Wong et al 32 analyzing the distribution of TB case notifications in Thailand (2010) according to the population density, observed an overlap of high population density areas in areas with greater amount of TB case notifications.…”

Section: Discussionmentioning

confidence: 99%

“…Their use in public health provides a better understanding of the dynamics of the disease processes and diffusion as well as the relationship between the disease and the environment 1 . Some studies have evaluated tuberculosis (TB) distribution using spatial analysis tool [2][3][4][5][6][7] . In Portugal, the spatial distribution of TB incidence rates (2004)(2005)(2006) showed high values in large cities (Porto, Lisbon and Setúbal Peninsula), in north-eastern and in southern Portugal 8 .…”

Section: Introductionmentioning

confidence: 99%

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Distribution of pulmonary tuberculosis in Rio de Janeiro (Brazil): a spatial analysis

Rodrigues

Andrade

O’Dwyer

et al. 2017

Ciênc. saúde coletiva

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The aim of this study was to analyze the spatial distribution of the tuberculosis endemic in Rio de Janeiro State from 2002 to 2011. A retrospective study was conducted in the state of Rio de Janeiro from 2002 to 2011. Spatial analysis techniques were used to describe the distribution of tuberculosis incidence in the state. Multilevel Poisson regression model was used to access the relationship of tuberculosis and the following factors: “sex”, “age-group” and “diagnostic year” (individual-level factors). Demographic density and municipality were also included in the model as contextual-level factors. A reduction in endemic tuberculosis was observed over the years. The highest incidence rates were concentrated on the south coast of the state, covering Rio de Janeiro City (capital) and neighboring cities. We detected a significant clustering of high TB incidence rates on the south coast of the state and a cluster of low incidence in the northeastern region of state. The risk of tuberculosis was higher in early 2000s, in males and in 40-59 age group. Metropolitan regions are important risk areas for the spread of tuberculosis. These findings could be used to plan control measures according to the characteristics of each region.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distribution of pulmonary tuberculosis in Rio de Janeiro (Brazil): a spatial analysis

Rodrigues

Andrade

O’Dwyer

et al. 2017

Ciênc. saúde coletiva

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“…Previous studies have demonstrated that the characteristics of pulmonary tuberculosis (PTB)exist an obvious spatial-temporal heterogeneity at the national level or the provincial level (Tweya et al, 2013;Ribeiro et al, 2015;Kolifarhood et al, 2015;Hassarangsee et al, 2015), and it is believed that a better understanding of the patterns on spatial-temporal heterogeneity of smear positive PTB are important to formulate effective national prevention and control strategies, and allocate the limited health resources of national TB program (NTP) (Areias et al, 2015;Wubuli et al, 2015). As the most infectious form of TB and the main source of infection, prolonged exposure to smear positive PTB patient are highly susceptible to infect with TB, meanwhile, the longer, the more dangerous (Chen et al, 2016;Shi et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Analysis on spatial-temporal distribution characteristics of smear positive pulmonary tuberculosis in China, 2004–2015

Mao

Zeng

Zheng

et al. 2019

International Journal of Infectious Diseases

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Background: In China, tuberculosis (TB) is still a major infectious disease threatening people's health. Smear positive pulmonary TB is one of the most common infectious forms of TB and it might easily cause the outbreak in some areas. With a better understanding of the spatial-temporal variations of smear positive PTB, we would reach the targets for TB prevention and controlling, identify high-risk areas and periods. Thus, the aim of this study was to investigate the spatial-temporal variations of smear positive PTB. Methods: Provincial level data of reported smear positive PTB monthly cases and incidence from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health of China. Purely spatial-temporal descriptive analysis was used to characterize the distribution patterns of smear positive PTB. The global spatial auto-correlation statistics (Moran's I) and the local indicators of spatial association (LISA) were conducted to identify the spatial auto-correlation and high risk areas of smear positive PTB cases. Furthermore, the space-time scan statistic was adopted to detect the spatial-temporal clusters in different periods. Results: A total of 4,711,571 smear positive PTB cases were notified in China with an average annual incidence of 29.59/100,000. The proportion of male in different age groups were obviously higher than that of women. The largest number of cases was reported in the 20-24 years age group. Time-series analysis indicated that monthly incidence appeared a clearly seasonality and periodicity, which the seasonal peaks occurred in January and March. Smear positive PTB cases had a positive global spatial auto-correlation in 2013-2015 (Moran's I = 0.186, P = 0.046). Spatial clusters were identified in four periods, located in the different regions. The time period of 2004-2006, the most likely spatial-temporal cluster (RR = 1.69, P < 0.001) was mainly located in Hubei, Hunan, Jiangxi and Anhui of central China,

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“…[35][36] Strategic measures of prevention are urgent to the incidence control and decreasing in significantly affected regions, reinforce the need for technologies such as geocodification and genotyping as important tools in TB control and prevention in priority areas, the utilization of spatial analysis to identify local particularities, geographic, cultural and socioeconomic differences, valuing the specific needs of educative actions about the disease. [37][38][39][40][41][42][43][44]…”

Section: Strategic Measures To Fight Tuberculosismentioning

confidence: 99%

Tuberculosis Dynamics From Spatial Analysis: Integrative Review

Lima

Santos

Silva

et al. 2019

Rev. Infec. e Saude

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Objective: to analyze from literature, the contributions of spatial analysis to comprehend the tuberculosis dynamics. Method: integrative review of literature preformed within 2008 to 2017, developed from published manuscripts in any language on LILACS, PubMed and SCOPUS databases. Results: 140 studies were retrieved, of which 50 were included. The main findings refer to predominance of the use of tuberculosis incidence rates as outcome variable and its association with social and geographic conditions. The American continent presented the highest number of studies, although the African countries presented the highest incidence rates. Conclusion: the complexity of tuberculosis incidence in the geographic space is associated with epidemiologic factors. The spatial analysis presents advancements for the management of tuberculosis worldwide allowing identifying inequalities and health conditions of a population. RESUMOObjetivo: analisar a partir da literatura, as contribuições da análise espacial para compreender a dinâmica da tuberculose. Método: revisão integrativa da literatura realizada no período de 2008 a 2017, desenvolvida a partir de manuscritos publicados em qualquer idioma nas bases de dados LILACS, PubMed e SCOPUS. Resultados: foram resgatados 140 estudos, dos quais 50 incluídos. Os principais achados referem-se à predominância do uso das taxas de incidência de tuberculose como variável de desfecho e sua associação com as condições sociais e geográficas. O continente americano apresentou o maior número de estudos, apesar dos países africanos apresentarem as maiores taxas de incidência. Conclusão: a complexidade da incidência da tuberculose no espaço geográfico está associada aos fatores epidemiológicos. A análise espacial representa avanços para o gerenciamento da tuberculose mundialmente permitindo identificar desigualdades e condições de saúde de uma população. Descritores: Tuberculose; Análise Espacial; Epidemiologia; Revisão. RESUMÉNObjetivo: Analizar a partir de la literatura las contribuciones del análisis espacial para comprender la dinámica de la tuberculosis. Método: revisión bibliográfica integradora realizada entre 2008 y 2017, desarrollada a partir de manuscritos publicados en cualquier idioma en las bases de datos LILACS, PubMed y SCOPUS. Resultados: se rescataron 140 estudios, de los cuales se incluyeron 50. Los principales hallazgos se refieren al predominio del uso de tasas de incidencia de tuberculosis como variable de resultado y su asociación con condiciones sociales y geográficas. El continente americano presentó el mayor número de estudios, aunque los países africanos tuvieron las tasas de incidencia más altas. Conclusión: La complejidad de la incidencia de tuberculosis en el espacio geográfico está asociada a factores epidemiológicos. El análisis espacial representa los avances en el manejo de la tuberculosis en todo el mundo, lo que permite identificar las desigualdades y las condiciones de salud de una población.

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Genotypic and Spatial Analysis ofMycobacterium tuberculosisTransmission in a High-Incidence Urban Setting

Cited by 35 publications

References 27 publications

Distribution of pulmonary tuberculosis in Rio de Janeiro (Brazil): a spatial analysis

Distribution of pulmonary tuberculosis in Rio de Janeiro (Brazil): a spatial analysis

Analysis on spatial-temporal distribution characteristics of smear positive pulmonary tuberculosis in China, 2004–2015

Tuberculosis Dynamics From Spatial Analysis: Integrative Review

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