Spatial patterns of pulmonary tuberculosis incidence and their relationship to socio-economic status in Vitoria, Brazil
OBJECTIVE: To investigate spatial patterns of the incidence of pulmonary tuberculosis (TB) and its relationship with socio-economic status in Vitoria, Espirito Santo, Brazil.DESIGN: In a 4-year, retrospective, territory-based surveillance study of all new pulmonary TB cases conducted in Vitoria betw...
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Published in | The international journal of tuberculosis and lung disease Vol. 14; no. 11; pp. 1395 - 1402 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Paris, France
IUATLD
01.11.2010
International Union against Tuberculosis and Lung Disease |
Subjects | |
Online Access | Get full text |
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Summary: | OBJECTIVE: To investigate spatial patterns of the incidence of pulmonary tuberculosis (TB) and its relationship with socio-economic status in Vitoria, Espirito Santo, Brazil.DESIGN: In a 4-year, retrospective, territory-based surveillance study of all new pulmonary TB cases conducted
in Vitoria between 2002 and 2006, spatial patterns of disease incidence were compared using spatial clustering statistics (Anselin's local indicators of spatial association [LISA] and Getis-Ord Gi* statistics), smoothed empirical Bayes estimates and model-predicted incidence rates.
Spatial Poisson models were fit to examine the relationship between socio-economic status and TB incidence.RESULTS: A total of 651 TB cases were reported across 78 neighborhoods, with rates ranging from 0 to 129 cases per 100 000 population. Moran's I indicated strong
spatial autocorrelation among incidence rates (0.399, P < 0.0001), and four areas of high incidence were identified by LISA and Gi* statistics. Smoothed spatial empirical Bayes estimates demonstrate that two of these areas range from 70 to 90 cases/100 000, while the other
two range from 40 to 70 cases/100 000. TB incidence and socio-economic status had a significant curvilinear relationship (P = 0.02).CONCLUSIONS: Data derived from these spatial statistical tools will help TB control programs to allocate TB resources to those populations
most at risk of increasing TB rates and to target areas where TB control efforts need to be concentrated. |
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Bibliography: | (R) Medicine - General 1027-3719(20101101)14:11L.1395;1- ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 1027-3719 1815-7920 |