dc.creatorde Cassia Oliveira Cury, Maria Rita
dc.creatorPaschoal, Vania Del'Arco
dc.creatorTonelli Nardi, Susilene Maria
dc.creatorChierotti, Ana Patricia
dc.creatorRodrigues Junior, Antonio Luiz
dc.creatorChiaravalloti Neto, Francisco
dc.date.accessioned2013-11-07T11:19:46Z
dc.date.accessioned2018-07-04T16:23:26Z
dc.date.available2013-11-07T11:19:46Z
dc.date.available2018-07-04T16:23:26Z
dc.date.created2013-11-07T11:19:46Z
dc.date.issued2012
dc.identifierREVISTA DE SAUDE PUBLICA, SAO PAULO, v. 46, n. 1, supl., Part 1-2, pp. 110-118, FEB, 2012
dc.identifier0034-8910
dc.identifierhttp://www.producao.usp.br/handle/BDPI/42982
dc.identifier10.1590/S0034-89102011005000086
dc.identifierhttp://dx.doi.org/10.1590/S0034-89102011005000086
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1635208
dc.description.abstractOBJECTIVE: To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. METHODS: Cases of leprosy that occurred between 1998 and 2007 in Sao Jose do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. RESULTS: While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. CONCLUSIONS: The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.
dc.languageeng
dc.publisherREVISTA DE SAUDE PUBLICA
dc.publisherSAO PAULO
dc.relationREVISTA DE SAUDE PUBLICA
dc.rightsCopyright REVISTA DE SAUDE PUBLICA
dc.rightsopenAccess
dc.subjectLEPROSY, EPIDEMIOLOGY
dc.subjectSOCIOECONOMIC FACTORS
dc.subjectGEOGRAPHIC INFORMATION SYSTEMS, UTILIZATION
dc.subjectEPIDEMIOLOGIC SURVEILLANCE
dc.titleSpatial analysis of leprosy incidence and associated socioeconomic factors
dc.typeArtículos de revistas


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