Spatial analysis of leprosy incidence and associated socioeconomic factors

• Autor(a) principal: Cury, Maria Rita de Cassia Oliveira
• Data de Publicação: 2012
• Outros Autores: Paschoal, Vania Del´Arco, Nardi, Susilene Maria Tonelli, Chierotti, Ana Patrícia, Rodrigues Júnior, Antonio Luiz, Chiaravalloti-Neto, Francisco
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista de Saúde Pública
• Texto Completo: https://www.revistas.usp.br/rsp/article/view/33083
• topic: Leprosy; epidemiology; Socioeconomic Factors; Geographic Information Systems; utilization; Epidemiologic Surveillance; Hanseníase; epidemiologia; Fatores Socioeconômicos; Sistemas de Informação Geográfica; utilização; Vigilância Epidemiológica; Lepra; epidemiologia; Factores Socioeconómicos; Sistemas de Información Geográfica; utilización; Vigilancia Epidemiológica

OBJECTIVE: 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 São José 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.