02451nas a2200205   4500000000100000008004100001653002700042653001600069653001200085653001100097100001400108700001500122700001300137700001600150245013300166856005100299300001200350490000700362520187600369       2013                            d10aSocio economic factors10aMethodology10aleprosy10aBrazil1 aSampaio P1 aBertolde A1 aMaciel E1 aZandonade E00aCorrelation between the spatial distribution of leprosy and socioeconomic indicators in the city of Vitoria, State of ES, Brazil  uhttps://leprosyreview.org/article/84/4/25-6265  a256-2650 v843 a<p>Introduction: Leprosy is a disease that is directly linked to poverty. The number of cases in Vitoria, the capital city of Espırito Santo, has been decreasing in recent years, but the disease remains highly endemic. This research aimed to identify relationships between the epidemiological status of leprosy and socioeconomic indicators during the period from 2005 to 2009. Methods: An ecological study was performed based on the spatial distribution of leprosy in Vitoria, Espırito Santo, between 2005 and 2009. The source data used were records available at the Secretary of State for Health of the Espırito Santo. We used the Urban Quality Index (IQU) as the leprosy-associated socioeconomic variable. The data were analysed with covariate and spatial effects by the WinBugs programme (Version 1.4) and R (Version 2.12). Results: The spatial distribution of leprosy in the district is not uniform. By studying the geographic distribution of leprosy cases, and the risks estimated by the complete Bayesian model, it was possible to gain further insight into the distribution of leprosy cases. It was noted that neighbourhoods with a low IQU have a higher leprosy case detection rate than neighbourhoods with a higher IQU. This result reinforced the theory that a low IQU is associated with the emergence of leprosy. Conclusion: The model methodology adopted enabled the verification of the effect of the influence of covariates related to the social determinants of health as well as the spatial structure, in contrast to the gross rate method that does not aggregate this information. The results obtained suggest that leprosy control may be promoted by improving the socioeconomic indicators of neighbourhoods, and highlights the need for implementation of health policies aimed at people who live in areas where they are at greatest risk of getting sick.</p>