02818nas a2200409   4500000000100000008004100001260001300042653001500055653001100070653001000081653002100091653001100112653001400123653001100137653001100148653001200159653002000171653002100191653001500212653002200227653002600249653002600275653002100301653001700322100001700339700001800356700001300374700001500387700001300402700001400415245007900429856005300508300001100561490000700572520181500579022001402394       2009                            d  c2009 Aug10aAdolescent10aBrazil10aChild10aChild, Preschool10aHumans10aIncidence10aIncome10aInfant10aleprosy10aLogistic Models10aNeeds Assessment10aOdds Ratio10aPopulation Growth10aSocioeconomic Factors10aSpace-Time Clustering10aUrban Population10aUrbanization1 aImbiriba ENB1 aSilva Neto AL1 aSouza WV1 aPedrosa VL1 aCunha MG1 aGarnelo L00aSocial inequality, urban growth and leprosy in Manaus: a spatial approach.  uhttp://www.scielosp.org/pdf/rsp/v43n4/en_842.pdf  a656-650 v433 a<p><b>OBJECTIVE: </b>To analyze the epidemiology of leprosy according to spatial distribution and living conditions of the population.</p><p><b>METHODS: </b>Ecological study based on the spatial distribution of leprosy in the municipality of Manaus, Northern Brazil, from 1998 to 2004. The 4,104 cases identified in the Sistema de Informações de Agravos de Notificação (Sinan -National Notification System) were georeferenced according to the addresses in the 1,536 urban census tracts through four different sources: postal service (73.7% of addresses found), Property Registration Program (7.3%), Family Health Program (2.1%), and Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics) data sheet (1.5%). Calculation of detection coefficient was performed based on the 2001 population. Local empirical Bayesian method was used for the spatial distribution analysis, in order to estimate leprosy risk, making rate variation shorter when they were calculated for small areas. Logistic regression was employed to analyze the association between geographical distribution and risk factors. The incidence of cases in children under 15 (severity indicator) and Social Need Index built from variables of the 2000 census were adopted as explicative variables.</p><p><b>RESULTS: </b>The mean coefficient of detection was hyperendemic in 34.0% of the census tracts, and very high in 26.7%. Odds ratio was obtained for explicative variables and proved to be significant. Low-income and incidence in children under 15 were combined to identify priority areas for intervention.</p><p><b>CONCLUSIONS: </b>Spatial analysis of leprosy showed that the distribution of the disease is heterogeneous and is more strongly present in regions inhabited by more vulnerable groups.</p>  a1518-8787