OBJECTIVE: To analyze the spatial distribution of the incidence of leprosy and identify areas at risk for occurrences of hyper-endemic disease in northeastern Brazil.
METHODS: Ecological study using municipalities as the analysis unit. Data on new cases of leprosy came from the Health Hazard Notification System (SINAN). This study focused on Pernambuco and covered the years 2005 to 2014. Indicators for monitoring were calculated per 100,000 inhabitants. The local empirical Bayes method was used to minimize rate variance and spatial autocorrelation maps were used for spatial pattern analysis (box maps and Moran maps).
RESULTS: 28,895 new cases were registered in the study period. The average incidence was 21.88/100,000; the global Moran's I index was 0.36 (p < 0.01), thus indicating the existence of spatial dependence; and the Moran map identified 20 municipalities with high priority for attention. The average incidence rate among individuals under 15 years of age was 8.78/100,000; the global Moran's I index showed the presence of positive spatial autocorrelation (0.43; p < 0.01), and the Moran map showed a main cluster of 15 hyper-endemic municipalities. The average rate of grade 2 physical disability at the time of diagnosis was 1.12/100,000; the global Moran index presented a positive spatial association (0.17; p < 0.01); and the Moran map located clusters of municipalities (high-high) in three mesoregions.
CONCLUSION: Application of different spatial analysis methods made it possible to locate areas that would not have been identified by epidemiological indicators alone. This article is protected by copyright. All rights reserved.
BT - Tropical medicine & international health : TM & IH C1 -http://www.ncbi.nlm.nih.gov/pubmed/29704447?dopt=Abstract
DO - 10.1111/tmi.13067 J2 - Trop. Med. Int. Health LA - eng N2 -OBJECTIVE: To analyze the spatial distribution of the incidence of leprosy and identify areas at risk for occurrences of hyper-endemic disease in northeastern Brazil.
METHODS: Ecological study using municipalities as the analysis unit. Data on new cases of leprosy came from the Health Hazard Notification System (SINAN). This study focused on Pernambuco and covered the years 2005 to 2014. Indicators for monitoring were calculated per 100,000 inhabitants. The local empirical Bayes method was used to minimize rate variance and spatial autocorrelation maps were used for spatial pattern analysis (box maps and Moran maps).
RESULTS: 28,895 new cases were registered in the study period. The average incidence was 21.88/100,000; the global Moran's I index was 0.36 (p < 0.01), thus indicating the existence of spatial dependence; and the Moran map identified 20 municipalities with high priority for attention. The average incidence rate among individuals under 15 years of age was 8.78/100,000; the global Moran's I index showed the presence of positive spatial autocorrelation (0.43; p < 0.01), and the Moran map showed a main cluster of 15 hyper-endemic municipalities. The average rate of grade 2 physical disability at the time of diagnosis was 1.12/100,000; the global Moran index presented a positive spatial association (0.17; p < 0.01); and the Moran map located clusters of municipalities (high-high) in three mesoregions.
CONCLUSION: Application of different spatial analysis methods made it possible to locate areas that would not have been identified by epidemiological indicators alone. This article is protected by copyright. All rights reserved.
PY - 2018 T2 - Tropical medicine & international health : TM & IH TI - Spatial analysis of reported new cases and local risk of leprosy in hyper-endemic situation in north-eastern Brazil. SN - 1365-3156 ER -