Spatial analysis of reported new cases and local risk of leprosy in hyper-endemic situation in Northeastern Brazil
| Autor: | André Luiz Sá de Oliveira, Cintia Michele Gondim de Brito, Celivane Cavalcanti Barbosa, Vera Rejane do Nascimento Gregório, Zulma Medeiros, Andrea Torres Ferreira, José Luiz Portugal, Cristine Vieira do Bonfim |
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| Rok vydání: | 2018 |
| Předmět: |
Male
Index (economics) Adolescent Endemic Diseases 030231 tropical medicine Spatial distribution 03 medical and health sciences Spatio-Temporal Analysis 0302 clinical medicine Risk Factors Leprosy Humans 030212 general & internal medicine Spatial dependence Child Spatial analysis Empirical Bayes method Incidence Incidence (epidemiology) Infant Newborn Public Health Environmental and Occupational Health Infant Ecological study Infectious Diseases Geography Child Preschool Common spatial pattern Female Parasitology Cartography Brazil |
| Zdroj: | Tropical Medicine & International Health. 23:748-757 |
| ISSN: | 1360-2276 |
| DOI: | 10.1111/tmi.13067 |
| Popis: | OBJECTIVE To analyse 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 minimise rate variance, and spatial autocorrelation maps were used for spatial pattern analysis (box maps and Moran maps). RESULTS A total of 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. |
| Databáze: | OpenAIRE |
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