Spatial distribution of leprosy in areas of risk in Vitoria, State of Espirito Santo, Brazil, 2005 to 2009

• Published in: Revista da Sociedade Brasileira de Medicina Tropical
• Main Authors: Poliane Barbosa Sampaio, Elizabeth Santos Madeira, Lucia Diniz, Ethel Leonor Noia, Eliana Zandonade
• Format: Article in Journal/Newspaper
• Language: English
• Published: Sociedade Brasileira de Medicina Tropical (SBMT) 2013
• Subjects: Leprosy; Epidemiology; Spatial distribution; Arctic medicine. Tropical medicine; RC955-962; Arctic
• Online Access: https://doi.org/10.1590/0037-8682-0070-2012; https://doaj.org/article/59fb502c99ed427aa4ece947f63d939c

Introduction Leprosy remains a relevant public health issue in Brazil. The objective of this study was to analyze the spatial distribution of new cases of leprosy and to detect areas with higher risks of disease in the City of Vitória. Methods The study was ecologically based on the spatial distribution of leprosy in the City of Vitória, State of Espírito Santo between 2005 and 2009. The data sources used came from the available records of the State Health Secretary of Espírito Santo. A global and local empirical Bayesian method was used in the spatial analysis to produce a leprosy risk estimation, and the fluctuation effect was smoothed from the detection coefficients. Results The study used thematic maps to illustrate that leprosy is distributed heterogeneously between the neighborhoods and that it is possible to identify areas with high risk of disease. The Pearson correlation coefficient of 0.926 (p = 0.001) for the Local Method indicated highly correlated coefficients. The Moran index was calculated to evaluate correlations between the incidences of adjoining districts. Conclusions We identified the spatial contexts in which there were the highest incidence rates of leprosy in Vitória during the studied period. The results contribute to the knowledge of the spatial distribution of leprosy in the City of Vitória, which can help establish more cost-effective control strategies because they indicate specific regions and priority planning activities that can interfere with the transmission chain.