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ARTIGO ARTICLE

Análises espaciais na identificação das áreas de risco para a esquistossomose mansônica no
Município de Lauro de Freitas, Bahia, Brasil
Identification of schistosomiasis risk areas using spatial analysis in Lauro de Freitas, Bahia
State, Brazil
Luciana Lobato Cardim 1,2
Antonio Sergio Ferraudo 3
Selma Turrioni Azevedo Pacheco 2
Renato Barbosa Reis 4
Marta Mariana Nascimento Silva 1
Deborah Daniela M. Trabuco Carneiro
Maria Emilia Bavia 1

Escola de Medicina
Veterinária, Universidade
Federal da Bahia, Salvador,
Brasil.
2 Departamento de Vigilância à Saúde, Secretaria
Municipal de Saúde de Lauro de Freitas, Lauro de Freitas,
Brasil.
3 Departamento de Ciências
Exatas, Universidade
Estadual Paulista,
Jaboticabal, Brasil.
4 Centro de Pesquisa Gonçalo
Moniz, Fundação Oswaldo
Cruz, Salvador, Brasil.
1

Correspondência
L. L. Cardim
Departamento de Medicina
Veterinária Preventiva,
Escola de Medicina
Veterinária, Universidade
Federal da Bahia.
Av. Adhemar de Barros 500,
Salvador, BA
40170-970, Brasil. [e-mail] 1

Abstract

Introdução

The spread of schistosomiasis mansoni defies efforts by Brazil’s Unified National Health System, thus demonstrating the need to reassess endemic control programs in the country. The aim of this study was to demarcate geographic areas at risk of schistosomiasis in Lauro de Freitas, Bahia
State, Brazil, and to establish the epidemiological and socioeconomic profile of the disease in this municipality (county). Kernel density estimator exploratory analysis was used for visual identification of areas at risk. Kulldorff & Nagarwalla’s spatial analysis was used to obtain statistically significant clusters and to measure risk. These technologies identified four risk areas for schistosomiasis. Clusters identified within the risk areas were characterized by lower socioeconomic conditions. Multiple correspondence analyses showed a distinct profile for positive patients in the primary cluster. The techniques employed