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Revista Pan-Amazônica de Saúde

versão impressa ISSN 2176-6223versão On-line ISSN 2176-6223

Resumo

LIMA, Sandra Souza et al. Spatial analysis of tuberculosis in Belém, Pará State, Brazil. Rev Pan-Amaz Saude [online]. 2017, vol.8, n.2, pp.55-63. ISSN 2176-6223.  http://dx.doi.org/10.5123/s2176-62232017000200007.

INTRODUCTION:

Tuberculosis (TB) in Brazil is mainly located in major urban centers and is associated with the social and economical patterns. In 2011, Belém, the capital of Pará State, showed one of the highest incidence.

OBJECTIVES:

To investigate the spatial distribution of Mycobacterium tuberculosis in Belém between 2006 and 2010, and to associate the incidence of infection with the life quality of the population.

MATERIALS AND METHODS:

Morbidity and mortality information were obtained from national public information sources (SINAN, SIM and IBGE). Global Moran's index (GMI) and local Moran's index were used to identify spatial associations.

RESULTS:

Incidence rate of TB was 93 cases/100,000 inhabitants and mortality reached 4 cases/100,000. GMI showed negative space dependence with regard to incidence and positive space dependence in mortality rates among districts. Incidence of TB showed an increase according to the poorest quality of life areas of the city. The Bayesian method was successful to analyze the incidence of TB in low population density areas. The incidence was spatially distributed randomly and associated with the socioeconomic conditions of population. The low mortality rate was an evidence of the good treatment services and follow up of the patients.

CONCLUSION:

The use of spatial analysis and statistical methods, that improve the quality of the information, are important to better evaluate the future prevention actions against infectious agents. It is necessary to continue with TB prevention campaigns and patient follow-up in order to increase adherence to treatment and decrease mortality among the population with the greatest difficulty in accessing health services.

Palavras-chave : Tuberculosis; Spatial Analysis; Bayesian Method.

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