Clusters of leprosy transmission and of late diagnosis in a highly endemic area in Brazil: focus on different spatial analysis approaches


Autoria(s): Alencar, Carlos H.; Ramos, Alberto N., Jr.; Santos, Emerson S. dos; Richter, Joachim; Heukelbach, Jorg
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

02/10/2013

02/10/2013

2012

Resumo

Objective The Brazilian National Hansens Disease Control Program recently identified clusters with high disease transmission. Herein, we present different spatial analytical approaches to define highly vulnerable areas in one of these clusters. Method The study area included 373 municipalities in the four Brazilian states Maranha o, Para ', Tocantins and Piaui '. Spatial analysis was based on municipalities as the observation unit, considering the following disease indicators: (i) rate of new cases / 100 000 population, (ii) rate of cases < 15 years / 100 000 population, (iii) new cases with grade-2 disability / 100 000 population and (iv) proportion of new cases with grade-2 disabilities. We performed descriptive spatial analysis, local empirical Bayesian analysis and spatial scan statistic. Results A total of 254 (68.0%) municipalities were classified as hyperendemic (mean annual detection rates > 40 cases / 100 000 inhabitants). There was a concentration of municipalities with higher detection rates in Para ' and in the center of Maranha o. Spatial scan statistic identified 23 likely clusters of new leprosy case detection rates, most of them localized in these two states. These clusters included only 32% of the total population, but 55.4% of new leprosy cases. We also identified 16 significant clusters for the detection rate < 15 years and 11 likely clusters of new cases with grade-2. Several clusters of new cases with grade-2 / population overlap with those of new cases detection and detection of children < 15 years of age. The proportion of new cases with grade-2 did not reveal any significant clusters. Conclusions Several municipality clusters for high leprosy transmission and late diagnosis were identified in an endemic area using different statistical approaches. Spatial scan statistic is adequate to validate and confirm high-risk leprosy areas for transmission and late diagnosis, identified using descriptive spatial analysis and using local empirical Bayesian method. National and State leprosy control programs urgently need to intensify control actions in these highly vulnerable municipalities.

Brazilian Research Council (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, CNPq)

Brazilian Research Council CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico)

Department of Science and Technology of the Brazilian Ministry of Health (DECIT)

Department of Science and Technology of the Brazilian Ministry of Health (DECIT)

CAPES (Fundacao Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil)

Fundacao Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES, Brazil)

Identificador

TROPICAL MEDICINE & INTERNATIONAL HEALTH, MALDEN, v. 17, n. 4, pp. 518-525, APR, 2012

1360-2276

http://www.producao.usp.br/handle/BDPI/33930

10.1111/j.1365-3156.2011.02945.x

http://dx.doi.org/10.1111/j.1365-3156.2011.02945.x

Idioma(s)

eng

Publicador

WILEY-BLACKWELL

MALDEN

Relação

TROPICAL MEDICINE & INTERNATIONAL HEALTH

Direitos

closedAccess

Copyright WILEY-BLACKWELL

Palavras-Chave #LEPROSY #CONTROL #PUBLIC HEALTH #SPATIAL ANALYSIS #BRAZIL #EPIDEMIOLOGY #LEPRE #CONTROLE #SANTE PUBLIQUE #ANALYSE SPATIALE #BRESIL #EPIDEMIOLOGIE #LEPRA #CONTROL #SALUD PUBLICA #ANALISIS ESPACIAL #BRASIL #EPIDEMIOLOGIA #RISK-FACTORS #POPULATION #DISEASE #BANGLADESH #DISABILITY #HEALTH #REGION #AMAZON #GIS #PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH #TROPICAL MEDICINE
Tipo

article

original article

publishedVersion