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Author Notes:

E-mail: csalgado@ufpa.br

Conceived and designed the experiments: JGB LdSG JSS CGS.

Performed the experiments: JGB LdSG CGS.

Analyzed the data: JGB DB GMVP UK CGS.

Contributed reagents/materials/analysis tools: JSS GMVP UK CGS.

Wrote the paper: JGB DB JSS GMVP UK CGS.

We would like to thank Patrícia Ervedosa Ribeiro, Márcia Leão, Ricardo Braga Amorim and André Luiz Correa de Sousa for collecting samples and data from patients; Michael Page for the GIS course at Emory University; the Castanhal health secretary and community health agents and the study participants.

Subjects:

Research Funding:

This work was supported by CNPq (grant and scholarship for CGS), CAPES (scholarship for JGB - process 157512-0), FAPESPA, SESPA, UFPA, The Order of Malta grants for leprosy (MALTALEP) to JSS and CGS.

The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

Keywords:

  • Adolescent
  • Brazil
  • Child
  • Endemic Diseases
  • Humans
  • Leprosy
  • Spatial Analysis

Spatial Analysis Spotlighting Early Childhood Leprosy Transmission in a Hyperendemic Municipality of the Brazilian Amazon Region

Tools:

Journal Title:

PLoS Neglected Tropical Diseases

Volume:

Volume 8, Number 2

Publisher:

, Pages e2665-e2665

Type of Work:

Article | Final Publisher PDF

Abstract:

Background:More than 200,000 new cases of leprosy were reported by 105 countries in 2011. The disease is a public health problem in Brazil, particularly within high-burden pockets in the Amazon region where leprosy is hyperendemic among children.Methodology:We applied geographic information systems and spatial analysis to determine the spatio-temporal pattern of leprosy cases in a hyperendemic municipality of the Brazilian Amazon region (Castanhal). Moreover, we performed active surveillance to collect clinical, epidemiological and serological data of the household contacts of people affected by leprosy and school children in the general population. The occurrence of subclinical infection and overt disease among the evaluated individuals was correlated with the spatio-temporal pattern of leprosy.Principal Findings:The pattern of leprosy cases showed significant spatio-temporal heterogeneity (p < 0.01). Considering 499 mapped cases, we found spatial clusters of high and low detection rates and spatial autocorrelation of individual cases at fine spatio-temporal scales. The relative risk of contracting leprosy in one specific cluster with a high detection rate is almost four times the risk in the areas of low detection rate (RR = 3.86; 95% CI = 2.26-6.59; p < 0.0001). Eight new cases were detected among 302 evaluated household contacts: two living in areas of clusters of high detection rate and six in hyperendemic census tracts. Of 188 examined students, 134 (71.3%) lived in hyperendemic areas, 120 (63.8%) were dwelling less than 100 meters of at least one reported leprosy case, 125 (66.5%) showed immunological evidence (positive anti-PGL-I IgM titer) of subclinical infection, and 9 (4.8%) were diagnosed with leprosy (8 within 200 meters of a case living in the same area).Conclusions/Significance:Spatial analysis provided a better understanding of the high rate of early childhood leprosy transmission in this region. These findings can be applied to guide leprosy control programs to target intervention to high risk areas.

Copyright information:

© 2014 Barreto et al.

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