| Literature DB >> 28587683 |
Leonardo Augusto Kohara Melchior1,2, Andréia Fernandes Brilhante2, Francisco Chiaravalloti-Neto3,4.
Abstract
BACKGROUND: Acre has reported the highest incidence of American cutaneous leishmaniasis (ACL) in Brazil in recent years. The present study seeks to identify high and low risk agglomerations of ACL in space and space-time during the period from 2007 to 2013 in Acre, and also to characterize the occurrence of the disease in time and according to sociodemographic variables.Entities:
Keywords: Acre; Brazil; Cutaneous leishmaniasis; Geographical information system; Scan statistics; Spatial analysis
Mesh:
Year: 2017 PMID: 28587683 PMCID: PMC5461694 DOI: 10.1186/s40249-017-0311-5
Source DB: PubMed Journal: Infect Dis Poverty ISSN: 2049-9957 Impact factor: 4.520
Fig. 1Map of the study area of Acre and its municipalities and territorial divisions in meso- and micro-regions
Distribution of ACL cases by incidence, number of cases and temporal tendency in the meso-regions, micro-regions, municipalities, and the state of Acre as a whole, 2007 – 2013
| Locality | ri |
| % | ARI | 95% | Tendency |
|---|---|---|---|---|---|---|
| State | ||||||
| Acre | 12.4 | 6 257 | 100 | -1.2 | -1.9; -0.5 | Diminishing |
| Meso-region | ||||||
| Acre Valley | 13.6 | 4 904 | 78 | -1.8 | -2.7; -0.9 | Diminishing |
| Juruá Valley | 9.4 | 1 353 | 22 | +0.2 | -2.9; +3.3 | Stationary |
| Micro-region and municipalities | ||||||
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| Assis Brasil | 89.1 | 371 | 6 | -2.8 | -4.6; -1.1 | Diminishing |
| Xapuri | 81.9 | 903 | 14 | -0.8 | -1.2; -0.4 | Diminishing |
| Brasiléia | 29.4 | 434 | 7 | +0.7 | -2.4; +3.9 | Stationary |
| Epitaciolândia | 12.4 | 129 | 2 | +1.7 | -0.7; +4.0 | Stationary |
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| 17 |
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| Manoel Urbano | 29.8 | 163 | 3 | -3.0 | -5.6; -0.4 | Diminishing |
| Santa Rosa do Purus | 18.5 | 60 | 1 | -2.2 | -16.6; +12.3 | Stationary |
| Sena Madureira | 31.0 | 813 | 13 | +3.3 | +1.5; +5.1 | Increasing |
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| 11 |
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| Feijó | 16.8 | 380 | 6 | -2.6 | -7.6; +2.4 | Stationary |
| Jordão | 19.3 | 89 | 1 | -2.9 | -10.1; +4.3 | Stationary |
| Tarauacá | 8.8 | 215 | 3 | -4.1 | -15.8; +7.6 | Stationary |
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| 11 |
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| Cruzeiro do Sul | 3.1 | 169 | 3 | +7.8 | -1.0; +16.5 | Stationary |
| Mâncio Lima | 17.8 | 189 | 3 | +6.6 | +4.3; +9.0 | Increasing |
| Marechal Thaumaturgo | 21.9 | 221 | 4 | -2.7 | -7.9; +2.5 | Stationary |
| Porto Walter | 4.8 | 31 | 0 | -19.4 | -29.4; -9.4 | Diminishing |
| Rodrigues Alves | 5.9 | 59 | 1 | +7.1 | -3.8; +17.9 | Stationary |
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| 32 |
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| Acrelândia | 12.4 | 108 | 2 | -5.6 | -12.0; +0.7 | Stationary |
| Bujari | 30.8 | 169 | 3 | -5.9 | -6.3; -5.5 | Diminishing |
| Capixaba | 24.0 | 153 | 2 | -1.9 | -14.3; +10.6 | Stationary |
| Plácido de Castro | 9.7 | 120 | 2 | -7.2 | -16.6; +2.3 | Stationary |
| Porto Acre | 14.5 | 151 | 2 | -11.2 | -14.8; -7.7 | Diminishing |
| Rio Branco | 5.5 | 1 264 | 20 | -3.3 | -5.6; -1.1 | Diminishing |
| Senador Guiomard | 4.7 | 66 | 1 | -1.9 | -11.3; +7.5 | Stationary |
ri = rate of incidence (cases/10 000 inhabitants/year); n = number of cases in the period; (%) = state contribution (percentage); ARI = annual rate of increase (percentage);95% CI = confidence interval of 95% (percentage); Tendency = interpretation of the tendency; the names of the micro-regions and their results are in bold and italic
Fig. 2Locations of the detected clusters of ACL cases, based on the a) space-time analysis and b) purely spatial analysis, Acre state, 2007 – 2013
Fig. 3Distribution of ACL incidence in the micro-regions of Acre by sex and age group, 2007 – 2013