Geographic information systems and applied spatial statistics are efficient tools to study Hansen's disease (leprosy) and to determine areas of greater risk of disease.
Applied Spatial Statistics used in conjunction with geographic information systems (GIS) provide an efficient tool for the surveillance of diseases. Here, using these tools we analyzed the spatial distribution of Hansen's disease in an endemic area in Brazil. A sample of 808 selected from a universe of 1,293 cases was geocoded in Mossoró, Rio Grande do Norte, Brazil. Hansen's disease cases were not distributed randomly within the neighborhoods, with higher detection rates found in more populated districts. Cluster analysis identified two areas of high risk, one with a relative risk of 5.9 (P = 0.001) and the other 6.5 (P = 0.001). A significant relationship between the geographic distribution of disease and the social economic variables indicative of poverty was observed. Our study shows that the combination of GIS and spatial analysis can identify clustering of transmissible disease, such as Hansen's disease, pointing to areas where intervention efforts can be targeted to control disease.
Queiroz
José Wilton
JW
Health Post-Graduate Program, Department of Internal Medicine, Health Science Center; Department of Biochemistry, Bioscience Center, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil. jwq@supercabo.com.bn
Dias
Gutemberg H
GH
Nobre
Maurício Lisboa
ML
De Sousa Dias
Márcia C
MC
Araújo
Sérgio F
SF
Barbosa
James D
JD
Bezerra da Trindade-Neto
Pedro
P
Blackwell
Jenefer M
JM
Jeronimo
Selma M B
SM
D001938:Brazil / Q000453:epidemiology; D019353:Endemic Diseases; D040362:Geographic Information Systems; D006801:Humans; D007918:Leprosy / Q000453:epidemiology*; D012307:Risk Factors; D012959:Socioeconomic Factors; D013997:Time Factors