British Leprosy Relief Association
The use of Geographical Information System (GIS) to improve active leprosy case finding campaigns in the Municipality of Mossoró, Rio Grande do Norte State, Brazil
M.C.F. de Souza Dias et al.
GIS System for leprosy case finding in Brazil
de Souza DiasMárcia Célia Freitasa
aMunicipal Health Secretariat of Mossoró, Brazil
bRio Grande do Norte State University, Mossoró, Brazil
cGiselda Trigueiro Hospital, Natal, Brazil
Correspondence to: M.C.F de Souza Dias, Josefina Pinto St., 46 – Santo Antônio; Zip Code: 59611-290 – Mossoró/RN – Brazil (Tel: +55 84 3316 9873; Fax: +55 84 3317 5233; e-mail: firstname.lastname@example.org)
There is a high incidence of leprosy in the municipality of Mossoró, Rio Grande do Norte state, where the detection coefficient has risen from 2.78/10 000 population in 1998 to 5.14 in 2004. While cases have been registered throughout the urban area, the disease is concentrated in select neighbourhoods. This study was undertaken using Geographical Information System (GIS) with the objective of defining low-cost, effective strategies to control leprosy. The land registry map of the city, Ikonos satellite images and the SINAN (National Morbidity Notification Information System) database were used as the cartographical basis for the study. The sample for the leprosy mapping was drawn from the 358 new cases of the disease diagnosed in the municipality between 1998 and 2002. The houses of 281 patients were located (78.5% of the total) and their addresses geo-referenced using a GPS handheld device. Subsequently, geographical analysis was carried out using ArcView 9.0 software showing predominant concentration of cases in the neighbourhoods of Barrocas, Santo Antônio, Bom Jardim and Paredões. This mapping served as the basis for four active case finding campaigns conducted in the most highly concentrated areas between March and September of 2005. Campaigns guided by spatial analysis led to the diagnosis of 104 new cases of the disease (50% of the total number of new cases detected in the municipality in 2005). The use of GIS in leprosy diagnosis has shown to be extremely effective, providing a clear visual understanding of the distribution of the disease in the municipality, which results in targeted interventions and important cost reductions in leprosy control activities.