Identification of urban leprosy clusters

Area of Science:

• Public Health
• Epidemiology
• Geographic Information Systems (GIS)

Background:

• Urban overpopulation and migration contribute to disordered growth and concentrated populations in precarious conditions.
• Leprosy remains a public health concern, necessitating spatial analysis to understand transmission patterns.
• Identifying disease clusters is crucial for effective resource allocation and intervention strategies.

Purpose of the Study:

• To identify potential clusters of individuals with a history of leprosy in São José do Rio Preto, Brazil, using residential grouping.
• To analyze the spatial and temporal distribution of leprosy cases within the urban environment.
• To pinpoint high-risk areas for leprosy transmission and inform public health strategies.

Main Methods:

• A population-based, descriptive, ecological study was conducted.
• Geoprocessing techniques, including MapInfo and CrimeStat, were employed for spatial analysis.
• Space-time analysis evaluated 425 leprosy cases treated between 1998 and 2010, defining clusters as concentrations of at least 8 individuals within 300 meters.

Main Results:

• Ten distinct leprosy case clusters were identified, encompassing 98 (23.1%) of the geocoded cases.
• A second-order cluster region, considered high-risk, contained 129 cases (30.3%).
• Analysis also included the year of treatment initiation and clinical leprosy forms.

Conclusions:

• The study successfully identified ten spatial clusters of leprosy cases in São José do Rio Preto.
• A significant high-risk area for new leprosy cases was pinpointed, guiding future public health efforts.
• Spatial analysis is a valuable tool for understanding and controlling leprosy in urban settings.