Exploring clustering of leprosy in the Comoros and Madagascar: A geospatial analysis

Abstract

Objectives: To identify patterns of spatial clustering of leprosy. Design: We performed a baseline survey for a trial on post-exposure prophylaxis for leprosy in Comoros and Madagascar. We screened 64 villages, door-to-door, and recorded results of screening, demographic data and geographic coordinates. To identify clusters, we fitted a purely spatial Poisson model using Kulldorff’s spatial scan statistic. We used a regular Poisson model to assess the risk of contracting leprosy at the individual level as a function of distance to the nearest known leprosy patient. Results: We identified 455 leprosy patients; 200 (44.0%) belonged to 2735 households included in a cluster. Thirty-eight percent of leprosy patients versus 10% of the total population live ≤25 m from another leprosy patient. Risk ratios for being diagnosed with leprosy were 7.3, 2.4, 1.8, 1.4 and 1.7, for those at the same household, at 1–<25 m, 25–<50 m, 50–<75 m and 75–<100 m as/from a leprosy patient, respectively, compared to those living at ≥100 m. Conclusions: We documented significant clustering of leprosy beyond household level, although 56% of cases were not part of a cluster. Control measures need to be extended beyond the household, and social networks should be further explored.

Keywords

• Clustering
• Leprosy
• Active case finding
• Spatial analysis