Ruminants Epidemiology, Spatial Clustering and Multivariate Risk Modelling of Cutaneous Leishmaniasis in District...

Cutaneous leishmaniasis (CL) remains a significant public health concern in endemic regions of Pakistan, particularly in ecologically diverse and resource-limited areas. This study aimed to investigate the epidemiology, risk factors, lesion characteristics, seasonal trends and spatial distribution of CL in District Bajaur, Khyber Pakhtunkhwa, Pakistan.

A cross-sectional observational study was conducted in 2022, including clinically suspected and laboratory-confirmed CL cases from all nine tehsils of District Bajaur. Demographic information, lesion characteristics (site, type and number), season of presentation and regional distribution were collected using a structured questionnaire. Statistical analyses included univariate and multivariate logistic regression, multinomial regression, Poisson regression, stratified analyses and interaction modelling. Spatial clustering was evaluated using Z-scores, Moran's I statistics and GIS-based risk mapping.

CL prevalence was significantly higher among males, younger individuals, unmarried participants and during the summer season. Lesions were predominantly located on exposed body parts, especially the hands and face, with dry lesions and single-lesion presentations being most common. Multivariate analysis identified male gender, younger age, unmarried status, summer season, dry lesion type and single lesions as independent risk factors. Stratified and interaction analyses indicated an elevated risk among young males during the summer. Spatial analysis revealed significant clustering of cases, with Khar, Loe Mamund and Salarzai identified as high-risk tehsils. A clinician-friendly risk scoring system was developed to estimate individual infection probability.

CL in District Bajaur is influenced by a complex interaction of demographic, clinical, seasonal and spatial factors. These findings emphasize the importance of targeted surveillance, vector control strategies and risk-based interventions to reduce disease burden in endemic regions.