Molecular epidemiological and spatiotemporal analysis of lumpy skin disease outbreaks in cattle from Karnataka, India

Lumpy Skin Disease (LSD), is a re-emerging transboundary disease of cattle, which has severely impacted India's livestock population. This study investigates its molecular epidemiology, spatial patterns, and risk factors in Karnataka from 2021-2024.

In this study, total of 1,353 different types of samples from 451 suspected LSD cases were analyzed using PCR. Spatial clustering was assessed using QGIS and GeoDa. Risk factor analysis and phylogenetic studies were performed to identify susceptible groups and viral lineages.

Among the analyzed samples, scabs showed the highest positivity rate at 83.6%, followed by nasal swabs at 80.9%, and blood samples at 76.9%, underscoring the utility of nasal swabs as a simple and effective non-invasive clinical sample for diagnosis and clinical surveillance. Spatial analysis conducted with QGIS (v3.32.2) and GeoDa (v1.22) identified strong spatial autocorrelation and consistent clustering of cases in densely populated livestock areas, driven by environmental factors and mechanical vectors, including blood-feeding arthropods like flies (Stomoxys calcitrans, Haematobia irritans) and ticks (Rhipicephalus and Amblyomma species). Vaccination campaigns achieved near 100% coverage in most districts by 2022, substantially reducing LSD-related mortality rate from 1.45% to negligible levels in 2024. Risk factor analysis identified cattle aged 1 to 5 years and females as most susceptible, with exotic breeds exhibiting 2.1-2.6 times higher odds of infection than indigenous breeds. Molecular studies unveiled a genetically stable lumpy skin disease virus strain unique to Karnataka, consistent with the low mutation rate of DNA viruses.

These findings emphasize that, despite vaccination success, persistent hotspots and vulnerable cattle groups remain. Therefore, region-specific strategies such as targeted vector control, robust molecular surveillance, and GIS-based early outbreak alerts are necessary for LSD control in endemic regions. This study also highlights how the integration of combining molecular diagnostics, epidemiological modeling, and spatial analytics can strengthen LSD surveillance and redefine disease control strategies, ultimately mitigating its socio-economic impact.