Spatiotemporal cluster analysis and predicting lumpy skin disease outbreaks in cattle in selected zones of Oromia region, Ethiopia from 2008-2022

Abstract

Lumpy skin disease (LSD) is a viral infection that affects cattle, causing significant economic loss and posing a threat to food security. This is a study in the selected zones of Oromia Region, Ethiopia, spanning 15 years (2008–2022), aimed to identify spatiotemporal distribution, cluster of LSD outbreaks, and to project potential future outbreaks for the years from 2023–2027. The findings revealed 457 outbreaks, 50,025 recorded cases with 879 fatalities. The study analyzed LSD outbreak spatial cluster (Moran I, Getis Ord Gi and ST-model), time series data using classical additive and STL decomposition, and four forecasting models (ARIMA, SARIMA, ETS, and SL+random walk) were used. Seven hotspots emerged predominantly in the northwestern and eastern segments of the Arsi zone. The study further pinpointed two spatial and twelve spatiotemporal clusters, including all distinct temporal clusters between January 1, 2009, and December 31, 2009, characterized by a relative risk (RR) of 2.68, a log likelihood ratio (LLR) of 16.23, and a P-value of 0.001. Seasonal trends indicate that LSD peaks during the wet months from September to December and is low in cold dry period from March to May. Among the forecasting methodologies evaluated, the SARIMA (1, 1, 1) (0, 2, 3) [12] model was best fit its counterparts, as reflected by the lowest RMSE, MA, and MASE, suggesting enhanced forecast accuracy for LSD outbreaks from 2023 to 2027. These findings provided valuable insights into the dynamics of the disease and can inform the development of effective LSD control and prevention strategies in the study zones.