This study characterized and compared the spatiotemporal dynamics of animal and livestock disease frequency in Shashemene District, West Arsi, Oromia, Ethiopia. The work aimed to quantify spatial and temporal disease distributions, classify events into sporadic, endemic, epidemic, and pandemic-candidate patterns, estimate key epidemiological parameters including incidence and effective reproduction numbers (iR/iisube/sub/i), and identify environmental and connectivity-related drivers of transmission. A retrospective spatiotemporal observational design was applied, synthesizing five to ten years of surveillance, laboratory, and farmer-reported data from district records over the period 2014 to 2023. A total of 500 recorded disease events across cattle, sheep, goats, poultry, and equids were analyzed at kebele-level resolution using Bayesian hierarchical modeling integrated with Geographic Information Systems and time-varying iR/iisube/sub/i estimation. The analysis demonstrated that disease events were significantly concentrated during the wet season, accounting for 64.2% of cases, compared to 35.8% during the dry season. Sheep pox, 19.8%, and lumpy skin disease, 18.2%, consistently emerged as the most frequent conditions. Epidemic patterns were strongly associated with livestock movement and market connectivity, with odds ratios ranging from 1.78 to 2.12 and iR/iisube/sub/i values peaking at 2.05 in high-traffic trade corridors, compared to iR/iisube/sub/i = 1.52 in lower-frequency areas. Endemic patterns were linked to high animal density, limited veterinary infrastructure, and restricted access to services. Environmental drivers, particularly rainfall and temperature, showed a positive correlation with disease incidence, r = 0.324, especially for vector-borne and soil-borne pathogens. Overall, the findings established livestock mobility, seasonal climatic variability, and network connectivity as the principal drivers of disease dynamics in the district. The study concluded that transitioning from reactive responses to proactive, climate-sensitive, and network-informed interventions was critical to reducing disease burden and strengthening evidence-based veterinary public health policy.
Kinfe Kibebew (Fri,) studied this question.