Spatiotemporal Distribution Characteristic and Influencing Factors of African Swine Fever Outbreaks (2018/8-2019/12) in China.

ABSTRACT: African swine fever (ASF), a highly lethal viral disease with no effective vaccines or treatments, poses a significant threat to the global pig industry. Since its first report in China in August 2018, it has spread rapidly, severely impacting China's pig industry. This study developed a Bayesian spatiotemporal model to explore ASF's spatiotemporal patterns, assess relative risk (RR), and identify key factors, aiming to inform targeted prevention strategies. Data (disease-related deaths, pig inventory, GDP, temperature, and 6 other factors) were collected from 31 mainland Chinese provinces from August 2018 to December 2019. The INLA algorithm estimated parameters, with the optimal model selected via DIC and WAIC. Multicollinearity was addressed using VIF and Spearman's correlation coeffici

SUBMITTER: Li J 

PROVIDER: S-EPMC12517988 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature