African Swine Fever (ASF) is a highly contagious hemorrhagic viral disease of domestic and wild pigs. ASF has led to huge economic loss and social impact worldwide. The biological mechanism of ASF’s infections is still not fully understood, and the lack of preventative options at the individual level further complicates this major global health challenge. In this paper, we propose a novel method to model the spread of ASF in China by integrating the data of pork import/export, transportation networks, and port distribution centers. We first empirically analyze the overall patterns of ASF spread and performs extensive experiments to evaluate the efficacy of a number of distance measures. These empirical analyses show that the arrival of ASF is not purely based on the geographic distance from existing infected regions. The pork supply-demand patterns have clearly influenced the spread of ASF, which cannot be well explained by conventional geographical distance and the recent effective distance methods. Predictions based on the new distance measure achieve better performance in predicting the disease spreading among Chinese provinces and thus have the potential to enable more proactive and accurate deployment of interventions.