Introduction: Livestock movement patterns play a crucial role in animal and public health management, disease transmission and sustainable livestock farming. Understanding these patterns is vital for disease surveillance and preventing the spread of animal diseases. Study Area: This study was conducted in the far north-eastern region of KwaZulu-Natal (KZN) province, South Africa, with Eswatini bordering to the west and Mozambique to the north. The study area is located at a wildlife–livestock interface and includes sections classified as a foot-and-mouth disease (FMD) control zone. Animal and animal product movements within, into and out of the area are restricted by state veterinary-issued movement permits. Aims: The study aimed to quantitatively describe livestock movement characteristics within, into and out of the study area and identify potential hubs for disease transmission. Study Design and Sampling Strategy: Data sources included official animal movement permit records (2015–2018) from the KZN Department of Agriculture and Rural Development, and the data are obtained via face-to-face interviews with livestock traders (August to November 2020). Traders' data were used to complement the interpretation of the permit dataset and to understand the livestock movement patterns, especially from the perspective of traders who operate from our study area. The permit data offered a detailed record of official livestock movements over multiple years, enabling us to identify the movement trends. In contrast, the face-to-face interviews provided real-time insights from traders regarding informal movement trends and disruptions not reflected in the permit data. The permit dataset was used to construct stratified animal movement networks by species using social network analysis (SNA), treating dip tanks (origins) and the destination locations (municipalities, districts or provinces) as two disjoint sets before being projected into a one-mode network. Bipartite-specific sta