The outbreak of infectious diseases is one of the major challenges in the farming and aquaculture industries, causing significant economic losses. Recent advances in high-throughput sequencing technologies have provided detailed analyses of how these diseases affect host animals at multiple molecular levels. Multi-omics approaches allow for a comprehensive investigation of complex interactions, providing a holistic view of the interrelationships between the biomolecules and their functions. The integration and analysis of these heterogeneous datasets are essential steps towards generating knowledge in the framework of precision livestock and aquaculture. This research focused on studies that use multi-omics data integration rather than those that apply multiple omics approaches separately without integration. Moreover, it summarises recent publications addressing the application of integrative multi-omics techniques in economically relevant livestock species such cattle, pigs, goats, sheep, and aquatic organisms affected by diverse pathogens (virus, bacteria, and fungi, among others). This study provides an up-to-date overview of the integration methods used in this field, the omic tools available for different species, and the molecular mechanisms underlying host responses to infection. Our findings highlight the fact that multi-omics integration improves our understanding of disease mechanisms. However, this approach presents challenges due to inconsistent methodology and a lack of rigour and standardization in statistical analysis, particularly in farming and aquaculture studies.