Abstract Tick-borne diseases (TBDs) pose a major public health concern in tropical regions, where co-infections and pathogen interactions complicate disease control. Understanding how these interactions vary across vertebrate hosts and tick vectors, and their impact on disease transmission, is crucial for developing effective intervention strategies. This study examined the effects of pathogen interactions within vertebrate hosts and tick vectors on the transmission dynamics of tick-borne pathogens (TBPs) in Ogun State, Nigeria, testing the hypothesis that these interactions differ between tick vectors and cattle hosts (i.e., species dependence) and thereby influence transmission. A comprehensive field and laboratory study was conducted across three agroecological zones of Ogun State, involving 1771 ticks from 11 cattle breeds and 21 herds, and analyzing 225 cattle blood samples. Pathogen prevalence was determined using genus-specific end-point polymerase chain reaction (PCR) assays for Anaplasma, Rickettsia, Babesia, Borrelia, and Coxiella. Interaction dynamics were analyzed using Yule's Q statistic for correlation assessment and a network approach to map interactions across tick species and cattle breeds. Additionally, mathematical modeling simulated disease transmission dynamics under varying pathogen interaction scenarios, enhancing our understanding of their impact on epidemiological trends. Significant differences in pathogen prevalence and interaction patterns emerged between vertebrate hosts and tick vectors. Ticks showed a lower pathogen prevalence (25.35%) and simpler co-infection patterns, while cattle exhibited high infection rates with complex co-infection dynamics. Notably, synergistic interactions among pathogens such as Anaplasma, Rickettsia, and Babesia were common in cattle, increasing pathogen load and transmission potential. In contrast, ticks displayed competitive interactions that reduced co-infection rates and potentially limited transmission. Modeling results indicated that synergistic interactions among pathogens in cattle, alongside competitive interactions in ticks, collectively maximized disease prevalence over the 6-month modeling period. These findings highlight that pathogen interactions are strongly species-dependent, significantly influencing TBD epidemiology. The integration of empirical data and modeling offers a comprehensive framework for predicting disease spread and developing targeted control measures in tropical settings.