A host shifting event occurs when a strain that was previously zoonotic begins to circulate exclusively among the new host species.Pathogen transfer is most likely to occur between species which are frequently in close contact with each other. It can also occur indirectly between species with less frequent contact if facilitated by an intermediary species; for example, a reservoir species may transfer the virus to a vector species, which in turn transfers the virus to humans. The degree of phylogenetic relatedness between host species also influences the likelihood that a pathogen is transmitted between them, likely because of the similarity of the hosts immunological defenses; for example, most human zoonotic transmissions come from other species of mammals. Pathogens of more distantly related species, on the other hand, such as plant viruses, may not be capable of infecting humans at all. Other factors influencing transmission rates include geographic proximity and intraspecies behaviors. Due to climate change and land use expansion, the risk of viral spillover is predicted to significantly increase. Prevalence and control
Cross-species transmission is the most significant cause of disease emergence in humans and other species. Wildlife zoonotic diseases of microbial origin are also the most common group of human emerging diseases, and CST between wildlife and livestock has appreciable economic impacts in agriculture by reducing livestock productivity and imposing export restrictions. This makes CST of major concern for public health, agriculture, and wildlife management.
The process of using genetic markers to estimate CST rates should take into account several important factors to reduce bias. One is that the phylogenetic tree constructed in the analysis needs to capture the underlying epidemiological process generating the tree. The models need to account for how the genetic variability of a pathogen influences a disease in a species, not just general differences in genomic structure. Two, the strength of the analysis will depend on the amount of mutation accumulated since the pathogen was introduced in the system. This is due to many models using the number of mutations as an indicator of CST frequency. Therefore, efforts are focused on estimating either time since the introduction or the substitution rate of the marker (from laboratory experiments or genomic comparative analysis). This is important not only when using the MPR method but also for Likelihood approaches that require an estimation of the mutation rate. Three, CST will also affect disease prevalence in the potential host, so combining both epidemiological time series data with genetic data may be an excellent approach to CST study

Bayesian analysis
Bayesian frameworks are a form of maximum likelihood-based analyses and can be very effective in cross-species transmission studies. Bayesian inference of character evolution methods can account for phylogenetic tree uncertainty and more complex scenarios, with models such as the character diffusion model currently being developed for the study of CST in RNA viruses. A Bayesian statistical approach presents advantages over other analyses for tracking CST origins.