How accurately can we assess zoonotic risk?

Abstract Identifying the animal reservoirs from which zoonotic viruses will likely emerge is central to understanding the determinants of disease emergence. Accordingly, there has been an increase in studies performing zoonotic ‘risk assessment’. Herein, we demonstrate that the virological data on which these analyses are conducted are highly biased, incomplete, and rapidly changing with ongoing virus discovery. We document a marked change in the composition of virus data sets, with the increased sampling and metagenomic sequencing of seemingly healthy wildlife reducing the proportion of viruses that are likely zoonotic as well as those associated with overt disease. We also show that the available data are incomplete, with significantly more viruses described in the literature than ratified by the International Committee on the Taxonomy of Viruses (ICTV). Finally, we document unequal study effort toward those viruses perceived as important for human and animal health, inflating the proportion of seemingly zoonotic viruses. Together, these shortcomings suggest that attempts to assess zoonotic risk using available virological data are likely to be inaccurate and largely identify those host taxa that have been studied most extensively. We suggest that virus surveillance at the human-animal interface may be a productive approach