ABSTRACTS SUBMISSION 248_Joy Vaz ‐ University of Georgia ‐ États‐Unis [email protected] Parasite and host traits predict the zoonotic risk of protozoa Joy Vaz, Barbara A. Han, John M. Drake Odum School of Ecology, University of Georgia, Athens, Georgia, USA; Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, USA; Cary Institute of Ecosystem Studies, Millbrook, New York, USA Protozoan zoonoses such Chagas disease and leishmaniasis remain endemic in large parts of the world, exacerbating social inequity and contributing heavily to the global burden of infectious disease. Novel protozoa species which have emerged from wildlife to humans in the recent decades (e.g., Plasmodium knowlesi, a causal agent of malaria) have proven difficult to control. Our ability to anticipate and prevent future emerging disease threats relies on identifying the characteristics of zoonotic pathogens and targeting surveillance efforts accordingly. While several studies have profiled the traits of zoonotic viruses, protozoa have received limited attention. We compiled a dataset of protozoa species which incorporates both parasite and host traits, including information on community structure and importance within a host‐parasite bipartite network. Using a machine learning algorithm, extreme gradient boosting, we distinguished zoonotic from non‐zoonotic protozoa with 85% accuracy. Our model found that traits of generalist protozoa (e.g., broad tissue tropism, high network centrality, multiple transmission modes) were most useful for predicting zoonotic status, compared to intrinsic biological traits (e.g., morphology), environmental traits (e.g., temperature), or host‐ related traits (e.g., life history). We ranked the zoonotic potential of protozoa species currently not known to be zoonotic based on their trait similarity to known zoonotic protozoa. Here we report parasitic protozoa species of wild mammals which are most likely to be undiscovered sources of current or future zoonoses, identifying them as priority targets for surveillance. 1. What is your pathogen? Multiple options possible (e.g. if working on coinfections) Coronavirus : Middle‐East Respiratory Syndrome Coronavirus Protozoan : Trypanosoma brucei, Toxoplasma gondii, Plasmodium brasilianum, Trypanosoma cruzi, Entamoeba coli, Balantidium coli, Trypanosoma rangeli, Leishmania shawi, Entamoeba chattoni, Plasmodium inui, Plasmodium cynomolgi, Plasmodium knowlesi, Sarcocystis hominis, 2. On a scale of 1‐5 is your work mostly eco/epidemiological or evolutionary? 1 (100% eco/epidemiological) 3. On a scale of 1‐5 is your work mostly theoretical or experimental/empirical? 4 Extraction du 10/5/2021 .