Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2

Intermediate host species provide a crucial link in the emergence of zoonotic infectiousdiseases, serving as a population where an emerging pathogen can mutate to becomehuman-transmissible. Identifying such species is thus a key component of predictingand possibly mitigating future epidemics. Despite this importance, intermediate hostspecies have not been investigated in much detail, and have generally only beenidentified by testing for the presence of pathogens in multiple candidate species. In thispaper, we present a mathematical model able to identify likely intermediate hostspecies for emerging zoonoses based on ecological data for the candidates andepidemiological data for the pathogen. Since coronaviruses frequently emerge throughintermediate host species and, at the time of writing, pose an urgent pandemic threat,we apply the model to the three emerging coronaviruses of the twenty-first century,accurately predicting palm civets as intermediate hosts for SARS-CoV-1 anddromedary camels as intermediate hosts for MERS. Further, we suggest mink,pangolins, and ferrets as intermediate host species for SARS-CoV-2. With the capacityto evaluate intermediate host likelihood among different species, researchers canfocus testing for possible infection sources and interventions more effectively.