Metadata about: Despite massive investment in research on reservoirs of emerging pathogens, it remains difficult to rapidly identify the wildlife origins of novel zoonotic viruses. Viral surveillance is costly but rarely optimized using model-guided prioritization strategies, and predictions from a single model may be highly uncertain. Here, we generate an ensemble of eight network- and trait-based statistical models that predict mammal-virus associations, and we use model predictions to develop a set of priority recommendations for sampling potential bat reservoirs and intermediate hosts for SARS-CoV-2 and related betacoronaviruses. We find over 200 bat species globally could be undetected hosts of betacoronaviruses. Although over a dozen species of Asian horseshoe bats (Rhinolophus spp.) are known to harbor SARS-like coronaviruses, we find at least two thirds of betacoronavirus reservoirs in this bat genus might still be undetected. Although identification of other probable mammal reservoirs is likely beyond existing predictive capacity, some of our findings are surprisingly plausible; for example, several civet and pangolin species were highlighted as high-priority species for viral sampling. Our results should not be over-interpreted as novel information about the plausibility or likelihood of SARS-CoV-2’s ultimate origin, but rather these predictions could help guide sampling for novel potentially zoonotic viruses; immunological research to characterize key receptors (e.g., ACE2) and identify mechanisms of viral tolerance; and experimental infections to quantify competence of suspected host species.

About: Despite massive investment in research on reservoirs of emerging pathogens, it remains difficult to rapidly identify the wildlife origins of novel zoonotic viruses. Viral surveillance is costly but rarely optimized using model-guided prioritization strategies, and predictions from a single model may be highly uncertain. Here, we generate an ensemble of eight network- and trait-based statistical models that predict mammal-virus associations, and we use model predictions to develop a set of priority recommendations for sampling potential bat reservoirs and intermediate hosts for SARS-CoV-2 and related betacoronaviruses. We find over 200 bat species globally could be undetected hosts of betacoronaviruses. Although over a dozen species of Asian horseshoe bats (Rhinolophus spp.) are known to harbor SARS-like coronaviruses, we find at least two thirds of betacoronavirus reservoirs in this bat genus might still be undetected. Although identification of other probable mammal reservoirs is likely beyond existing predictive capacity, some of our findings are surprisingly plausible; for example, several civet and pangolin species were highlighted as high-priority species for viral sampling. Our results should not be over-interpreted as novel information about the plausibility or likelihood of SARS-CoV-2’s ultimate origin, but rather these predictions could help guide sampling for novel potentially zoonotic viruses; immunological research to characterize key receptors (e.g., ACE2) and identify mechanisms of viral tolerance; and experimental infections to quantify competence of suspected host species.

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