Optimising predictive models to prioritise viral discovery in zoonotic reservoirs.

ABSTRACT: Despite the global investment in One Health disease surveillance, it remains difficult and costly to identify and monitor the wildlife reservoirs of novel zoonotic viruses. Statistical models can guide sampling target prioritisation, but the predictions from any given model might be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use the bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of probable reservoir hosts. In early 2020, we generated an ensemble of eight statistical models that predicted host-virus associations and developed priority sampling recommendations for potential bat reservoirs of betacoronaviruses and bri

SUBMITTER: Becker DJ 

PROVIDER: S-EPMC8747432 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature