Tissue tropism and transmission ecology predict virulence of human RNA viruses.

ABSTRACT: Novel infectious diseases continue to emerge within human populations. Predictive studies have begun to identify pathogen traits associated with emergence. However, emerging pathogens vary widely in virulence, a key determinant of their ultimate risk to public health. Here, we use structured literature searches to review the virulence of each of the 214 known human-infective RNA virus species. We then use a machine learning framework to determine whether viral virulence can be predicted by ecological traits, including human-to-human transmissibility, transmission routes, tissue tropisms, and host range. Using severity of clinical disease as a measurement of virulence, we identified potential risk factors using predictive classification tree and random forest ensemble models. The random for

SUBMITTER: Brierley L 

PROVIDER: S-EPMC6879112 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature