Fig 4. Partial dependence from random forest models in predicting severe virulence.

Predicted probability of classifying virulence as ‘severe’ for each of the most informative risk factors in random forest models applied to all known human RNA viruses and zoonotic viruses only (primary tissue tropism, any known neural tropism, any known renal tropism, level of human-to-human transmissibility, primary transmission route, and any known vector-borne transmission). Predicted probabilities are marginal, i.e., averaging over any effects of other predictors. Boxes denote distribution of probabilities across 200 random forest models with alternative training/test partitions, with heavy lines denoting median probability. Dashed line denotes raw prevalence of ‘severe’ virulence rating among the respective training datasets. Colour key denotes predictor variable type as in Fig 3, i.e., blue = tissue tropism, green = transmissibility, red = transmission route. Supporting data are available via figshare: 10.6084/m9.figshare.7406441.v3 (https://figshare.com/articles/Data_and_supporting_R_script_for_Tissue_Tropism_and_Transmission_Ecology_Predict_Virulence_of_Human_RNA_Viruses/7406441/3).