Abstract
Host jumps-defined as the process by which a pathogen establishes sustained transmission in novel hosts-are threats to human and animal welfare, but anticipating which pathogen will be the next to successfully host jump remains elusive. A spillover event must precede a host jump, and so spillover rate is thought to be related to risk. However, nonendemic pathogens that spill over frequently have demonstrated a poor ability to host jump from any given spillover. So which is riskier, pathogens that spill over rarely or commonly? Applying a Bayesian framework to a general model of host jump risk, we show that 1) the riskiest pathogens can be those that spill over at low, intermediate, or high rates, and 2) as the rate of spillover gets large, the information gained from past spillovers is exactly counterbalanced by the increased number of future spillovers. Taken together, this means that spillover rate has little to no value in explaining host jump risk. Rather, we show that novel pathogens (i.e., pathogens with a relatively short history of spilling over in their current form) are substantially more likely to result in host jumps than pathogens that have had long-associated opportunities for spillover into the novel host. Notably, a pathogen might be thought of as novel if spillover only recently became possible, or if it recently underwent substantial evolutionary change. We therefore propose that the length of historical association, but not spillover rate, will be an important predictor of host jump risk.