Epidemiological Feedbacks Affect Evolutionary Emergence of Pathogens

The evolutionary emergence of new pathogens via mutation poses a considerable risk to human and animal populations. Most previous studies have investigated cases where a potentially pandemic strain emerges though mutation from an initial maladapted strain (i.e., its basic reproductive ratio R-0 < 1). However, an alternative (and arguably more likely) cause of novel pathogen emergence is where a weakly adapted strain (with R-0 approximate to 1) mutates into a strongly adapted strain (with R-0 >> 1). In this case, a proportion of the host susceptible population is removed as the first strain spreads, but the impact this feedback has on emergence of mutated strains has yet to be quantified. We produce a model of pathogen emergence that takes into account changes in the susceptible population over time and find that the ongoing depletion of susceptible individuals by the first strain has a drastic effect on the emergence probability of the mutated strain, above that assumed by just scaling the reproductive ratio. Finally, we apply our model to the documented emergence of Chikungunya virus on La Reunion Island and demonstrate that the emergence probability of the mutated strain was reduced approximately 10 fold, compared to models assuming that susceptible depletion would not affect outbreak probability. These results highlight the importance of taking population feedbacks into account when predicting disease emergence.