Transmission of one predicts another: Apathogenic proxies for transmission dynamics of a fatal virus

Abstract

Identifying drivers of transmission prior to an epidemic--especially of an emerging pathogen--is a formidable challenge for proactive disease management efforts. We tested a novel approach in the Florida panther, hypothesizing that apathogenic feline immunodeficiency virus (FIV) transmission could predict transmission dynamics for pathogenic feline leukemia virus (FeLV). We derived a transmission network using FIV whole genome sequences, and used exponential random graph models to determine drivers structuring this network. We used these drivers to predict FeLV transmission pathways among panthers and compared predicted outbreak dynamics against empirical FeLV outbreak data. FIV transmission was primarily driven by panther age class and distances between panther home range centroids. Prospective FIV-based modeling predicted FeLV dynamics at least as well as simpler, often retrospective approaches, with evidence that FIV-based predictions captured the spatial structuring of the observed FeLV outbreak. Our finding that an apathogenic agent can predict transmission of an analogously transmitted pathogen is an innovative approach that warrants testing in other host-pathogen systems to determine generalizability. Use of such apathogenic agents holds promise for improving predictions of pathogen transmission in novel host populations, and could thereby provide new strategies for proactive pathogen management in human and animal systems.