EID Disease in Complex Communities: Multi-host Multi-pathogen Interactions

Award Period: 

Sunday, September 1, 2013 to Saturday, June 30, 2018

Award Amount: 

$1 664 693

Agency Name: 

NIH General Medical Sciences

Award Number: 


PI First Name: 


PI last name: 


Area/s of Research: 


One of the fundamental challenges facing contemporary disease ecology involves understanding infection dynamics within complex communities composed of multiple hosts and multiple pathogens. Hosts in nature are exposed to a ‘cocktail’ of different pathogens, therefore a central question concerns how interactions between co-occurring pathogens affect disease severity and pathogen transmission in host communities. Most research to date has been focused at a single level, examining either how multiple infections influence individual host pathology or using population surveys to identify correlations in pathogen co-occurrence within a host population. This ‘disconnect’ in scales (i.e., within-host vs. between- host) omits a critically important question – namely, how do pathogen interactions within hosts ‘scale up’ to influence between-host processes, such as transmission and disease dynamics? The primary goal of this project is to understand how interactions among three virulent pathogens at different scales of biological complexity, including within hosts, between species, and among communities, combine to influence disease dynamics in amphibians, a group of globally threatened vertebrates. This project combines cross-sectional field surveys of wetland communities with controlled laboratory and mesocosm experiments to determine (1) how amphibian pathogens covary in occurrence and intensity across multiple spatial scales (individual hosts, host species, wetland communities), (2) the individual and combined effects of each pathogen on host pathology and pathogen infection success, and (3) the net effects of variation in host and pathogen community structure for pathogen transmission and host-pathogen dynamics. A stochastic, simulation-based modeling framework uniquely focused on individual hosts will be used to interpret experimental results and link field distributions of pathogens with underlying mechanisms. This project focuses on three pathogens that have been widely implicated in causing amphibian pathology: the chytrid fungus Batrachochytrium dendrobatidis, the trematode Ribeiroia ondatrae, and the viral genus Ranavirus.