We are all atwitter about being award a new grant from the National Science Foundation Ecology and Evolution of Infectious Diseases! Titled, “Socioeconomic and Epidemiological Drivers of Pathogen Dynamics in Wildlife Trade Networks,” this work focuses on understanding the factors that magnify or reduce the spread through and potential for pathogen spillover from the live animal trade. We are working closely with some terrific partners in the Amphibian Pet Trade, as well as sociologists, modelers, outreach specialists, and more. The work is being led by Matt Gray at the University of Tennessee and I am a co-PI for the WSU component (with Jonah Piovia-Scott).

Non-technical Summary:

The wildlife trade industry involves an estimated 2.5M live animals, valued >$300B USD, moving among >180 nations per year. This represents a key pathway for the evolution, emergence, and spread of novel pathogens.  Zoonotic and wildlife pathogens (e.g., SARS-CoV-2 and chytrid fungi, respectively) have cost global economies trillions of dollars, led to substantial human life and biodiversity loss, and been linked to wildlife trade. Managing disease in live animal trade networks presents distinctive challenges. Various socioeconomic factors can influence the decisions businesses make about the species they trade and the biosecurity practices they use, which in turn can influence the prevalence, persistence, and spread of pathogens. Therefore, animal trade networks represent a bidirectionally coupled system between pathogen-host ecology and decisions made by business, consumer, and government stakeholders (Fig. 1).

The overarching goal of this project is to identify how socioeconomic decisions made by stakeholders drive pathogen dynamics in a wildlife trade network and use this information to identify disease mitigation strategies that are economically viable and minimize spillover risk (i.e., pathogen transmission from captive to wild populations). This project is partnering with the U.S. wildlife trade industry and government stakeholders, and will facilitate discussions among them to identify strategies that promote clean trade, while considering socioeconomic impacts on the industry. The project uses a combination of socioeconomic surveys, facilitated discussions, pathogen surveillance, and controlled experiments to build a series of predictive models that can be used to guide policy decisions in wildlife trade and prevent the next global pandemic.