Socioeconomic and Epidemiological Drivers of Pathogen Dynamics in Wildlife Trade Networks

野生动物贸易产业估计涉及250万只活动物，价值3000亿美元，每年在180个国家之间流动。这是新病原体进化、出现和传播的关键途径。人畜共患病和野生动物病原体(如SARS-CoV-2和壶菌)给全球经济造成了数万亿美元的损失，导致大量人类生命和生物多样性的丧失，并与野生动物贸易有关。活体动物贸易网络中的疾病管理面临着独特的挑战。各种社会经济因素可以影响企业对他们交易的物种和他们使用的生物安全措施做出的决定，这反过来又会影响病原体的流行、持续和传播。因此，动物贸易网络代表了病原体-宿主生态与企业、消费者和政府利益相关者做出的决策之间的双向耦合系统。该项目将为学生和博士后提供培训机会。该项目的总体目标是确定利益相关者做出的社会经济决策如何推动野生动物贸易网络中病原体的动态，并利用这些信息确定经济上可行的疾病缓解策略，并将溢出风险降至最低(即病原体从圈养种群传播到野生种群)。该项目正在与美国野生动物贸易行业和政府利益相关者合作，并将促进他们之间的讨论，以确定促进清洁贸易的战略，同时考虑对该行业的社会经济影响。该项目利用社会经济调查、促进讨论、病原体监测和受控实验相结合的方式，建立了一系列预测模型，可用于指导野生动物贸易的政策决策，防止下一次全球大流行。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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. This project will provide training opportunities for students and post-docs. 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.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.