Disease dynamics across complex agricultural networks

复杂农业网络中的疾病动态

• 批准号: RGPIN-2020-03871
• 负责人: Greer, Amy
• 金额: $ 2.91万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=739524
• 关键词: Disease; dynamics; across; complex; agricultural

Outbreaks in economically valuable animal populations have important social, environmental and economic costs. Horses are considered livestock by both provincial and federal agriculture agencies in Canada and the equine industry contributes over 19 billion dollars annually to the Canadian economy. Emergency management and preparedness in the face of outbreaks in agricultural animal populations (including horses) is of significant importance. Yet, the equine industry has lagged behind other agricultural commodity groups in this area. The movement of horses creates opportunities for the introduction and spread of infectious diseases and the equine industry has adopted a number of biosecurity recommendations. However, these recommendations are based on limited empirical data. This critical information gap hinders our ability to perform thorough risk assessments of the epidemic potential that exists, and inform evidence-based biosecurity policies. History has demonstrated that events that bring horses together from different locations have the potential to propagate disease spread events. The systematic application of network science and epidemiological modeling as tools for informing decision-making under uncertainty is a useful approach for the management of infectious disease risks in the equine population. The over-arching goal of this program of research is to examine the hypothesis that equine network structure and human behaviour interact to influence the success of equine biosecurity. Modeling disease transmission across a network presents a number of theoretical and applied challenges that warrant further study. Specifically we will, 1) collect empirical network data, 2) incorporate network data into epidemic models, and 3) consider disease-behaviour interactions. This proposal represents an important step forward for understanding disease dynamics as they evolve across complex networks. The properties of network epidemic models are often counterintuitive and small changes can have a dramatic impact on the model outcomes. In these cases, intuition can be a very poor guide for decision-making. Collecting data to better support our understanding of how network structure and human behaviour interact to influence opportunities for pathogens to be spread at equine co-mingling sites represents an important next step for veterinary research in Canada. The proposed research represents an important step to build upon the current biosecurity standards documents for the Equine Sector, develop evidence-based recommendations that will support the Canadian equine industry in preparing emergency preparedness plans, and allow more timely emergency response within the Canadian agricultural sector.

经济有价值的动物种群的爆发具有重要的社会，环境和经济成本。加拿大的省和联邦农业机构都认为马匹被认为是牲畜，而马产业每年为加拿大经济贡献超过190亿美元。面对农业动物种群爆发（包括马匹）的紧急管理和准备很重要。然而，马产业落后于该领域的其他农产品群体。马匹的运动为引入和传播传染病创造了机会，而马产业则采用了许多生物安全建议。但是，这些建议基于有限的经验数据。这些关键信息差距阻碍了我们对存在的流行潜力的全面风险评估的能力，并为基于证据的生物安全政策提供了信息。历史表明，将马匹从不同位置融合在一起的事件有可能传播疾病传播事件。网络科学和流行病学建模作为在不确定性下为决策提供信息的工具的系统应用是一种有用的方法，用于管理马人群中传染病风险。该研究计划的总体目标是研究马网络结构和人类行为相互作用以影响马生物安全性的成功的假设。 建模跨网络的疾病传播提出了许多理论和应用挑战，需要进一步研究。具体来说，我们将收集经验网络数据，2）将网络数据纳入流行模型，3）考虑疾病 - 行为相互作用。该提案代表着了解疾病动态在复杂网络中发展的重要一步。网络流行模型的特性通常是违反直觉的，小变化可能会对模型结果产生巨大影响。在这些情况下，直觉可能是决策的非常糟糕的指南。收集数据以更好地支持我们对网络结构和人类行为如何相互作用以影响病原体在马共同汇合站点的机会的理解是加拿大兽医研究的重要下一步。拟议的研究代表了基于马部门的当前生物安全标准文件的重要一步，开发了基于证据的建议，该建议将支持加拿大马行业准备紧急准备计划，并允许加拿大农业部门内更及时的紧急响应。