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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=716033
• 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.

具有经济价值的动物种群的爆发会造成重大的社会、环境和经济成本。加拿大省级和联邦农业机构均将马视为牲畜，马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（包括马）的疫情爆发，应急管理和准备工作非常重要。然而，马产业在该领域落后于其他农产品类别。马匹的流动为传染病的引入和传播创造了机会，马业已采纳了许多生物安全建议。然而，这些建议基于有限的经验数据。这种关键的信息差距阻碍了我们对存在的流行病潜力进行彻底风险评估并为基于证据的生物安全政策提供信息的能力。历史证明，将来自不同地点的马匹聚集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模型的系统应用作为在不确定性下为决策提供信息的工具是管理马种群传染病风险的有用方法。该研究计划的首要目标是检验马网络结构和人类行为相互作用以影响马生物安全成功的假设。 对疾病通过网络传播进行建模提出了许多值得进一步研究的理论和应用挑战。具体来说，我们将：1）收集经验网络数据，2）将网络数据纳入流行病模型，3）考虑疾病与行为的相互作用。该提案代表了理解疾病动态在复杂网络中演变的重要一步。网络流行病模型的属性通常是违反直觉的，微小的变化可能会对模型结果产生巨大影响。在这些情况下，直觉对于决策来说可能是一个非常糟糕的指导。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混合场所传播的机会的理解，是加拿大兽医研究的重要下一步。拟议的研究是在马业当前生物安全标准文件的基础上迈出的重要一步，制定基于证据的建议，支持加拿大马业制定应急准备计划，并允许加拿大农业部门更及时地做出应急响应。