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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763604
• 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.

在具有经济价值的动物种群中暴发疫情造成了重大的社会、环境和经济代价。在加拿大，马匹被省级和联邦农业机构视为家畜，马匹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(包括马)的暴发，应急管理和准备非常重要。然而，马业在这一领域落后于其他农业大宗商品集团。马的流动为传染病的引入和传播创造了机会，马业采纳了一些生物安全建议。然而，这些建议是基于有限的经验数据。这一关键信息差距阻碍了我们对存在的流行病潜力进行彻底的风险评估，并为基于证据的生物安全政策提供信息的能力。历史表明，将来自不同地点的马聚集在一起的事件有可能传播疾病传播事件。系统地应用网络科学和流行病学模型作为在不确定情况下提供决策信息的工具，是管理马群传染病风险的有用方法。这项研究计划的总体目标是检验马匹网络结构和人类行为相互作用影响马匹生物安全成功的假设。通过网络对疾病传播进行建模带来了许多理论和应用挑战，值得进一步研究。具体地说，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，以及3)考虑疾病与行为的相互作用。这一建议代表着理解疾病动力学向前迈出的重要一步，因为它们在复杂的网络中进化。网络传染病模型的性质往往是违反直觉的，微小的变化可能会对模型的结果产生巨大的影响。在这些情况下，直觉可能是一个非常糟糕的决策指南。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匹混合地点传播的机会的理解，是加拿大兽医研究的重要下一步。拟议的研究是在当前马匹行业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，支持加拿大马匹行业准备应急准备计划，并使加拿大农业部门能够更及时地做出应急反应。