Novel methodologies for design and analysis of dairy health surveillance programs

乳制品健康监测计划设计和分析的新方法

• 批准号: RGPIN-2020-05237
• 负责人: Dufour, Simon
• 金额: $ 3.42万
• 依托单位: Université de Montréal
• 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=740470
• 关键词: Novel; methodologies; design; analysis; dairy

The dairy sector represents a very important part of the Canadian economy with net farm receipts of $ 6.6 billion in 2018. Infectious diseases already present in our herds take a significant toll on profitability and sustainability of Canadian dairies. These diseases also have an impact on animal welfare, use of antimicrobials, and food safety. Moreover, the introduction of new diseases in a herd can have devastating impacts on profitability of that herd, but also on our ability to export our products, our animals, and our genetics on international markets. For these reasons, it is now crucial for our Canadian dairy producers to implement animal health surveillance and control programs that are based on strong scientific evidences. I am pursuing my research program with the long-term overarching goal of improving surveillance programs and biosecurity practices for control of various animal diseases. Specific short-term objectives will be to: 1)quantify the impacts of imperfect sampling strategies on the performances of animal health surveillance systems and develop sampling AND statistical modelling strategies for preventing biases; 2)validate fit for purpose diagnostic strategies for animal health surveillance for a few diseases of great importance in dairy production; 3)develop novel tools for easy and flexible data visualisation of multiple, large provincial and national datasets containing active and passive animal health surveillance information. To achieve these short-term objectives we will conduct a series of studies under three themes: 1) sampling strategies; 2) statistical modelling strategies; and 3) data visualisation. Research under the `sampling strategies' theme will help comparing different sampling approaches (e.g., choice of sampling materials, number of animals sampled per herd, frequency of sampling, number of herds sampled, choice of diagnostic tests) for five dairy cattle diseases identified as high priorities in the National Dairy Research Strategy (contagious mastitis, leucosis, bovine viral diarrhea, paratuberculosis, salmonellosis). Research under the `statistical modelling strategies' theme will evaluate existing, and propose novel cutting-edge statistical modelling approaches designed specifically for animal health surveillance systems. Finally, research activities under the `data visualisation' theme will lead to the development of easy and flexible data visualisation interfaces that will completely transform the way we currently interact with active and passive surveillance data. The proposed research program will have an outstanding impact on the Canadian industry. It will support the establishment of state-of-the-art animal health surveillance and improvement programs. Moreover, the novel data visualisation tools developed will make the surveillance data available in real-time for dairy practitioners and other end users, thus allowing for prompt response to infectious disease threats.

乳制品行业是加拿大经济的重要组成部分，2018年农场净收入为66亿加元。我们牛群中已经存在的传染病对加拿大奶牛场的盈利能力和可持续性造成了重大影响。这些疾病也对动物福利、抗菌药物的使用和食品安全产生影响。此外，在牛群中引入新的疾病会对牛群的盈利能力产生破坏性影响，也会对我们在国际市场上出口产品、动物和基因的能力产生破坏性影响。由于这些原因，加拿大乳制品生产商实施基于强有力科学证据的动物健康监测和控制计划至关重要。我正在追求我的研究计划，长期的总体目标是改善监测计划和生物安全实践，以控制各种动物疾病。具体的短期目标将是：1）量化不完善的抽样策略对动物健康监测系统性能的影响，并制定防止偏倚的抽样和统计建模策略; 2）验证用于乳品生产中一些重要疾病的动物健康监测的诊断策略是否符合目的; 3）开发新的工具，方便灵活地可视化包含主动和被动动物健康监测信息的多个大型省级和国家数据集。为了实现这些短期目标，我们将在三个主题下进行一系列研究：1）抽样策略; 2）统计建模策略; 3）数据可视化。“抽样战略”专题下的研究将有助于比较不同的抽样方法（例如，在国家奶牛研究战略中确定为高度优先的五种奶牛疾病（传染性乳腺炎、白血病、牛病毒性腹泻、副结核病、沙门氏菌病）的抽样材料选择、每群抽样动物数量、抽样频率、抽样牛群数量、诊断试验选择）。“统计建模战略”主题下的研究将评估现有的统计建模方法，并提出专门为动物健康监测系统设计的新的尖端统计建模方法。最后，“数据可视化”主题下的研究活动将导致开发简单灵活的数据可视化界面，这将彻底改变我们目前与主动和被动监视数据互动的方式。 拟议的研究计划将对加拿大工业产生重大影响。它将支持建立最先进的动物健康监测和改善计划。此外，开发的新型数据可视化工具将为乳品从业者和其他最终用户提供实时监测数据，从而能够对传染病威胁做出迅速反应。