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: 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=716323
• 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.

乳业部门代表了加拿大经济中非常重要的一部分，2018年的净农场收入为66亿加元。我们的牛群中已经存在的传染病对加拿大乳制品的盈利能力和可持续性造成了重大损失。这些疾病还对动物福利，抗菌剂和食品安全产生了影响。此外，在牛群中引入新疾病可能会对牛群的盈利能力产生毁灭性的影响，还对我们出口产品，动物以及我们在国际市场上的遗传学的能力。由于这些原因，现在对于我们的加拿大乳制品生产商来说，实施基于强烈的科学证据的动物健康监视和控制计划至关重要。 我正在以长期的总体目标进行研究计划，即改善监视计划和生物安全实践，以控制各种动物疾病。特定的短期目标将是： 1）量化不完善采样策略对动物健康监视系统性能的影响，并制定采样和统计建模策略以防止偏见； 2）验证适合于动物健康监测的目的诊断策略，以使几种在乳制品生产中非常重要的疾病； 3）开发新的工具，以便于包含主动和被动动物健康监视信息的多个，大型省和国家数据集的多个，大型省和国家数据集可视化。 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。在抽样策略的主题下的研究将有助于比较不同的抽样方法（例如，选择抽样材料的选择，每头样本的动物数量，抽样频率，抽样数量，诊断测试的选择，选择诊断测试的选择），用于五种牛牛疾病，被确定为在国家乳制研究策略中被确定为高度优先级的牛乳头，持续性疾病，持续的乳腺炎病毒病毒，bevine mastia nipoiss，buvine mastia nipoiss，buvine mastia diator，buvine bef hhear tima旁结核病，沙门氏菌病）。统计建模策略的主题的研究将评估现有，并提出专门为动物健康监视系统设计的新型尖端统计建模方法。最后，数据可视化主题下的研究活动将导致简单，灵活的数据可视化接口的开发，这些界面将完全改变我们目前与主动和被动监视数据的方式。 拟议的研究计划将对加拿大产业产生重大影响。它将支持建立最先进的动物健康监视和改进计划。此外，开发的新型数据可视化工具将使乳制品从业者和其他最终用户实时可用的监视数据，从而迅速应对感染性疾病威胁。