NordForsk Digitalisation of the Public Sector: Digitalisation of livestock data to improve veterinary public health

家畜疾病的成功管理确保了为社会上每个人提供一致的安全食品。行业、公共服务甚至公众对数据的使用是这项兽医公共卫生使命的关键部分。然而，管理这些数据带来了许多挑战：数据收集应该如何标准化，以及谁应该有权访问这些数据的不同方面？将农民的数据公之于众会带来什么风险？在我们日益国际化的社会中，需要维护哪些数据和程序才能有效地控制对我们安全食品供应的共同威胁？DigiVet项目将研究目前如何在伙伴国家使用牲畜数据，以及技术、培训和监管框架如何通过改善这些数据的公共利益使用来提供社会效益。我们的研究包括与利益相关者的研讨会，以绘制现有实践图，并记录差距、障碍和改进机会。三个案例研究将涵盖食源性疾病、抗菌剂的使用和牲畜的传染病。沙门氏菌等食源性疾病是一个严重的公共卫生问题，牲畜使用抗菌剂可能导致人类病原体出现抗药性问题，非洲猪瘟等外来和高度传染性的牲畜疾病有可能摧毁我们的国家农业部门，每一种疾病都对整个社会产生广泛影响。应对每一项挑战需要不同的方法，但每一种方法都因依赖类似的数据源而团结在一起，以便当局能够持续监测威胁并在需要时采取行动。对于这些应用程序中的每一个，我们将测试一个合作伙伴国家/地区在其他地理环境中使用的模型和统计数据分析，调查哪些方法在什么情况下有效，以及需要进行哪些更改以促进更有效地使用数据。我们还将调查与丢失、稀疏或粗略聚合的数据相关的风险，并评估使更高质量的数据更广泛地可用的潜在社会效益。

Successful management of livestock disease ensures a consistent supply of safe food for everyone in society. The use of data by industry, public services, and even the public at large is a key part of this veterinary public health mission. However, managing this data comes with many challenges: how should data collection be standardised, and who should have access to different aspects of this data? What risks are farmers exposed to by making their data publically available? What data and processes need to be maintained to be able to effectively control shared threats to our supply of safe food within our increasingly international society?The DigiVet project will study how livestock data is currently used across the partner nations, and how technology, training, and regulatory frameworks might provide societal benefit by improving the public-interest uses of these data. Our study includes workshops with stakeholders to map existing practices, and document the gaps, roadblocks, and opportunities for improvement. Three case studies will cover foodborne disease, antimicrobial usage, and contagious diseases of livestock. Foodborne illnesses such as Salmonella are a serious public health issue, antimicrobial usage in livestock may be contributing to the developing antimicrobial resistance problem in human pathogens, and exotic and highly contagious livestock diseases such as African swine fever have the potential to devastate our national agricultural sectors, each of which has wide-reaching implications for society as a whole. Meeting each of these challenges requires different approaches, but each are united by their dependence on similar sources of data to be able for the authorities to continually monitor the threat and act when needed. For each of these applications, we will test the models and statistical data analytics that are used in one partner nation across the other geographic settings, investigating what approaches will work under what circumstances, and what would need to change to facilitate more effective use of the data. We will also investigate the risks associated with missing, sparse, or coarsely aggregated data, and evaluate the potential societal benefits of making better quality data more widely available.