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

牲畜疾病的成功管理确保了社会上每个人安全食品的持续供应。行业、公共服务甚至公众对数据的使用是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，以及谁应该访问这些数据的不同方面？农民通过公开提供数据会面临哪些风险？在我们日益国际化的社会中，为了能够有效地控制对我们安全食品供应的共同威胁，需要维护哪些数据和流程？DigiVet项目将研究牲畜数据目前在伙伴国家的使用情况，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用途来提供社会效益。我们的研究包括与利益相关者的研讨会，以绘制现有实践，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、抗菌剂使用和牲畜传染病。沙门氏菌等食源性疾病是一个严重的公共卫生问题，牲畜中的抗菌剂使用可能导致人类病原体中的抗菌剂耐药性问题，非洲猪瘟等外来和高度传染性牲畜疾病有可能破坏我们国家的农业部门，其中每一种都对整个社会产生广泛影响。应对这些挑战需要不同的方法，但每种方法都依赖于类似的数据来源，以便当局能够持续监测威胁并在需要时采取行动。对于每一个应用程序，我们将测试在一个合作伙伴国家使用的模型和统计数据分析，在其他地理环境中，调查在什么情况下哪些方法会起作用，以及需要改变什么来促进更有效地使用数据。我们还将调查与缺失、稀疏或粗略汇总的数据相关的风险，并评估更广泛地提供更高质量数据的潜在社会效益。

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.