Digital epidemiology, also referred to as digital disease detection (DDD), successfully provided methods and strategies for using information technology to support infectious disease monitoring and surveillance or understand attitudes and concerns about infectious diseases. However, Internet-based research and social media usage in epidemiology and healthcare pose new technical, functional and formal challenges. The focus of this paper is on the ethical issues to be considered when integrating digital epidemiology with existing practices. Taking existing ethical guidelines and the results from the EU project M-Eco and SORMAS as starting point, we develop an ethical assessment model aiming at providing support in identifying relevant ethical concerns in future DDD projects. The assessment model has four dimensions: user, application area, data source and methodology. The model supports in becoming aware, identifying and describing the ethical dimensions of DDD technology or use case and in identifying the ethical issues on the technology use from different perspectives. It can be applied in an interdisciplinary meeting to collect different viewpoints on a DDD system even before the implementation starts and aims at triggering discussions and finding solutions for risks that might not be acceptable even in the development phase. From the answers, ethical issues concerning confidence, privacy, data and patient security or justice may be judged and weighted.

中文翻译：

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数字疾病检测技术的道德评估模型

数字流行病学，也称为数字疾病检测（DDD），成功提供了使用信息技术支持传染病监测和监视或了解对传染病的态度和关注的方法和策略。但是，基于流行病学和医疗保健的基于Internet的研究和社交媒体的使用提出了新的技术，功能和形式上的挑战。本文的重点是将数字流行病学与现有实践相结合时应考虑的道德问题。以现有的道德准则和欧盟项目M-Eco和SORMAS的结果为出发点，我们开发了一种道德评估模型，旨在为识别未来DDD项目中的相关道德问题提供支持。评估模型具有四个维度：用户，应用领域，数据来源和方法。该模型支持了解，识别和描述DDD技术或用例的道德方面，并从不同的角度识别有关技术使用的道德问题。它甚至可以在跨学科会议中应用，甚至在实施开始之前就DDD系统收集不同的观点，其目的是引发讨论并找到即使在开发阶段也不可接受的风险解决方案。从答案中，可以判断和权衡涉及信心，隐私，数据以及患者安全或正义的道德问题。它甚至可以在跨学科会议中应用，甚至在实施开始之前就DDD系统收集不同的观点，其目的是引发讨论并找到即使在开发阶段也不可接受的风险解决方案。从答案中，可以判断和权衡涉及信心，隐私，数据以及患者安全或正义的道德问题。它甚至可以在跨学科会议中应用，甚至在实施开始之前就DDD系统收集不同的观点，其目的是引发讨论并找到即使在开发阶段也不可接受的风险解决方案。从答案中，可以判断和权衡涉及信心，隐私，数据以及患者安全或正义的道德问题。