An ethical assessment model for digital disease detection technologies.

Denecke, Kerstin (2017). An ethical assessment model for digital disease detection technologies. Life Sciences, Society and Policy, 13(16), pp. 1-11. BioMed Central 10.1186/s40504-017-0062-x

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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.

Item Type:

Newspaper or Magazine Article


School of Engineering and Computer Science > Institute for Patient-centered Digital Health
School of Engineering and Computer Science


Denecke, Kerstin0000-0001-6691-396X




BioMed Central




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Date Deposited:

13 Nov 2019 10:33

Last Modified:

26 Oct 2023 13:53

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