Participatory Disease Surveillance Systems: Ethical Framework

Abstract

Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants’ physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants’ privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance.

Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System

“…The implementation of a digital infectious disease detection system based on self-recorded data poses serious challenges that require special attention, such as user privacy and security, data confidentiality, user acceptance, and motivations [ 26 , 101 ], especially during data collection, transmission, and data storage [ 102 , 103 ]. Personal health–related data are sensitive, and the data collection, transmission, and data storage procedure need to follow the standards and regulations provided by the major governing bodies, such as General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) [ 104 , 105 ].…”

“…Personal health–related data are sensitive, and the data collection, transmission, and data storage procedure need to follow the standards and regulations provided by the major governing bodies, such as General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) [ 104 , 105 ]. This includes privacy-preserving mechanisms such as pseudonymization and anonymization to meet the necessary data compliance requirement along with user informed consent [ 102 , 103 ]. According to GDPR, the deidentification procedure is one of the recommended anonymization standards to preserve data confidentiality [ 104 , 105 ].…”

Special Section on Ethics in Health Informatics

“…Among the 19 shortlisted papers, seven focused on various forms of data sharing and/or data use, five addressed privacy concerns, and one paper addressed both topic areas. Articles in the data sharing area explored a broad range of issues including passive data collection [6]; [patient] participatory methods in data-intensive biomedical research [7] and disease surveillance [8]; data management, use/re-use, and sharing internationally [9] and under the GDPR [10]; posthumous data donation [11]; and human protection with regard to data sharing [12]. Papers focused on privacy looked at the use and understanding of anonymization and de-identification practices in the literature [13]; health information disclosure [14]; balancing privacy and data use under the GDPR [15]; activities that work against citizen and patient trust with regard to personal information [16]; and terms of use violations by researchers accessing online patient information [17].…”

Digital Public Health – ein Überblick

“…B. Apps oder Fitnesstracker, auf mobilen Endgeräten generiert werden, gesammelt und zum Monitoring von Krankheiten verwendet. Dabei werden zwei grundlegend unterschiedliche Zugänge zu den Daten diskutiert [24] ein passiver Zugang, bei dem ohne Zustimmung der Teilnehmenden anonymisiert z. B. Suchanfragen, Twitter-Einträge oder Ähnliches analysiert werden, oder ein partizipativer Zugang, in dem Freiwillige ihre Daten in ein bereitgestelltes Überwachungssystem eintragen und so zum Monitoring beitragen.…”