ArticleEpidemics2022
In the shadow of privacy: Overlooked ethical concerns in COVID-19 digital epidemiology.
Article in Epidemics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Experts' Opinions on the Sustainable Use of Digital Health Tools for Effective Future Pandemic Preparedness and Response: Questionnaire Study.JMIR public health and surveillance · 2026Article
- Feasibility of AI-driven disease surveillance systems at international airports in sub-Saharan Africa: a narrative review.Frontiers in public health · 2026Review
- Exploring Attitudes and Obstacles Around Digital Public Health Tools: Insights From a Statewide Cross-Sectional Survey on Washington's Vaccine Verification System.Journal of medical Internet research · 2025Article
- Data sharing in the PRIMED Consortium: Design, implementation, and recommendations for future policymaking.American journal of human genetics · 2025Review
- Digital determinants of sexual and reproductive health-workforce perspectives on digital and data literacies.Health promotion international · 2025Article
- A scoping review of ethical aspects of public-private partnerships in digital health.NPJ digital medicine · 2025Article
- Epidemiological methods in transition: Minimizing biases in classical and digital approaches.PLOS digital health · 2025Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic witnessed a surge in the use of health data to combat the public health threat. As a result, the use of digital technologies for epidemic surveillance showed great potential to collect vast volumes of data, and thereby respond more effectively to the healthcare challenges. However, the deployment of these technologies raised legitimate concerns over risks to individual privacy. While the ethical and governance debate focused primarily on these concerns, other relevant issues remained in the shadows. Leveraging examples from the COVID-19 pandemic, this perspective article aims to investigate these overlooked issues and their ethical implications. Accordingly, we explore the problem of the digital divide, the role played by tech companies in the public health domain and their power dynamics with the government and public research sector, and the re-use of personal data, especially in the absence of adequate public involvement. Even if individual privacy is ensured, failure to properly engage with these other issues will result in digital epidemiology tools that undermine equity, fairness, public trust, just distribution of benefits, autonomy, and minimization of group harm. On the contrary, a better understanding of these issues, a broader ethical and data governance approach, and meaningful public engagement will encourage adoption of these technologies and the use of personal data for public health research, thus increasing their power to tackle epidemics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.