ReviewThe Lancet. Infectious diseases2014
Ensuring privacy in the study of pathogen genetics.
Review in The Lancet. Infectious diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- Differential privacy in health research: A scoping review.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Addressing Ethical Challenges in US-Based HIV Phylogenetic Research.The Journal of infectious diseases · 2020Article
- Ethical challenges in pathogen sequencing: a systematic scoping review.Wellcome open research · 2020Article
- Ethical issues associated with HIV molecular epidemiology: a qualitative exploratory study using inductive analytic approaches.BMC medical ethics · 2019Article
- Societal Implications of the Internet of Pathogens.Journal of clinical microbiology · 2019Article
- Perceptions of molecular epidemiology studies of HIV among stakeholders.Journal of public health research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Rapid growth in the genetic sequencing of pathogens in recent years has led to the creation of large sequence databases. This aggregated sequence data can be very useful for tracking and predicting epidemics of infectious diseases. However, the balance between the potential public health benefit and the risk to personal privacy for individuals whose genetic data (personal or pathogen) are included in such work has been difficult to delineate, because neither the true benefit nor the actual risk to participants has been adequately defined. Existing approaches to minimise the risk of privacy loss to participants are based on de-identification of data by removal of a predefined set of identifiers. These approaches neither guarantee privacy nor protect the usefulness of the data. We propose a new approach to privacy protection that will quantify the risk to participants, while still maximising the usefulness of the data to researchers. This emerging standard in privacy protection and disclosure control, which is known as differential privacy, uses a process-driven rather than data-centred approach to protecting privacy.
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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.