EMBARGO: February 9th, 2015, 11am Pacific/2pm Eastern/7pm UK
Using Big Data to Detect Disease Outbreaks: Is it Ethical?
Personal information taken from social media, blogs, page views and so on are used to detect
disease outbreaks, however, does this violate our privacy, consent and trust?
Dr. Effy Vayena from the University of Zurich and colleagues map the numerous ethical challenges
confronting digital disease detection (DDD) and propose a framework to address the questions.
In the article publishing this week in PLOS Computational Biology, the authors argue that this use of
big data has the potential to strengthen global public health surveillance, including in low resource
countries. However, the treatment and success of big data depends on answering ethical questions of
confidentiality when using personal information.
To address these ethical objections the authors focus on the following three categories:



Privacy and consent – the requirements need to be adapted for a public health context (as
opposed to a commercial context).
Methodological robustness - methodology is evolving and requires constant adaptation to
avoid false identification of outbreaks that could cause harm.
Legitimacy – digital disease detection needs codes of best practice to meet ethical
requirements as well as clear communication to the public to prevent hype.
The researchers say:
“Big data can play a
major role in public
health and its potential
has been demonstrated.
However, we are only at
the beginning and there
is no way to tap into this
resource without an
ethical and trustworthy
framework. The road to
trust requires a lot of
effort and ethical
diligence.”
Focus Feature
This article forms a
Focus Feature and is
accompanied by four
other articles. In an
accompanying Editorial Philip Bourne writes about the need for more law and order in “Confronting
the Ethical Challenges of Big Data in Public Health”. Please also see the following blog post by Jason
Papin on PLOS Biologue for more information on the other articles in the Focus Feature.
Image Caption: Focus Feature
Image Credit: Steve Rainwater/Flickr
Image Link: http://www.plos.org/wp-content/uploads/2015/01/Camera-Lens.jpg
All works published in PLOS Computational Biology are Open Access, which means that all content is
immediately and freely available. Use this URL in your coverage to provide readers access to the
paper upon publication: http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003904
Press-only preview: http://www.plos.org/wp-content/uploads/2015/02/pcbi.1003904_2.pdf
Contact: Effy Vayena
Address: University of Zurich
Institute of Biomedical Ethics
Pestalozzistrasse 24
Zurich, 8032
Swizterland
Phone: +41 44 634 8081
Email: vayena@ethik.uzh.ch
Citation: Vayena E, Salathé M, Madoff LC, Brownstein JS (2015) Ethical Challenges of Big Data in
Public Health. PLoS Comput Biol 11(2): e1003904.doi:10.1371/journal.pcbi.1003904
Funding: The authors received no specific funding for this article.
Competing Interests: Marcel Salathé is an Associate Editor for PLOS Computational Biology.
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