Abstract
Surveillance is essential for communicable disease prevention and control. Traditional notification of demographic and clinical information, about individuals with selected (notifiable) infectious diseases, allows appropriate public health action and is protected by public health and privacy legislation, but is slow and insensitive. Big data–based electronic surveillance, by commercial bodies and government agencies (for profit or population control), which draws on a plethora of internet- and mobile device–based sources, has been widely accepted, if not universally welcomed. Similar anonymous digital sources also contain syndromic information, which can be analysed, using customised algorithms, to rapidly predict infectious disease outbreaks, but the data are nonspecific and predictions sometimes misleading. However, public health authorities could use these online sources, in combination with de-identified personal health data, to provide more accurate and earlier warning of infectious disease events—including exotic or emerging infections—even before the cause is confirmed, and allow more timely public health intervention. Achieving optimal benefits would require access to selected data from personal electronic health and laboratory (including pathogen genomic) records and the potential to (confidentially) re-identify individuals found to be involved in outbreaks, to ensure appropriate care and infection control. Despite existing widespread digital surveillance and major potential community benefits of extending its use to communicable disease control, there is considerable public disquiet about allowing public health authorities access to personal health data. Informed public discussion, greater transparency and an ethical framework will be essential to build public trust in the use of new technology for communicable disease control.
Highlights
Surveillance is essential for communicable disease prevention and control
There are risks and benefits associated with Big Data analytics (Davis and Patterson 2012), but little public understanding of what they are, what they depend on and how, if at all, individuals can influence their use
For example, infectious disease research and diagnostics have been transformed by nucleic acid–based pathogen identification and genome sequencing, which are faster, more informative and more amenable to digitisation than traditional culture-based “cottage industry” methods (Gilbert 2002)
Summary
We are under constant, state-sanctioned surveillance (Hanley 2017), which is officially “justified” on the grounds of national security, crime prevention, road safety or public service improvement. Denmark’s system, which is one of the most advanced in the world (Rothstein 2008), has reportedly failed to realise its potential to improve healthcare service delivery, in part because of failure to develop common technical standards for health information exchange (Kierkegaard 2013) Wherever such systems have been proposed, there are unresolved controversies about privacy, effects on doctor/patient relationships and trust, whether individuals can opt out, who controls or can have access to data and when consent is required, how to protect data from unauthorised use or accidental loss (Fairweather and Rogerson 2001), and use of “de-identified” data for ethically approved research. Methods used range from reports of unusual or suspicious index cases by astute (medical or veterinary) clinicians to mandatory notification of diseases of public health importance, syndromic surveillance and digital epidemiology
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