Abstract
The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission—aiding infection control measures and policies—emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: (i) automation and algorithmic reliance impacting freedom of choice, (ii) big data analytics complexity impacting informed consent, (iii) reliance on profiling impacting individual and group identities and justice/fair access and (iv) increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement.
Highlights
The terms big data and big data analytics are often used within the context of healthcare as an all-encompassing phrase referring to the use of large datasets
At what point are individuals prepared to compromise on some rights, such as that of privacy and autonomy, if it benefits them? Under what circumstances in the field of infectious diseases can individuals give up some individual benefits in order to greatly enhance public good? And, assuming that there is a benefit to the individual directly, to what extent should society be able to operate without disclosure and transparency regarding decisions taken automatically through data access and use?
One of the key challenges in the field of Big data analytics (BDA) in infectious diseases is connected to the difficulty for individuals to be fully aware of what happens to their data after collection, as this might be generated in one locality, aggregated in a second, processed in a third, and so on
Summary
The terms big data and big data analytics are often used within the context of healthcare as an all-encompassing phrase referring to the use of large datasets. BDA is useful in monitoring diseases outbreaks; stratifying patients for treatment, risk exposure and treatment outcome prediction; and for the prediction of behavioural patterns with the aim of informing public health interventions (Darrell et al 2015; Lee et al 2016) Despite these positive outcomes, the routine use of BDA is increasingly challenged with examples of wrongful conclusions (Lazer et al 2014), potential misuse of personal information, well-publicised privacy breeches and ongoing profiling of individuals for commercial purposes (Smith 2012; Richards and King 2014; Martin 2015). We discuss the ethical challenges according to four headings: (i) automation and algorithmic reliance impacting freedom of choice, (ii) big data analytics complexity impacting informed consent, (iii) reliance on profiling impacting individual and group identities and justice/fair access and (iv) increased surveillance and population intervention capabilities impacting behavioural norms and practices
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