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: automation and algorithmic reliance impacting freedom of choice, big data analytics complexity impacting informed consent, reliance on profiling impacting individual and group identities and justice/fair access and 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. (shrink)

This paper argues that specific individual informed consent and other forms of consent predicated on a right to autonomy may not in all circumstances be appropriate for the establishment and use of large data sets of health information. We suggest that there are inherent failings in such an approach, shortcomings that we analyse below. We argue that individuals share an obligation to contribute their data, as doing so is cost-free and benefits accrue to the population as a whole. Large health (...) data sets can be considered public goods – goods that are non-rival in consumption and in some cases non-exclusive in use – and contributing to these goods may be an obligation, the meeting of which allows citizens to invest in knowledge infrastructure. The approach argued for here is a variation of a communitarian ethic in which people have an obligation to contribute their data but have no correlative right to expect or receive an individual benefit. (shrink)