The embracing of "big data" approaches is providing useful methods for public health research, surveillance, and intervention. Information is increasingly collected from traditional data sources, such as electronic health records, laboratory databases, and surveys, as well as in real time from personal mobile devices, internet use, social media, and environmental sensors - resulting in large and complex databases for analyses. Advances in technologies and data analytic techniques provide powerful ways to predict human behavior (such as health risk behaviors) or the outbreak of disease in a population. These techniques can also be used to provide helpful recommendations for risk reduction and guide clinical intervention and treatments. Importantly, the use of these modern techniques and data collection methods also raise important ethical concerns such as those associated with misuse of data, privacy, lack of transparency, and inaccurate prediction. This chapter provides an overview of "big data analytics" used in public health as well as current and emerging ethical issues and risks. Recommendations for the fields of public health and healthcare in general are provided.

Chapter Contents:

• 3.1 Introduction
• 3.2 Overview of big data analytics
• 3.3 Enabling technologies
• 3.4 Data sources and collection methods
• 3.4.1 Traditional databases
• 3.4.2 Electronic health records
• 3.4.3 Internet and social media
• 3.4.4 Mobile and wearables devices
• 3.4.5 Genomics data
• 3.5 Advantages of big data in public health
• 3.6 Ethics and Risks
• 3.6.1 Privacy and misuse of data
• 3.6.2 Informed consent and transparency
• 3.6.3 Risk associated with discrimination and inaccurate prediction
• 3.6.4 Other considerations
• 3.7 Recommendations
• 3.8 Conclusion
• References

Inspec keywords: data privacy; ethical aspects; Big Data; health care

Other keywords: large complex databases; clinical intervention; ethical issues; public health research; risk reduction; public health surveillance; ethics; clinical treatment; healthcare; big data analytic techniques; data privacy; disease; public health intervention; human behavior prediction; data collection method

Subjects: Economic, social and political aspects of computing; Biology and medical computing; Data security