publication . Other literature type . Article . 2019

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

Chiara Garattini; Jade Raffle; Dewi Nur Aisyah; Felicity Sartain; Zisis Kozlakidis;
Open Access
  • Published: 01 Mar 2019
  • Publisher: Springer Science and Business Media LLC
  • Country: United Kingdom
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 c...
Persistent Identifiers
Subjects
Medical Subject Headings: education
free text keywords: Philosophy, History and Philosophy of Science, Infectious diseases, Big data analytics, Ethics, Mobile phones, Wearables, Research Article, Infectious diseases, Big data analytics, Ethics, Mobile phones, Wearables, Wearable computer, Freedom of choice, Infectious disease (medical specialty), Big data, business.industry, business, Health care, Profiling (computer programming), Constructive, Accrual, Data science, Computer science
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)
91 references, page 1 of 7

Asadi Someh, I., et al. (2016). Ethical implications of big data analytics. Research-in-Progress Papers. 24. http://aisel.aisnet.org/ecis2016_rip/24

Bayham, J., Kuminoff, N. V., Gunn, Q., & Fenichel, E. P. (2015). Measured voluntary avoidance behaviour during the 2009 A/H1N1 epidemic. Proceedings of the Royal Society B, 282(1818), 20150814. doi:10.1098/rspb.2015.0814. [OpenAIRE]

Blais, C. M., & White, J. L. (2015). Bioethics in practice-a quarterly column about medical ethics: Ebola and medical ethics-ethical challenges in the management of contagious infectious diseases. The Ochsner Journal, 15(1), 5-7.

Bollier, D. (2010). The promise and peril of big data. Washington: The Aspen Institute.

Bosch, T., et al. (2016). Next-generation sequencing confirms presumed nosocomial transmission of livestockassociated methicillin-resistant Staphylococcus aureus in the Netherlands. Applied and Environmental Microbiology, 82(14), 4081-4089.

Buehler, J. W., Berkelman, R. L., Hartley, D. M., & Peters, C. J. (2003). Syndromic surveillance and bioterrorism-related epidemics. Emerging Infectious Diseases, 9, 1197-1204. [OpenAIRE]

Camaraa, C. L. (2015). Security and privacy issues in implantable wearable device: a comprehensive survey. Journal of Biomedical Informatics, 271-289.

Cecaj, A., Mamei, M., & Zambonelli, F. (2016). Re-identification and information fusion between anonymized CDR and social network data. Journal of Ambient Intelligence and Humanized Computing, 7(1), 83-96.

Center for Global Development. (2014). Delivering on the data revolution in sub-Saharan Africa. Center for global development and the African Population and Health Research Center. DC: Washington.

Chana, M. (2012). Current status and future challenges. Artificial Intelligence in Medicine, 56, 137-156.

Chapman, G. B., & Coups, E. J. (2006). Emotions and preventive health behavior: worry, regret, and influenza vaccination. Health Psychology, 25(1), 82-90. [OpenAIRE]

Cinnamon, J., Jones, S. K., & Adger, W. N. (2016). Evidence and future potential of mobile phone data for disease disaster management. Geoforum, 75, 253-264.

Clarke, R. (2016). Big data, big risks. Information Systems Journal, 26(1), 77-90. doi:10.1111/isj.12088.

Darrell, A., et al. (2014). The benefits of big data analytics in the healthcare sector: what are they and who benefits? In Wang, B., Li, R. and Perixxo, W. (eds.), Big data analytics in bioinformatics and healthcare (Chapter 18, pp.406-439 ) Hershey:IGI Global.

Dell, N.L., et al. (2011). Towards a point-of-care diagnostic system: automated analysis of immunoassay test data on a cell phone. Proceedings of the 5th ACM workshop on netoworked systems for developing regions (NSDR'11). 28th of June, New York, (pp. 3-8). doi: 10.1145/1999927.1999931.

91 references, page 1 of 7
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 c...
Persistent Identifiers
Subjects
Medical Subject Headings: education
free text keywords: Philosophy, History and Philosophy of Science, Infectious diseases, Big data analytics, Ethics, Mobile phones, Wearables, Research Article, Infectious diseases, Big data analytics, Ethics, Mobile phones, Wearables, Wearable computer, Freedom of choice, Infectious disease (medical specialty), Big data, business.industry, business, Health care, Profiling (computer programming), Constructive, Accrual, Data science, Computer science
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)
91 references, page 1 of 7

Asadi Someh, I., et al. (2016). Ethical implications of big data analytics. Research-in-Progress Papers. 24. http://aisel.aisnet.org/ecis2016_rip/24

Bayham, J., Kuminoff, N. V., Gunn, Q., & Fenichel, E. P. (2015). Measured voluntary avoidance behaviour during the 2009 A/H1N1 epidemic. Proceedings of the Royal Society B, 282(1818), 20150814. doi:10.1098/rspb.2015.0814. [OpenAIRE]

Blais, C. M., & White, J. L. (2015). Bioethics in practice-a quarterly column about medical ethics: Ebola and medical ethics-ethical challenges in the management of contagious infectious diseases. The Ochsner Journal, 15(1), 5-7.

Bollier, D. (2010). The promise and peril of big data. Washington: The Aspen Institute.

Bosch, T., et al. (2016). Next-generation sequencing confirms presumed nosocomial transmission of livestockassociated methicillin-resistant Staphylococcus aureus in the Netherlands. Applied and Environmental Microbiology, 82(14), 4081-4089.

Buehler, J. W., Berkelman, R. L., Hartley, D. M., & Peters, C. J. (2003). Syndromic surveillance and bioterrorism-related epidemics. Emerging Infectious Diseases, 9, 1197-1204. [OpenAIRE]

Camaraa, C. L. (2015). Security and privacy issues in implantable wearable device: a comprehensive survey. Journal of Biomedical Informatics, 271-289.

Cecaj, A., Mamei, M., & Zambonelli, F. (2016). Re-identification and information fusion between anonymized CDR and social network data. Journal of Ambient Intelligence and Humanized Computing, 7(1), 83-96.

Center for Global Development. (2014). Delivering on the data revolution in sub-Saharan Africa. Center for global development and the African Population and Health Research Center. DC: Washington.

Chana, M. (2012). Current status and future challenges. Artificial Intelligence in Medicine, 56, 137-156.

Chapman, G. B., & Coups, E. J. (2006). Emotions and preventive health behavior: worry, regret, and influenza vaccination. Health Psychology, 25(1), 82-90. [OpenAIRE]

Cinnamon, J., Jones, S. K., & Adger, W. N. (2016). Evidence and future potential of mobile phone data for disease disaster management. Geoforum, 75, 253-264.

Clarke, R. (2016). Big data, big risks. Information Systems Journal, 26(1), 77-90. doi:10.1111/isj.12088.

Darrell, A., et al. (2014). The benefits of big data analytics in the healthcare sector: what are they and who benefits? In Wang, B., Li, R. and Perixxo, W. (eds.), Big data analytics in bioinformatics and healthcare (Chapter 18, pp.406-439 ) Hershey:IGI Global.

Dell, N.L., et al. (2011). Towards a point-of-care diagnostic system: automated analysis of immunoassay test data on a cell phone. Proceedings of the 5th ACM workshop on netoworked systems for developing regions (NSDR'11). 28th of June, New York, (pp. 3-8). doi: 10.1145/1999927.1999931.

91 references, page 1 of 7
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