Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

Area of Science:

• Healthcare Big Data Analytics
• Infectious Disease Epidemiology
• Bioethics

Background:

• Healthcare generates vast amounts of data, necessitating advanced analytics.
• Big data analytics offers tools for disease prediction, patient stratification, and service improvement.
• The field is rapidly evolving, impacting various medical disciplines.

Purpose of the Study:

• To explore the application of big data analytics in infectious diseases.
• To compare traditional and new data accumulation models in infectious disease management.
• To identify and discuss the ethical implications of big data analytics in this domain.

Main Methods:

• Comparative analysis of traditional and big data-driven information accumulation models.
• Discussion of ethical challenges including automation, consent, profiling, and surveillance.
• Exploration of future trends, including the use of personal device data.

Main Results:

• Big data analytics is crucial for infectious disease control, outbreak response, and policy modeling.
• Significant ethical concerns arise from algorithmic reliance, data complexity, profiling, and surveillance.
• The integration of data from personal devices presents new ethical considerations.

Conclusions:

• Ethical considerations must be integrated into the development and deployment of big data analytics in infectious diseases.
• Transparent ethical frameworks are necessary for societal acceptance and responsible innovation.
• Addressing these ethical challenges is vital for leveraging big data's potential while safeguarding individual and societal values.