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Big data for human security: The case of COVID-19
Pedro Cárdenas1, Ioannis Ivrissimtzis1, Boguslaw Obara2
1Dept. Computer Science, Durham University, United Kingdom.
Journal of Computational Science
|February 21, 2022
Summary
Big Data Analytics helps manage COVID-19 social unrest. This framework aids policymakers in addressing pandemic-related societal challenges and maintaining human security.
Area of Science:
- Computational Social Science
- Public Health Informatics
- Data Science
Background:
- The COVID-19 pandemic introduced significant societal shifts and uncertainties, impacting health, economy, and public order.
- Government containment measures have sometimes led to public discontent and social unrest, posing human security risks.
Purpose of the Study:
- To present a big data forecasting and analytics framework.
- To demonstrate the framework's application in addressing COVID-19-induced social unrest.
Main Methods:
- Utilisation of a big data forecasting and analytics framework.
- Analysis of data related to the COVID-19 pandemic and subsequent social unrest.
Main Results:
- The framework provides a powerful tool for policymakers.
- Effective management of the dual challenges of virus containment and social stability.
Conclusions:
- Big Data Analytics is crucial for navigating the complexities of the 'new normal' post-COVID-19.
- The presented framework supports evidence-based decision-making for enhanced human security during pandemics.
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