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Leveraging Data Science to Combat COVID-19: A Comprehensive Review
Siddique Latif1,2, Muhammad Usman3,4, Sanaullah Manzoor4
1University of Southern Queensland Springfield Queensland 4300 Australia.
IEEE Transactions on Artificial Intelligence
|November 20, 2023
Summary
This review systematizes data science applications for COVID-19 research, covering AI, machine learning, and data visualization. It identifies key datasets, analyzes research trends, and highlights challenges in combating the pandemic.
Area of Science:
- Data Science
- Infectious Disease Research
- Public Health
Background:
- The COVID-19 pandemic, caused by SARS-CoV-2, rapidly spread globally starting in March 2020.
- Over 21 million cases were reported worldwide by mid-August 2020, necessitating urgent research efforts.
- Data science offers powerful tools for understanding and mitigating the pandemic's impact.
Purpose of the Study:
- To systematically review and categorize COVID-19 research utilizing data science methods.
- To survey available public datasets and repositories for tracking disease spread and mitigation.
- To provide a bibliometric analysis of early COVID-19 data science research and identify common challenges.
Main Methods:
- Broad definition of data science, including artificial intelligence (AI), machine learning (ML), statistics, modeling, simulation, and data visualization.
- Comprehensive literature review of recent COVID-19 research leveraging data science.
- Survey of public datasets and repositories relevant to COVID-19.
- Bibliometric analysis of published research papers.
- Identification and discussion of common challenges and pitfalls.
Main Results:
- A systematic overview of diverse data science applications in COVID-19 research.
- Identification of key public datasets and repositories for epidemiological tracking and intervention analysis.
- A bibliometric analysis revealing the rapid growth and focus areas of COVID-19 data science research.
- A curated list of common challenges and potential pitfalls in applying data science to pandemic response.
Conclusions:
- Data science plays a crucial role in understanding, tracking, and combating the COVID-19 pandemic.
- Accessible datasets and robust data science methodologies are vital for effective public health responses.
- Continued development and sharing of resources, like the live repository provided, are essential for ongoing research and mitigation efforts.
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