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Data analytics during pandemics: a transportation and location planning perspective.
Elif Bozkaya1, Levent Eriskin2, Mumtaz Karatas2
1Department of Computer Engineering, National Defence University, Turkish Naval Academy, 34940 Tuzla, Istanbul Turkey.
Annals of Operations Research
|August 8, 2022
Summary
The COVID-19 pandemic highlighted the importance of data analytics for understanding disease spread and human mobility. This review examines data-driven transportation and location planning solutions used during the pandemic.
Area of Science:
- Public Health
- Transportation Science
- Data Science
Background:
- The COVID-19 pandemic underscored the critical need for reliable data in disease management and prediction.
- Vast amounts of data from diverse sources were processed to understand disease dynamics, human mobility, and travel behavior.
- Data-driven analytics and Operations Research tools became essential for addressing transportation and location planning challenges.
Purpose of the Study:
- To review studies addressing transportation and location problems during the COVID-19 pandemic, with a specific emphasis on data analytics.
- To discuss major data collection streams employed during the pandemic.
- To highlight the significance of rapid and reliable data sharing.
Main Methods:
- Literature review of studies focusing on data analytics for transportation and location problems during the COVID-19 pandemic.
- Analysis of data collection streams and their utilization.
- Discussion of challenges and limitations associated with data usage.
Main Results:
- Data analytics and Operations Research were extensively applied to transportation and location planning during the pandemic.
- Various data collection streams were utilized, emphasizing the need for rapid and reliable data sharing.
- Identified challenges and limitations in data usage for pandemic-related planning.
Conclusions:
- The pandemic demonstrated the indispensable role of data analytics in addressing complex public health and logistical challenges.
- Effective data sharing and robust analytical approaches are crucial for informed decision-making in public health crises.
- Future research should focus on overcoming data limitations and enhancing analytical methodologies for similar future events.
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