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Insights from the COVID-19 Pandemic: A Survey of Data Mining and Beyond

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Abstract

The global health crisis of COVID-19 has ushered in an era of unprecedented data generation, encompassing the virus’s transmission patterns, societal consequences, and governmental responses. Data mining has emerged as a pivotal tool for extracting invaluable insights from this voluminous dataset, offering critical support for informed decision-making. While existing surveys primarily explore methodologies for detecting COVID-19 in medical imagery and official sources, this article comprehensively examines the pandemic through big data mining. We emphasize the significance of social network analysis, shedding light on the pandemic’s profound influence on community socio-economic behavior. Additionally, we illuminate advancements in diverse domains, encompassing behavioral impact analysis on social media, contact tracing implications, early disease screening through medical imaging, and insights derived from health-related time-series data analytics. Our study further organizes the literature by categorizing it based on data sources, dataset types, analytical approaches, techniques, and application scenarios. Finally, we delineate prevailing challenges and forthcoming research prospects, charting the course for future investigations.

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Data Availibility Statement

Data is available from the authors upon reasonable request.

Notes

  1. https://www.who.int/health-topics/infodemic

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Authors and Affiliations

  1. Department of Computer Science, University of Sharjah, Sharjah, UAE

    Imad Afyouni, Ibrahim Hashim & Zaher Aghbari

  2. Department of Computer Science, UAE University, Al Ain, UAE

    Tarek Elsaka

  3. Tawuniya, Data Science Specialist Riyadh, Riyadh, Saudi Arabia

    Mothanna Almahmoud

  4. Computer Science Department, Al al-Bayt University, Mafraq, 25113, Jordan

    Laith Abualigah

  5. MEU Research Unit, Middle East University, Amman, 11831, Jordan

    Laith Abualigah

  6. Applied Science Research Center, Applied Science Private University, Amman, 11931, Jordan

    Laith Abualigah

  7. Jadara Research Center, Jadara University, Irbid, 21110, Jordan

    Laith Abualigah

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  1. Imad Afyouni
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  2. Ibrahim Hashim
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  3. Zaher Aghbari
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  4. Tarek Elsaka
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  5. Mothanna Almahmoud
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  6. Laith Abualigah
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All authors contribute equally.

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Correspondence to Laith Abualigah.

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Afyouni, I., Hashim, I., Aghbari, Z. et al. Insights from the COVID-19 Pandemic: A Survey of Data Mining and Beyond. Appl. Spatial Analysis 17, 1359–1411 (2024). https://doi.org/10.1007/s12061-024-09588-5

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