IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v5y2024i3d10.1007_s43069-024-00362-4.html
   My bibliography  Save this article

Exploring the Effectiveness of Graph-based Computational Models in COVID-19 Research

Author

Listed:
  • Dennis Opoku Boadu

    (University of Ghana)

  • Justice Kwame Appati

    (University of Ghana)

  • Joseph Agyapong Mensah

    (Ashesi University)

Abstract

The world has witnessed various scientific disciplines’ rapid growth and advancement, leading to groundbreaking discoveries and advances in multiple fields in recent years. One such field that has gained significant attention, particularly during the COVID-19 pandemic, is the application of graph theory techniques in studying the spread and mitigation of the virus. In this paper, we delve into the intricacies of graph theory and its utilization in analyzing COVID-19, shedding light on the innovative approaches researchers worldwide employ. Also, the study evaluates the various implementation of graph theories in spreading and controlling the virus using diverse datasets. The researchers retrieved several works in the COVID-19 and graph theory field from digital databases. However, studies deducted that GT approaches, algorithms and techniques offer insights into transmission hotspots, spread dynamics in social, control and mobility networking, vaccination optimization, evaluation of interventions and epidemic prediction, among other valuable findings. Limitations and future directions were also directed in the study.

Suggested Citation

  • Dennis Opoku Boadu & Justice Kwame Appati & Joseph Agyapong Mensah, 2024. "Exploring the Effectiveness of Graph-based Computational Models in COVID-19 Research," SN Operations Research Forum, Springer, vol. 5(3), pages 1-41, September.
  • Handle: RePEc:spr:snopef:v:5:y:2024:i:3:d:10.1007_s43069-024-00362-4
    DOI: 10.1007/s43069-024-00362-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-024-00362-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s43069-024-00362-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Wei Cao & Xifu Wang, 2022. "Brittleness Evolution Model of the Supply Chain Network Based on Adaptive Agent Graph Theory under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    4. Mohammad Reza Davahli & Krzysztof Fiok & Waldemar Karwowski & Awad M. Aljuaid & Redha Taiar, 2021. "Predicting the Dynamics of the COVID-19 Pandemic in the United States Using Graph Theory-Based Neural Networks," IJERPH, MDPI, vol. 18(7), pages 1-12, April.
    5. Per Block & Marion Hoffman & Isabel J. Raabe & Jennifer Beam Dowd & Charles Rahal & Ridhi Kashyap & Melinda C. Mills, 2020. "Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world," Nature Human Behaviour, Nature, vol. 4(6), pages 588-596, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shuangqing Sheng & Wei Song & Hua Lian & Lei Ning, 2022. "Review of Urban Land Management Based on Bibliometrics," Land, MDPI, vol. 11(11), pages 1-25, November.
    2. Gour Gobinda Goswami & Tahmid Labib, 2022. "Modeling COVID-19 Transmission Dynamics: A Bibliometric Review," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    3. Das, Kallol & Patel, Jayesh D. & Sharma, Anuj & Shukla, Yupal, 2023. "Creativity in marketing: Examining the intellectual structure using scientometric analysis and topic modeling," Journal of Business Research, Elsevier, vol. 154(C).
    4. Ying Liang & Wei Song, 2022. "Ecological and Environmental Effects of Land Use and Cover Changes on the Qinghai-Tibetan Plateau: A Bibliometric Review," Land, MDPI, vol. 11(12), pages 1-23, November.
    5. Lanzalonga Federico & Chmet Federico & Petrolo Basilio & Brescia Valerio, 2023. "Exploring Diversity Management to Avoid Social Washing and Pinkwashing: Using Bibliometric Analysis to Shape Future Research Directions," Journal of Intercultural Management, Sciendo, vol. 15(1), pages 41-65, March.
    6. Hutchinson, Mark C. & Lucey, Brian, 2024. "A bibliometric and systemic literature review of biodiversity finance," Finance Research Letters, Elsevier, vol. 64(C).
    7. Ballouk, Hossein & Ben Jabeur, Sami & Challita, Sandra & Chen, Chaomei, 2024. "Financial stability: A scientometric analysis and research agenda," Research in International Business and Finance, Elsevier, vol. 70(PA).
    8. Jin Su & Mo Wang & Mohd Adib Mohammad Razi & Norlida Mohd Dom & Noralfishah Sulaiman & Lai-Wai Tan, 2023. "A Bibliometric Review of Nature-Based Solutions on Urban Stormwater Management," Sustainability, MDPI, vol. 15(9), pages 1-23, April.
    9. Manta Eduard Mihai & Davidescu Adriana Ana Maria & Geambasu Maria Cristina & Florescu Margareta Stela, 2023. "Exploring the research area of direct taxation. An empirical analysis based on bibliometric analysis results," Management & Marketing, Sciendo, vol. 18(s1), pages 355-383, December.
    10. Khan, Ashraf & Goodell, John W. & Hassan, M. Kabir & Paltrinieri, Andrea, 2022. "A bibliometric review of finance bibliometric papers," Finance Research Letters, Elsevier, vol. 47(PA).
    11. Ajjima Jiravichai & Ruth Banomyong, 2022. "A Proposed Methodology for Literature Review on Operational Risk Management in Banks," Risks, MDPI, vol. 10(5), pages 1-18, May.
    12. Deepa Sharma & Suman Chakraborty & Ashwath Ananda Rao & Lumen Shawn Lobo, 2023. "The Relationship of Corporate Social Responsibility and Firm Performance: A Bibliometric Overview," SAGE Open, , vol. 13(1), pages 21582440231, March.
    13. Riaz Tabassum & Selama Aslam Izah & Nor Normaziah Mohd & Hassan Ahmad Fahmi Sheikh, 2024. "Meaningful Review of Existing Trends, Expansion, and Future Directions of Green Bond Research: A Bibliometric Approach," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 34(1), pages 1-36, March.
    14. Albiona Pestisha & Zoltán Gabnai & Aidana Chalgynbayeva & Péter Lengyel & Attila Bai, 2023. "On-Farm Renewable Energy Systems: A Systematic Review," Energies, MDPI, vol. 16(2), pages 1-25, January.
    15. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    16. Abidin Kemeç & Ayşenur Tarakcıoglu Altınay, 2023. "Sustainable Energy Research Trend: A Bibliometric Analysis Using VOSviewer, RStudio Bibliometrix, and CiteSpace Software Tools," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    17. Dušan Nikolić & Dragan Ivanović & Lidija Ivanović, 2024. "An open-source tool for merging data from multiple citation databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4573-4595, July.
    18. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
    19. Bhavna Thawani & Tushar Panigrahi & Meena Bhatia, 2024. "Eleven years of integrated reporting: a bibliometric analysis," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 21(4), pages 666-684, December.
    20. Ghousia Jabeen & Gurunadham Goli & Kafila & R. Gobinath, 2024. "A bibliometric review on gender equity in human resource management," Future Business Journal, Springer, vol. 10(1), pages 1-18, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:snopef:v:5:y:2024:i:3:d:10.1007_s43069-024-00362-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.