Abstract In the early months of 2020, a fast-spreading outbreak was brought about by the new virus SARS-CoV-2. The uncontrolled spread, which led to a pandemic, illustrated the healthcare system’s slow response time to public health emergencies at that time. Blockchain technology was anticipated to be crucial in the effort to contain the COVID-19 pandemic. In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. Modern innovations such as blockchain and artificial intelligence (AI) were shown to be promising in limiting the spread of a virus. Blockchain could specifically aid in the battle against pandemics by supporting early epidemic identification, assuring the ordering of clinical information, and maintaining a trustworthy medical chain during disease tracing. AI also offered smart forms of diagnosing coronavirus therapies and supported the development of pharmaceuticals. Blockchain and AI software for epidemic and pandemic containment were analyzed in that research. First, a new conceptual strategy was proposed to tackle COVID-19 through an architecture that fused AI with blockchain. State-of-the-art research on the benefits of blockchain and AI in COVID-19 containment was then reviewed. Recent initiatives and use cases developed to tackle the coronavirus pandemic were also presented. A case study using federated intelligence for COVID-19 identification was also provided. Finally, attention was drawn to problems and prospective directions for further investigation into future coronavirus-like wide-ranging scenarios.
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Bansal, A., Padappayil, R. P., Garg, C., Singal, A., Gupta, M., & Klein, A. L. (2020). Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review. Journal of Medical Systems, 44(9). 10.1007/s10916-020-01617-3
Cheng, X., Chen, J., Shen, D., Tang, F., & Cao, G. (2020). The integration of blockchain and AI technologies in addressing COVID-19 outbreaks. Journal of Medical Internet Research, 22(8), e20760. 10.2196/20760
Chesbrough, H. (2020). To recover faster from Covid-19, open up: Managerial implications from an open innovation pespective. Industrial Marketing Management, 88, 410–413. 10.1016/j.indmarman.2020.04.010
Colombi, D., Bodini, F. C., Petrini, M., Maffi, G., Morelli, N., Milanese, G., Silva, M., Sverzellati, N., & Michieletti, E. (2020). Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia. Radiology, 296(2), E86–E96. 10.1148/radiol.2020201433
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Dorri, A., Luo, F., Kanhere, S. S., Jurdak, R., & Zhang, R. (2019). SPB: A Secure Private Blockchain-Based Solution for Distributed Energy Trading. IEEE Communications Magazine, 57(7), 120–126. 10.1109/mcom.2019.1800577
Fetzer, T., Hensel, L., Hermle, J., & Roth, C. (2021). coronavirus Perceptions and Economic Anxiety. The Review of Economics and Statistics, 103(5), 968–978. 10.1162/rest_a_00946
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Garg, L., Chukwu, E., Nasser, N., Chakraborty, C., & Garg, G. (2020b). Anonymity Preserving IoT-Based COVID-19 and Other Infectious Disease Contact Tracing Model. IEEE Access, 8, 159402–159414. 10.1109/access.2020.3020513
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Pham, Q., Nguyen, D. H., Huynh-The, T., Hwang, W., & Pathirana, P. N. (2020). Artificial Intelligence (AI) and Big Data for coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts. IEEE Access, 8, 130820–130839. 10.1109/access.2020.3009328
Rangone, A., & Busolli, L. (2021). Managing charity 4.0 with Blockchain: a case study at the time of Covid-19. International Review on Public and Nonprofit Marketing, 18(4), 491–521. 10.1007/s12208-021-00281-8
Ray, P. P., Dash, D., Salah, K., & Kumar, N. (2021). Blockchain for IoT-Based Healthcare: Background, Consensus, Platforms, and Use Cases. IEEE Systems Journal, 15(1), 85–94. 10.1109/jsyst.2020.2963840
Saleh, H. M., Avdoshin, S., & A, D. (2019). Platform for Tracking Donations of Charitable Foundations Based on Blocchain Technology. 10.1109/apsse47353.2019.00031
Saleh, S. N., & Shayor, F. (2020). High-Level Design and Rapid Implementation of a Clinical and Non-clinical Blockchain-Based Data Sharing Platform for COVID-19 Containment. Frontiers in Blockchain, 3. 10.3389/fbloc.2020.553257
Sarker, I. H. (2019). Context-aware rule learning from smartphone data: survey, challenges and future directions. Journal of Big Data, 6(1). 10.1186/s40537-019-0258-4
Shen, J., & Shafiq, M. O. (2019). Learning Mobile Application Usage - A Deep Learning Approach. 10.1109/icmla.2019.00054
Shi, F., Wang, J., Shi, J., Wu, Z., Wang, Q., Tang, Z., He, K., Shi, Y., & Shen, D. (2021). Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19. IEEE Reviews in Biomedical Engineering, 14, 4–15. 10.1109/rbme.2020.2987975
Ting, D. S. J., Carin, L., Dzau, V. J., & Wong, T. Y. (2020). Digital technology and COVID-19. Nature Medicine, 26(4), 459–461. 10.1038/s41591-020-0824-5
Wang, J., Li, M., He, Y., Li, H., Xiao, K., & Wang, C. (2018). A Blockchain Based Privacy-Preserving Incentive Mechanism in Crowdsensing Applications. IEEE Access, 6, 17545–17556. 10.1109/access.2018.2805837
Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where Is Current Research on Blockchain Technology?—A Systematic Review. PLOS ONE, 11(10), e0163477. 10.1371/journal.pone.0163477
Zhou, P., Yang, X., Wang, X., Hu, B. Y., Zhang, L., Zhang, W., Si, H. R., Zhu, Y., Li, B., Huang, C., Chen, H. S., Chen, J. M., Luo, Y., Guo, H., Di Jiang, R., Liu, M., Chen, Y., Shen, X., Wang, X., … Shi, Z. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579(7798), 270–273. 10.1038/s41586-020-2012-7
Singh, S., & Verma, S. B. (2024). Resolving Covid-19 with Blockchain and AI: A Systematic Review. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 13(1), e31454. https://doi.org/10.14201/adcaij.31454
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