Abstract
Coronaviruses are a family of viruses found in several animal species, such as bats, cattle, cats, camels, and humans. With more than 1.6 million people dead worldwide, as of December 2020, the Covid-19 pandemic has brought about a unified need to address global health crises more aggressively. There is great urgency in decreasing the impact of a potential future outbreak, which can be done by gathering information about the disease and its effects on humans. Various artificial intelligence (AI) techniques can be utilized for the pandemic, such as COVID (CoV) management, a vast scientific field involving computers performing tasks capable of only human brains. Among the subsets of AI, there are Machine Learning (ML) techniques, which can learn from historical data examples without programming. While no prior data regarding the virus exists, the growing cases make for more data. In this research, we employ a literature review method to understand pandemic management’s current state and how it can benefit by utilizing AI capabilities.
Keywords: Pandemic Management, Artificial Intelligence, Machine Learning, Coronavirus, Covid-19, Intelligent Cities, Smart Cities
References
- 1.Albahri A.S., Hamid R.A. "Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.". Journal of Medical Systems. 2020;44(7) doi: 10.1007/s10916-020-01582-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Bansal A., Padappayil R.P., Garg C., Singal A., Gupta M., Klein A. "Utility of artificial intelligence amidst the COVID 19 pandemic: a review.". Journal of Medical Systems. 2020;44(9):1–6. doi: 10.1007/s10916-020-01617-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Baveja A., Kapoor A., Melamed B. "Stopping Covid-19: A pandemic-management service value chain approach.". Annals of Operations Research. 2020;289(2):173–184. doi: 10.1007/s10479-020-03635-3. https://ezproxy.tcnj.edu:2083/10.1007/s10479-020-03635-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Bird JJ, Barnes CM, Premebida C, Eka’rt A, Faria DR. "Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach.". PLoS ONE. 2020;15(10):e0241332. doi: 10.1371/journal.Pone.0241332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Colvin, G. (2020) “The biggest errors the Trump administration made in response to COVID.” https://fortune.com/2020/11/13/covid-trump-administration-mishandling-mistakes-coronavirus/
- 6.Coronavirus cases:. (n.d.). https://www.worldometers.info/coronavirus/?utm_campaign=homeAdvegas1%3F
- 7.Isaacs D. "Artificial intelligence in healthcare.". Journal of Paediatrics & Child Health. 2020;56(10):1493–1495. doi: 10.1111/jpc.14828. https://ezproxy.tcnj.edu:2083/10.1111/jpc.14828. [DOI] [PubMed] [Google Scholar]
- 8.Jaehun Lee, Suh Taewon Roy D., Baucus M. "Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence.". Journal of Open Innovation. 2019;5(3):1–13. https://ezproxy.tcnj.edu:2083/10.3390/joitmc5030044. [Google Scholar]
- 9.Naudé W. "Artificial intelligence vs COVID-19: limitations, constraints and pitfalls.". Ai & Society. 2020:1. doi: 10.1007/s00146-020-00978-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Niazkar M., Niazkar H.R. "COVID-19 Outbreak: Application of Multi-gene Genetic Programming to Country-based Prediction Models.". Electronic Journal of General Medicine. 2020;17(5) [Google Scholar]
- 11.Ehiorobo O.A. "Strategic Agility and AI-Enabled Resource Capabilities for Business Survival in Post-COVID-19 Global Economy.". International Journal of Information, Business and Management. 2020;12(4):201–213. [Google Scholar]
- 12.Park Y., Casey D., Joshi I., Zhu J., Cheng F. "Emergence of new disease-how can artificial intelligence help?". Trends in Molecular Medicine. 2020 doi: 10.1016/j.molmed.2020.04.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Tekkeşin A.İ. "Artificial Intelligence in Healthcare: Past, Present and Future.". Anatolian Journal of Cardiology / Anadolu Kardiyoloji Dergisi. 2019;22:8–9. doi: 10.14744/AnatolJCardiol.2019.28661. https://ezproxy.tcnj.edu:2083/10.14744/AnatolJCardiol.2019.28661. [DOI] [PubMed] [Google Scholar]
- 14.Vaid S., Kalantar R., Bhandari M. "Deep learning COVID-19 detection bias: accuracy through artificial intelligence.". International Orthopaedics. 2020:1. doi: 10.1007/s00264-020-04609-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Chamola V., Hassija V., Gupta V., Guizani M. "A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact.". Ieee access. 2020;8:90225–90265. [Google Scholar]
- 16.Yaqoob S., Siddiqui A.H., Harsvardhan R., Ahmad J., Srivastava V.K., Verma M.K., Verma P., Singh A.N. "An Overview of Novel Coronavirus SARS-Cov-2 Spanning around the Past, Present and Future Perspectives.". Journal of Pure & Applied Microbiology. 2020;14:775–788. https://ezproxy.tcnj.edu:2083/10.22207/JPAM.14.SPL1.15. [Google Scholar]
- 17.Yigitcanlar, T., Butler, L., Windle, E., Desouza, K. C., Mehmood, R., and Corchado, J. M. (2020) “Can Building ‘Artificially Intelligent Cities’ Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar’s Perspective.” Sensors (14248220), 20(10), 2988. https://ezproxy.tcnj.edu:2083/10.3390/s20102988. [DOI] [PMC free article] [PubMed]
- 18.Yong, S. (2020) “How the pandemic defeated America.” https://www.theatlantic.com/magazine/archive/2020/09/coronavirus-american-failure/614191/
