A review of emerging innovations in COVID-19


  • Sakshi Saggi Independent Researcher Review Article, India




Artificial intelligence, Big data, COVID-19, Disruptive innovation, Internet of Things, Virtual reality


The COVID-19 pandemic has globally impacted humanity. Human health, productivity, social life and function is affected. Every country has felt effects, domestic as well as international. Emerging technologies also known as disruptive technologies have played a significant role in the pandemic. This literature review is a manifest overview on the utilization of existing technologies during the COVID-19 pandemic. The strengths, weakness, opportunities and threats of the innovative technologies under review have been summarized. Their benefits and further scope of disruptive innovations have been reviewed. The review aims to identify and highlight approaches/gaps for improvement and future application.


Christensen institute. Fact sheet: Disruptive innovations. Available at: https://www. christenseninstitute.org/disruptive-innovations/. Accessed on 1 November 2021.

Trewartha A, Dagdelen J, Huo H, Cruse K, Wang Z, He T. (2020). An automated COVID-19 research aggregation and analysis platform. COVID Scholar. 2020.

IBM Cloud Education. What is artificial intelligence (AI)? Available at: https://www.ibm.com/cloud/ learn/what-is-artificial-intelligence. Accessed on 1 November 2021.

Elwazir MY, Hosny S. Artificial intelligence in COVID-19 ultrastructure. J Microsc Ultrastruct. 2020;8(4):146-7.

Chua F, Armstrong-James D, Desai SR, Barnett J, Kouranos V, Kon OM, et al. The role of CT in case ascertainment and management of COVID-19 pneumonia in the UK: insights from high-incidence regions. Lancet. 2020;8(5):438-40.

Pankhania M. Artificial intelligence and radiology: combating the COVID-19 conundrum. Indian J Radiol Imaging. 2021;31(1):4-10.

Born J, Beymer D, Rajan D, Coy A, Mukherjee VV, Manica M, et al. On the role of artificial intelligence in medical imaging of COVID-19. Patterns. 2021;2(6):100269.

Deep Mind. Fact sheet: Computational predictions of protein structures associated with COVID-19. Version 3. Available at: https://deepmind.com/ research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19. Accessed on 1 November 2021.

Mohanty S, Harun AI, Rashid M, Mridul M, Mohanty C, Swayamsiddha S. Application of artificial intelligence in COVID-19 drug repurposing. Diabete Metabol Syndrome Clinic Res Rev. 2020;14(5):1027-31.

Zhou Y, Wang F, Tang J, Nussinov R, Cheng F. Artificial intelligence in COVID-19 drug repurposing. Lancet. 2020;2(12):667-76.

Mendels DA, Dortet L, Emeraud C, Oueslati S, Girlich D, Ronat JB, et al. Using artificial intelligence to improve COVID-19 rapid diagnostic test result interpretation. Proceeding Nat Acad Sci. 2021;118(12).

Haleem A, Javaid M, Singh RP, Suman R. Applications of artificial intelligence (AI) for cardiology during COVID-19 pandemic. Sustainable Operat Comp. 2021;2:71-8.

Bekhet S, Hassaballah M, Kenk MA, Hameed M. A. An artificial intelligence based technique for COVID-19 diagnosis from chest X-Ray. NILES. 2020:191-5.

Buzaev IV, Plechev VV, Nikolaeva IE, Galimova R. M. Artificial intelligence: neural network model as the multidisciplinary team member in clinical decision support to avoid medical mistakes. Chronic Dis Translation Med. 2016;2(3):166-72.

Luo Z, Hu X, Tian X, Luo C, Xu H, Li Q, et al. (2019). Structure-property relationships in graphene-based strain and pressure sensors for potential artificial intelligence applications. Sensors. 2019;19(5):1250.

Das AK, Mishra S, Gopalan S. Predicting COVID-19 community mortality risk using machine learning and development of an online prognostic tool. Peer J. 2020;8:10083.

Elhoseny M, Shankar K, Uthayakumar J. Intelligent diagnostic prediction and classification system for chronic kidney disease. Scientif Rep. 2019;9(1):9583.

Mendes RG, Souza CR, Machado MN, Correa PR, DiThommazo-Luporini L, Arena R, et al. Predicting reintubation, prolonged mechanical ventilation and death in post-coronary artery bypass graft surgery: a comparison between artificial neural networks and logistic regression models. Archiv Med Sci. 2015;11(4):756-63.

Gozes O, Frid-Adar M, Greenspan H, Browning PD, Zhang H, Ji W, et al. Rapid AI development cycle for the coronavirus (COVID-19) pandemic: Initial results for automated detection & patient monitoring using deep learning CT image analysis. arXiv. 2020:5037.

Kundu S, Elhalawani H, Gichoya JW, Kahn CE. How might AI and chest imaging help unravel COVID-19's mysteries? Radiology. 2020;2(3):200053.

Cai X, Fry CV, Wagner CS. International collaboration during the COVID-19 crisis: autumn 2020 developments. Scientometric. 2021:1-10.

Nagendran M, Chen Y, Lovejoy CA, Gordon AC, Komorowski M, Harvey H, et al. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies. BMJ. 2020;368:689.

Wang G, Liu X, Li C, Xu Z, Ruan J, Zhu H, et al. A noise-robust framework for automatic segmentation of COVID-19 pneumonia lesions from CT images. IEEE Transact Med Imaging. 2020;39(8):2653-63.

Mello MM, Wang CJ. Ethics and governance for digital disease surveillance. Science. 2020;368(6494):951-4.

Aeris India. Fact sheet: What is Iot? Available at: https://www.aeris.com/in/what-is-iot/. Accessed on 1 November 2021.

Nasajpour M, Pouriyeh S, Parizi RM, Dorodchi M, Valero M, Arabnia HR. Internet of things for current covid-19 and future pandemics: an exploratory study. J Healthcare Informat Res. 2020;4(4):325-64.

IoT For All. Fact sheet: IOT based mobile applications and its effect on the user experience. Available at: https://www.iotforall.com/mobile-iot/. Accessed on 1 November 2021.

Europe PMC. Fact sheet: Smart city projects against COVID-19: Quantitative evidence from China. Available at: https://europepmc.org/article/PMC/PMC8015371. Accessed on 1 November 2021.

Singh RP, Javaid M, Haleem A, Suman R. Internet of things (IoT) applications to fight against COVID-19 pandemic. Diabetes Metabol Syndrome. 2020;14(4):521-4.

Visionstate Corp. Fact sheet: Visionstate ships first IOT buttons for rapid response to cleaning alerts. GlobeNewswire News Room. Available at: https://www.globenewswire.com/news-release/2020/03/23/2004645/0/en/Visionstate-Ships-First-IoT-Buttons-for-Rapid-Response-to-Cleaning-Alerts.html. Accessed on 1 November 2021.

South China Morning Post. Fact sheet: Spain's military uses DJI agricultural drones in fight against COVID-19. Available at: https://www.scmp.com/ tech/gear/article/3077945/spains-military-uses-dji-agricultural-drones-spray-disinfectant-fight. Accessed on 1 November 2021.

Dong Y, Yao YD. IOT platform for COVID-19 prevention and control: a survey. IEEE Access. 2021;9:49929-41.

Javaid M, Khan IH. Internet of things (IOT) enabled healthcare helps to take the challenges of covid-19 pandemic. Journal of Oral Biology and Craniofacial Research. 2021;11(2):209-14.

Gupta M, Abdelsalam M, Mittal S. (2020, April 13). Enabling and enforcing social distancing measures using smart city and its infrastructures: a COVID-19 use case. AR Xiv. 2020.

Gupta R, Ghosh A, Singh AK, Misra A. Clinical considerations for patients with diabetes in times of COVID-19 epidemic. Diabetes Metabol Syndrome Clinic Res Rev. 2020;14(3):211-2.

Hanna TP, Evans GA, Booth CM. Cancer, COVID-19 and the precautionary principle: Prioritizing treatment during a global pandemic. Nature Rev Clinic Oncol. 2020;17(5):268-70.

Wong TY, Bandello F. Academic Ophthalmology during and after the COVID-19 pandemic. Ophthalmology. 2020;127(8):51-2.

Mantovani E, Zucchella C, Bottiroli S, Federico A, Giugno R, Sandrini G, et al. Telemedicine and virtual reality for cognitive rehabilitation: a roadmap for the COVID-19 pandemic. Front Neurol. 2020;11:926.

Alyaqout K, AlQinai S, Almazeedi S, Karim JS, Al-Youha S, Al-Sabah S. Applying augmented reality to treat Fournier's gangrene in COVID-19 positive patients whilst safeguarding the multi-disciplinary surgical team: A case series. Int J Surg Case Rep. 2020;79:335-8.

Singh RP, Javaid M, Kataria R, Tyagi M, Haleem A, Suman R. Significant applications of virtual reality for COVID-19 pandemic. Diabetes Metabol Syndrome. 2020;14(4):661-4.

Atli K, Selman W, Ray A. A comprehensive multicomponent neurosurgical course with use of virtual reality: modernizing the medical classroom. J Surgic Educ. 2021;78(4):1350-6.

Siani A, Marley SA. Impact of the recreational use of virtual reality on physical and mental wellbeing during the COVID-19 lockdown. Health Technol. 2021;11(2):425-35.

Riva G, Wiederhold BK. How cyberpsychology and virtual reality can help us to overcome the psychological burden of coronavirus. Cyberpsychol Behavior Soc Network. 2020;23(5):277-9.

Health IT Analytics. Fact sheet: Intersection of big data analytics, COVID-19 top focus of 2020. Available at: https://healthitanalytics.com/ news/intersection-of-big-data-analytics-covid-19-top-focus-of-2020. Accessed on 1 November 2021.

Alsunaidi SJ, Almuhaideb AM, Ibrahim NM, Shaikh FS, Alqudaihi KS, Alhaidari FA, et al. Applications of big data analytics to control COVID-19 pandemic. Sensors. 2021;21(7):2282.

Wu J, Wang J, Nicholas S, Maitland E, Fan Q. Application of big data technology for COVID-19 prevention and control in China: lessons and recommendations. J Med Intern Res. 2020;22(10),:21980.

Ngan OM, Kelmenson AM. Using big data tools to analyze digital footprint in the COVID-19 pandemic: some public health ethics considerations. Asia Pac J Pub Health. 2020;33(1):129-30.

Ahmed I, Ahmad M, Jeon G, Piccialli F. A framework for pandemic prediction using Big Data Analytics. Big Data Res. 2021;25:100190.

Qiu HJ, Yuan LX, Wu QW, Zhou YQ, Zheng R, Huang XK, et al. Using the internet search data to investigate symptom characteristics of COVID-19: A Big Data study. World J Otorhinolaryngol Head Neck Surg. 2020;6(1):40-8.

Alotaibi S, Mehmood R, Katib I. The role of Big Data and Twitter data analytics in healthcare supply chain management. Smart Infrastruct App. 2019:267-79.

Guardian News and Media. UK coronavirus victims have lain undetected at home for two weeks. Available at: https://www.theguardian.com/ world/2020/jun/07/uk-coronavirus-victims-have-lain-undetected-at-home-for-two-weeks. Accessed on 1 November 2021.




How to Cite

Saggi, S. (2021). A review of emerging innovations in COVID-19. International Journal Of Community Medicine And Public Health, 9(1), 376–383. https://doi.org/10.18203/2394-6040.ijcmph20214808



Review Articles