• Pre-Collegiate Global Health Review

How Technology Helps Protect Global Health and Fight the COVID-19 Pandemic

Updated: Jan 13

By Kush Parikh, Troy High School, Troy, Michigan, USA


Whether it is mindlessly scrolling through social media, or even using voice assistant devices to order products online, there is no doubt that technology has fundamentally changed our lives. As COVID-19 hospitalizations and deaths climb, new and innovative digital technologies are being harnessed to support the global response to COVID-19 (Whitelaw, Mamas, and Van Spall, 2020). With no effective antiviral treatment in sight and vaccines only just becoming available, global efforts have been focused on containment and prevention strategies. The countries with the most effective handling of the virus have successfully implemented digital technologies to aid in contact tracing, patient diagnosis through artificial intelligence, and telemedicine for remote treatment options.


Contact tracing lets people know if they may have been exposed to COVID-19 and if they should self-isolate and quarantine (Centers for Disease Control and Prevention, 2020). Digital contact tracing helps the community by reducing the reliance on human recall and by quickly and effectively compiling information from densely populated areas with high transmission. Singapore has already launched a mobile application that sends short distance Bluetooth signals when individuals are in close contact with each other (Fig. 1). South Korea has taken a more aggressive approach by also using facial recognition technology and global positioning system (GPS) data from vehicles. South Koreans receive emergency text alerts if they might have had contact with an infected individual, instructing them to report to testing centers and to quarantine. This has been extremely effective as South Korea has among the lowest per-capita COVID-19 mortality rates in the world (Whitelaw et al., 2020). However, this technology does have its pitfalls. For example, not all identified exposure requires quarantine. A key limitation to this technology is that a large proportion of the population needs to have phones and needs to comply with the advice given, for these applications to be effective. Overall, this technology is successful in driving down transmission and should be adopted by developed countries with the technological infrastructure already in place.

Figure 1: Retrieved from Nature Medicine, Digital technologies in the public-health response to COVID-19. https://www.nature.com/articles/s41591-020-1011-4


In addition to contact tracing, artificial intelligence (A.I.) is a noticeable technology with the potential to improve the treatment and the reported outcome of COVID-19 patients by being an evidence-based medical tool. This means that A.I. can use previous patient data from all around the world to make more accurate diagnosis predictions. Using A.I. to diagnose and treat patients takes less time and is less complex than a normal doctor’s visit. The diagram below compares A.I. and non-A.I. based applications (Fig. 2). A.I. is used to quickly and cost-effectively examine irregular symptoms and notify the patients. For example, Singapore created an A.I.-powered chat bot named SGDormBot which is being used for symptom-based mass screening of migrant workers for COVID-19 (Chen and See, 2020). A.I. implements its useful algorithms to develop new diagnosis and management systems for COVID-19 cases. From there, A.I. takes advantage of neural networks to extract visual features of the condition to assist in the monitoring of patients. A.I. also helps with contact tracing of individuals by identifying COVID-19 "hotspots" (Vaishya, Javid, Khan, and Haleem, 2020). Finally, artificial intelligence utilizes collected data to successfully track and forecast the nature of the virus. It can help identify vulnerable regions and people groups and can notify public health officials to take measures accordingly.

Figure 2. Retrieved from Artificial Intelligence (AI) applications for COVID-19 pandemic. https://pubmed.ncbi.nlm.nih.gov/32305024/


A 2019 research project conducted by Chiara Kongoni and Carey Morewedge from Boston University found that most people are reluctant to use medical artificial intelligence even though it outperforms human doctors. The study found that this is because “AI does not consider one’s idiosyncratic characteristics and circumstances. People view themselves as unique…” (Longoni & Morewedge, 2019). These views lead most people to opt for human doctors as their primary source of healthcare. However, during the pandemic, it has been nearly impossible to conduct safe, socially distanced, physical checkups. This led to the advent of telemedicine - the delivery of health care services using information or communication technology (Mahajan, Singh, and Azad, 2020). Telemedicine can be achieved through conferencing apps such as Zoom, Google Meets, etc. In South Korea, the Association of Korean Medicine implemented the Korean Medicine (KM) Telemedicine Center to provide medical services to marginalized patients via the telephone. A total of 1570 treated patients reported an improvement in mental health with an average satisfaction of 8.3 out of 10 (Jang, 2020). There are many pros and cons with the use of telemedicine which is described in the chart (Fig. 3).The use of telemedicine is nothing new, however, over the course of the past few months, it has skyrocketed to over 2200% (Contreras, 2020). The graph (Fig. 4) shows the spike in telemedicine for the Wexner Medical Center in Ohio. In an effort to increase access to expert healthcare, telemedicine has become a new, yet crucial method of practicing medicine.

Figure 3: Retrieved from Indian Pediatrics, Using Telemedicine During the COVID-19 Pandemic. https://pubmed.ncbi.nlm.nih.gov/32412914/

Figure 4: Retrieved from Telemedicine: Patient-Provider Clinical Engagement During the COVID-19 Pandemic and Beyond. https://pubmed.ncbi.nlm.nih.gov/32385614/


All things considered, the integration of digital technology into pandemic policy can help flatten the COVID-19 incidence curve in countries that are still seeing a surge of cases by using digital contact tracing, artificial intelligence, and telemedicine. These technologies have already been proven effective in countries like Singapore and South Korea. The world must come together and use the power of technology to combat this deadly global outbreak.

References


American Medical Association. (n.d.). Telemedicine: Providing Safe Care During Coronavirus Pandemic. AMA Ed Hub. Retrieved from https://edhub.ama-assn.org/pages/telemedicine-cme-course


Budd, J., Miller, B.S., Manning, E.M. et al. (2020, August 7). Digital technologies in the public-health response to COVID-19. Nature Medicine. Retrieved from https://www.nature.com/articles/s41591-020-1011-4


Centers for Disease Control and Prevention. (2020, December 3). Contact Tracing. Retrieved from https://www.cdc.gov/coronavirus/2019-ncov/daily-life-coping/contact-tracing.html


Chen, J., & See, K. C. (2020, October 7). Artificial Intelligence for COVID-19: Rapid Review. Journal of Medical Internet Research. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595751/


Contreras, C.M., Metzger, G.A., Beane, J.D. et al. (2020, May 8). Telemedicine: Patient-Provider Clinical Engagement During the COVID-19 Pandemic and Beyond. Retrieved from https://pubmed.ncbi.nlm.nih.gov/32385614/


Jang, S., Kim, D., Yi, E. et al. (2020, December 16). Telemedicine and the use of Korean Medicine with COVID-19 patients in South Korea: an observational study. JMIR Public Health and Surveillance. Retrieved from https://pubmed.ncbi.nlm.nih.gov/33342765/


Longoni, C., & Morewedge, C. K. (2019, October 30). AI Can Outperform Doctors. So Why Don’t Patients Trust It? Harvard Business Review. Retrieved from https://hbr.org/2019/10/ai-can-outperform-doctors-so-why-dont-patients-trust-it]


Mahajan, V., Singh, T., & Azad, C. (2020, July 15). Using Telemedicine During the COVID-19 Pandemic. Indian pediatrics. Retrieved from https://pubmed.ncbi.nlm.nih.gov/32412914/


Vaishya, R., Javid, M., Khan, I. H., & Haleem, A. (2020, April 14). Artificial Intelligence (AI) applications for COVID-19 pandemic. PubMed. https://pubmed.ncbi.nlm.nih.gov/32305024/


Whitelaw, S., Mamas, A., Topol, E., & Van Spall, H. G. C. (2020, June 29). Applications of digital technology in COVID-19 pandemic planning and response. The Lancet Digital Health. https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30142-4/


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