Artificial Intelligence To The Rescue Of Coronavirus Epidemic

Since the first outbreak of Coronavirus (COVID-19) in Wuhan, China, the strain is stronger than ever now changing its mechanisms by the day and even by the hours. It is deadlier than seasonal influenza or what we know about SARS and MERS, which has recorded about 3.4% death cases globally so far as per the World Health Organization. Having spread across at least 100 countries, COVID-19 has turned out to be a growing global public health emergency.

Not only does it threaten lives, but it is affecting businesses, ruining the travel across the world and raising anxieties over the global economy. Despite having similarities with seasonal influenza, COVID-19 has some ambiguous properties with relatively new features preventing scientists from discovering a specific treatment or a vaccine. Also, it is as transmissible as influenza. As it is evolving, immunity is not so strong to avoid its risks, putting the entire human population to COVID-19 infection threats. Amid this global crisis, where even the slightest contact to the virus proves to be the deadliest, Artificial Intelligence reinvents the global efforts in curbing the further health risks by the pandemics.  

AI Fights with Coronavirus

We have already witnessed how quickly China has enabled faster and better response to this epidemic with the effective application of AI. They have brought to the rescue a range of Artificial Intelligence-equipped tools such as disinfecting robots, drones powered by thermal cameras, smart helmets, and facial recognition-based software suites.

But, how do these so common technologies like Machine Learning and Artificial Intelligence provide excellent assistance in the battle of disease prevention?

Artificial Intelligence expanding its capabilities with new dimensions to sustainability

Big data analytics is the step towards implementing the right strategy for the prevention of further disease transmission, which Machine learning and Artificial Intelligence can work with.

Discovering vaccines, treatments, and cures

It is not unknown that COVID-19 has no specific treatment and vaccines. But unlike the SARS outbreak that took more than a year to develop the right cures through clinical trials, by which point the pandemic came to end, AI seems to provide with some breakthrough in R&D for the discovery of effective treatments.

A deep insight into the patterns of COVID-19 is enabled using advanced AI techniques. This process helps analyze the genetic makeup against the already known virus mechanisms speeding up the research outcomes. Also, it is reported that an analysis could be made faster. One such instance reflected an analysis of the coronavirus RNA which was reduced from 55 minutes to 27 seconds. What does it mean? This AI-based analysis can lead to a rapid quarantine process through effective isolation.

Genetic sequencing is a critical part of understanding the mutations of the original virus prompting for continuous testing which is time-consuming. The computational power of AI is used to create vaccines through generating information involving genetic sequencing which is fast and accurate to obtain the right virus sample without spending much on the logistics costs. This could be another positive side to AI that gives confidence to several clinical libraries to roll out vaccines for clinical trials shortly.

Given trials, some challenges are likely in the forms of lack of resources and effective coordination to deploy the doses across the needy locations. For now, curbing transmission through containment as much as possible appears effective

Big data analytics for containment

To protect the public health from the threats of coronavirus, AI and data analytics can be leveraged to gain access to early signs that would probably point at the possible outbreak of the epidemic. Using the sophisticated AI tools and techniques, we can mobilize and put into use some specific strategies to identify, allocate resource and contain a week earlier than the officials could alert and stop it from spreading. These predetermined actions are more robust in combating a large-scale epidemic.

The government health insurance database is the most reliable source for harnessing essential data, which can be overlaid with immigration and customs databases and a robust data analytics platform can be orchestrated.

More so, we can derive information from different sources, e.g. clinical emergency data, flight records, social media, physicians’ records, and not to mention the sales records of anti-fever medication.

AI experts must adhere to the changing patterns of the events as to how they appear in a specific epidemiological outbreak and observe to find rare but meaningful traces of events such as glaring absenteeism from school in a certain area. For case identification, big data analytics provides real-time alerts as early as it detects clinical symptoms and travel records during a medical visit.

Novel technologies such as QR code tracking feature and online reporting of travel history may provide a new dimension to detect health risks of the travelers in the last 14 days amid the coronavirus crisis. Thereby, availing these reports much earlier can help health care systems or the government improve the scopes for effective quarantine procedures for patients or have an adequate supply of antiviral medications or materials.

For limiting the disease further, AI can provide an opportunity to predict the next probable outbreaks with a new virus by allowing scanning high traffic areas like the food market.

Taiwan has been successful so far in controlling the spread of COVID-19 by following active methods of big data analytics. Despite being 81 miles away from China and extremely high-risk, the country recorded 49 COVID-19 cases with only one death. Other countries too should establish a data analytics-based public health response mechanism to enable rapid action in battling the virus outbreak.

AI for quarantine

Policymakers can’t put patients into quarantine whenever they want to. Because it can result in disruptive consequences and contribute to negative long-term effects. Hence, health care systems must know when and how they need to isolate people. Syndromic Surveillance can be put into use to relay information outside of a clinical belt about the possible disease risks. By enabling statistical analysis using text mining and natural language processing, AI can watch activities on social media to corroborate data that could hint about patterns found in coronaviruses. Thereby, the combined efforts of syndromic surveillance and social media analytics help analyze rare events from different data sources and ease the investigation, speeding up the process of efficient and effective quarantine process.

Disease detection at hospitals and outside

For AI firms, this is not an opportunity to scale as AI leaders, but an utmost responsibility to extend help in tackling 2019- nCov.

Facial recognition cameras can be upgraded with technologies to scan crowds for symptoms and identify people not wearing masks. Deployed across schools, stations, and community centers, AI-enabled tools can identify faces covered with masks without tampering with its accuracy level.

Using a thermal sensor embedded on the smartphone, a real-time temperature can be measured in the public place. A similar feat can be achieved using an infrared sensor in combination with AI technology and computer vision that can detect individuals up to 200 in a crowded place and an alert can be sent to authorities when it detects temperature above 37.3 degrees Celsius since it is the first sign of coronavirus.

Deep learning models reduce the time for CT scan reports and show performance enhancement for radiologists. Thus, it holds the potential for encouraging early disease diagnosis, isolation and limiting the epidemic.

Since it is highly transmissible, AI can help in automating tasks for nurses and physicians. The capability of these systems including chatbots can generate an accurate report during a survey for detecting citizens for symptoms.

The wrap-up

AI drives decisions. And with data-driven decisions, we can act fast and smart by taking up immediate steps to prevent the coronavirus from spreading further. Irrational behavior and panic are most likely during an epidemic. But policy should be made to educate people through constant research and development. So, we need to remain vigilant while investing in new vaccine technologies to create a robust health care system. In the pursuit of this achievement, AI-powered solutions can help.