How machine learning will help us outsmart the coronavirus

COVID-19 is a new disease and we are still learning how it spreads…” At time of this writing, this is the message you’ll find when visiting the CDC (Centers for Disease Control and Prevention) website looking for information on how this novel coronavirus can spread.

What’s been so worrisome about COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is its accelerating rate of transmission. What emerged in Wuhan, China only 3 months ago, has rapidly infected people in nearly every country. According to the World Health Organization (WHO), “It took 67 days for 100,000 cases to be reported, but just 3 days to go from 400,000 to 500,000 cases.” This, despite unprecedented efforts by many countries large and small trying to contain this disease. And as the world finds itself underprepared in dealing with this type of crisis, countless battalions of experts in varying disciplines are contributing to containment and recovery efforts. One such set of experts includes data scientists, software engineers, and automation experts who are unleashing information and technology as our allies in this emergency.

Monitoring and Forecasting

Machine learning is already at work 24/7, assisting with improved tracking of COVID-19 data as well as predicting its spread on domestic and international scale. The breadth and depth of data produced on this pandemic makes it unfeasible for humans to review and analyze. This includes information from global news sources, health organizations, research teams, governments, the travel industry, as well as manufacturing and logistics data.

AI algorithms are being used by a number of experts to examine this mountainous, diverse set of data in order to better identify relevant information and pinpoint valuable correlations that exist between certain data points. For example, how to mitigate transmission risks, how the spread of the disease and its associate mortality rate maps from one area to another during a particular time interval, or how to forecast the efficacy of certain public health practices.

These findings have grown exponentially over recent months and have become the basis for a growing library of research papers now released as part of CORD-19 (the COVID-19 Open Research Dataset)—“the most extensive collection of scientific literature related to the ongoing pandemic.” CORD-19 came together as a result of a global partnership among leading research groups and the dataset is being offered as a free, open resource to researchers everywhere who can benefit from the currently 45,000 plus scholarly articles pertaining to the coronavirus family including COVID-19.

Both traditional data analytics and machine learning can prove essential in analyzing this rapidly expanding sea of data. While traditional data analytics is useful in descriptive ways, explaining current or historical events, machine learning shines in its endless predictive capabilities, learning from different types of structured and unstructured data. Good examples of unstructured data include news articles, images and videos, research reports, or communication threads between any number of people or groups. For this pandemic, AI learning systems can rapidly comb through and analyze massive amounts of data from hundreds of thousands of sources to expose pertinent patterns, correlations, and recommendations.

Diagnosis and Treatment

Modeling the spread of the virus is important and can help save lives by ensuring preparedness, optimized resource allocation, and efficient delivery of care. However, without rapid improvements in diagnosis and treatment, our collective abilities to contain the transmission and treat the virus will continue to be compromised. This is another area where machine learning can be of incredible value. And, in recognition, the U.S. Government has announced the COVID-19 High Performance Computing Consortium to provide researchers access to world-class supercomputers for advanced data science and artificial intelligence modeling.

AI has also silently emerged as a transformative technology for the healthcare industry, enabling incredible efficiencies in diagnosis, drug discovery, and drug development. In some cases, the medical community has already seen the benefits of AI and big data for managing the coronavirus outbreak. WHO and China teamed up for a joint mission, headed by Dr. Bruce Aylward of WHO and Dr. Wannian Liang of the People’s Republic of China, to understand this novel disease and inform next steps for readiness and preparedness of the rest of the global community. The 40-page report released last month describes how these new technologies were implemented “to strengthen contact tracing and the management of priority populations.” As the virus continues to spread, more data is being made available each day, broadening the scope of what can be accomplished with AI technologies.  

Other use cases include computer vision technology used on cameras in airports, railway stations, and other public areas to detect and flag individuals with fever. With this technology, a task which would otherwise require an army of people to administer can now be safely accomplished via machines at a rate of 300 people per minute. Computer vision can also help interpret CT scans and detect coronavirus in as little as 20 seconds versus the estimated 5-15 minutes it would take a human doctor to diagnose. Relying on humans to review and interpret millions of CT images per day is impracticable at best. With computer vision, machines can process those same millions of CT images at lightning speed and with accuracy on par with that of human doctors

Diagnosis is only part of the COVID-19 journey. As the world is currently experiencing in China, Italy, and the United States, healthcare systems are struggling to meet needs for treatment and patient care. Current estimates for availability of a COVID-19 vaccine are as high as 18 months or longer. That doesn’t count the time needed to manufacture and distribute the vaccine at the potential scale required. Even in ordinary times when the world is not facing a global pandemic, development of a single drug or vaccine requires incredible effort, resources, experimentation, testing, and time.

AI and machine learning have already proven successful at accelerating drug discovery by enabling massively more efficient chemical compound analysis, outcome estimation, and drug interaction modeling. These are tasks which can traditionally take billions of dollars and years of effort from armies of scientists before leading to positive results. AI can cut this time and cost significantly, allowing faster migration from discovery to development and ultimately release. Drug development focuses on transforming compounds into products that are safe for consumption, something for which machine learning technologies can be used to improve analysis and drug production yields. Today, the difference between efficiently producing a compound that works and one that doesn’t can mean the difference between making things better or much worse.

Manufacturing and Logistics 

AI has already proven transformative in manufacturing, logistics, delivery infrastructure and other aspects of supply chains. These are critical pillars in the global response to COVID-19 encompassing everything from personal protective equipment (PPE) to life-saving ventilators to everyday household supplies and food items. As demand for supplies and equipment continues to increase the world-over, optimizing these important pillars becomes more important than ever.  The modern supply chain is a vast network of producers, vendors, retailers, distributors, warehouses, and transportation companies connected to create and deliver goods to end customers. This network is complex and rich in data generated by people and the many smart sensors and devices along the entire chain. However, the entities participating in this process are mostly unprepared to fully harness the true power of predictive analytics, real-time insights, and intelligent automation needed to optimize costs, units, and operations. In fact, “94% of the Fortune 1000 are seeing coronavirus supply chain disruptions.” The current pandemic is accelerating work in a number of areas including advanced robotics for delivery and sterilization, as well as machine learning for demand forecasting, risk assessment, sourcing, cost, inventory, and logistics optimization. Delivery networks are also being stretched to the limit with numerous efforts in place to use machine learning to balance load and predict demand while also exploring new AI-powered machine delivery methods such as drone delivery where computer vision plays an important role. 

News and Education

At the Munich Security Conference in February, WHO Director-General Tedros Adhanom Ghebreyesus stated that “We’re not just fighting an epidemic; we’re fighting an infodemic.” Throughout news and social media, citizens are inundated with reports, tips, stats, and more, much of which is unclear, conflicting, and sometimes even inaccurate. This means that important messages can be lost in the noise and misinformation can permeate the knowledge sphere. This is another area where AI can prove valuable.

Similarly to how computer vision systems can rapidly scan images and video feeds at a scale unfeasible by humans, natural language processing (NLP) can be unleashed on the world’s news outlets and social media feeds to synthesize the sheer volume of information, remove redundancies, filter out old news, flag misinformation, and prioritize new or unique content. Misinformation and “fake” news can spread faster than any person can keep up, but AI systems with robust and diverse NLP capabilities can scale as far and wide as needed when powered by the right computing infrastructure.


This novel coronavirus has inspired significant global collaboration with people around the world working day and night to contain, manage, support, and treat those negatively impacted. Over the past several weeks, it has become clear that the need for answers and solutions is growing, and innovation is vital in order to accelerate recovery. Ultimately, the role of machine intelligence is to save time and create efficiency, something which may be more important now than ever before.

Machine learning is a powerful weapon in the arsenal of defense as it can help monitor and forecast the spread of the virus plus provide faster, more precise diagnostics and treatments. But it can also optimize manufacturing and distribution of goods and help in educating the public about the disease and our individual responsibilities in the context of COVID-19’s broader impact on our economy, healthcare system, businesses, and society at large. Significant resources are being poured into solutions which can help healthcare professionals and others rise to this unique challenge. This may be just the beginning, yet we’re already seeing examples where machine learning is helping us outsmart the coronavirus.