They are creating ways to track cases, sterilize surfaces and find vaccines. Their innovations may even help prevent the next pandemic.

One of the deadliest problems in the fight to contain the coronavirus pandemic has been our inability to quickly identify who’s been exposed to this invisible enemy. Long and asymptomatic incubation periods make it difficult to know who to quarantine. Authorities, striving to slow the disease’s spread, are asking entire populations to stay at home, forcing economies to grind to a near-halt.

Seeking to change all that, scientists are using artificial intelligence (AI) and Big Data in healthcare to develop ways that will help identify infected individuals, clean contaminated surfaces and treat—as well as prevent—infection.

Some tools are already being deployed; others are in development. COVID-19 is not the last virus the world will have to battle, and it may be that AI and Big Data could help prevent a pandemic like this one from happening again.

What can AI and Big Data do to fight the spread of infectious diseases?  

  • “Population health visualization” can help with early detection, intervention and prevention
  • Robots sterilizing surfaces can help control the spread of infections
  • Genetic sequencing and tools to identify the shape of virus proteins can expedite the discovery of effective treatments and vaccines

Here is how they do that:

The size of the U.S. surge suggests the virus has been spreading undetected for weeks.1 Mass testing is one cure for our inability to detect it fast enough. But it is only one.

Imagine if we could also quickly map geographically and track over time the occurrence of symptoms associated with a virus. What if we could identify links between the people who test positive and the people with whom they were likely to have come in contact? What if we could see those in the context of international and domestic travel patterns?

The future of Big Data and AI in healthcare is wide open.

Even now, data-based companies have epidemic forecasting models that integrate expansive medical databases with daily worldwide media outlets reporting and real-time travel patterns. Access to these forecasts could provide early detection and improve decision making by both governments and individuals to help prevent the spread of disease and save lives.

Several AI-based epidemic forecasting companies did generate alerts before there were officially reported cases of COVID-19 in the United States. BlueDot first spotted “unusual pneumonia” on December 30, 2019, published a paper predicting a global spread, and identified 11 cities after Wuhan that would next see COVID-19 cases. Metabiota in late February 2020 accurately predicted that Italy, Korea and the United States were at high risk of becoming the next hot spots for this novel coronavirus.

Other companies can already provide real-time mapping of disease incidence to help identify where to focus policy efforts. For example, Kinsa provides real-time data of atypical influenza-like symptoms collected from at least one million customers using its smart app–linked thermometers. Another company, Relola, has developed a mapping solution based on anonymous self-reports of health status and symptoms.

Imagine taking that effort to the next level with scalable chatbot technology that asks an entire population to give updates of daily health status and record any symptoms. We could create a comprehensive view of health conditions by geography, or any other category or interest. Authorities could direct policy efforts where needed most.

The U.S. Health Weather Map

This was developed by Kinsa in collaboration with a professor at Oregon State University, showing data from March 18 to April 8, 2020. Courtesy of Kinsa Inc.
Map showing how much influenza-like illness above the normal expected levels have been detected, in the U.S., since March 1. The map color-codes to show areas with many cases (red), moderate cases (dark orange), mild (light orange) and low (yellow). The map highlights that areas such as New York, areas of Michigan, and areas of Florida are some coded as red. Image is courtesy of Kinsa, Inc.

This technology might empower individuals as well as policymakers. What if you could easily find out that you’d been in contact with someone who’d been diagnosed with COVID-19? You’d likely self-quarantine and seek medical assistance. Indeed, just recently, Apple and Google introduced a plan for a Bluetooth-based opt-in contact tracing app which would alert its users of their potential exposure to someone with COVID-19.

In China, Qihoo 360 developed an app using mass data aggregation that lets people know whether they’ve traveled recently alongside someone infected with COVID-19. All you have to do is enter your travel date and flight number. More than 21 million people used the service within two days of its launch.

Robot-based technologies, already in use and proven effective, are likely to be increasingly adopted because they improve the efficiency of sterilization efforts while minimizing the risk of human exposure and reducing the threat of spreading an infection.

Germ-zapping robots can completely disinfect surfaces. Studies are finding that disinfecting robots can decrease environmental infection rates between 50% and 100%.2 Unsurprising, then, that some hospitals and hotels are using these tools.

Semi-autonomous UVD robots from Blue Ocean Robotics use ultraviolet-C rays to eradicate bacteria and germs from entire rooms faster and safer than humans could.

Similarly, private drone companies can disinfect public outdoor spaces. A single, standard-size drone is capable of carrying up to 2.5 gallons of disinfectant spray and sanitizing an area almost the size of two American football fields.3

Innovations in sequencing and protein structure prediction have allowed the biotech community to begin to experiment with potential solutions to the COVID-19 virus quicker than would previously have been possible.

On January 11, 2020, the Chinese authorities shared the genetic sequence of this novel coronavirus.4 But it isn’t enough to know the genetic sequence for a protein within a virus. It also helps to understand the protein’s structure, which determines its function.5 For example, our bodies use antibody proteins that are Y-shaped, and form unique hooks that latch on to viruses and bacteria, and tag them for elimination.

Discovering the shape of a new protein, such as the coronavirus’s spike protein, which attaches to the host cells and infects them, historically takes experts time and resources (high-resolution imaging tools are needed). In contrast, tech companies such as Baidu and Google DeepMind were able to use AI algorithms to predict the structure of the protein based on its genetic code much faster but just as accurately. 

As a result, the World Health Organization says COVID research has accelerated at an incredible speed.6 There are 70 vaccine candidates in clinical evaluation, including three already in clinical trials, as well as numerous investigations for potential treatments.7 For example:

  • Regeneron plans to begin large-scale manufacturing by mid-April of a virus-neutralizing “cocktail” therapy of antibodies that bind to the spike protein and block its ability to infect the host cells. 
  • Moderna is working on a vaccine that would deliver a spike protein DNA into a patient’s body to safely elicit an immune response. The company was able to go from sequence selection to its first human patient dosing in only 63 days, and under emergency use, could potentially make the vaccine available to some people as early as fall 2020.

On a personal level, the recent news has been frightening and sad. So many people are suffering. There may be some comfort and hope in knowing human ingenuity is developing new tools—using Big Data and AI in healthcare—that may help mitigate the current pandemic, and which could help prevent a crisis of this magnitude from happening again.

On an investment level, AI and Big Data are rapidly reshaping our world. While the use of these technologies is not new, their applications are increasingly reaching more and more industries, and helping solve more and more challenges. The fight against COVID-19 is one very important example.

Reach out to your J.P. Morgan team to learn more about this topic, and to discuss your portfolio in the context of your long-term goals for your wealth.


1 “Coronavirus screening may miss two-thirds of infected travelers entering U.S.” The Harvard Gazette, March 4, 2020.

2 “Bring in the Robot Cleaners: Travel Industry Innovations for the Pandemic,” The New York Times, 3/28/2020.

3 “Fever-Detecting Goggles and Disinfectant Drones: Countries Turn to Tech to Fight Coronavirus,” The Wall Street Journal, March 10, 2020.

4 While much less complex than a human genome (which has 3.2 billion nucleotides), the length of the RNA for this coronavirus family is the largest for any RNA virus (it has 29,904 nucleotides).

5  AlphaFold: Using AI for scientific discovery, January 15, 2020.

6 WHO Director General’s opening remarks at the media briefing on COVID-19, April 6, 2020.

7 Draft landscape of COVID-19 candidate vaccines –11 April 2020.” World Health Organization, April 11, 2020.