Did we miss an opportunity to slow Covid-19 spread with IoT?

A day before the ides of March, Inder Singh, Founder and CEO of Kinsa, noticed something interesting and alarming when he looked at the data pouring in from the company’s network of 1.5 million smartphone-app connected thermometers. Fevers were spiking in clusters of people across the United States, and the numbers indicated that this was no ordinary outbreak of influenza or seasonal cold viruses.

“I looked at…the illnesses that were across the country on March 14, and we were like, ‘Whoa, something’s hitting’,” Singh said while speaking on a virtual panel discussion hosted by Stacey on IoT’s Stacey Higginbotham. As it turns out, the event, which was entitled Why didn’t IoT predict Covid-19 and how can it help in the future? may have been misnamed, because Singh and fellow panelists, Dr. Jennifer Radin, an epidemiologist with the Digital Medicine Division at Scripps Research Translational Institute, and Dena Mendelsohn, Director of Health Policy and Data Governance at Elektra Labs, reported that IoT data was, indeed, available to predict the outbreak.

“We did see it coming,” Singh said. “The sad fact is we weren’t listening, or we weren’t proactively using the data that was suggesting it was coming.”

Singh explained that he quickly reported the temperature data anomalies he saw to a Kinsa public health advisor and then to the US Food and Drug Administration. “An official there said, ‘Listen, what you're showing us makes sense – there’s science here – but I’m not sure if it’s credible, because what we’re seeing is hotspots in the northeast and Florida and we haven’t seen case build up there’,” Sing recounted. “Three days later, we started seeing cases.”

On March 18, Kinsa launched an early warning system called HealthWeather™, which is a map that shows where there are unusually high levels of fever in the United States. The idea is to help public health first-responders understand where further investigation and resources may be needed. The image below shows data on May 20 for the area where I live near Chicago.

Other types of data

Mendelsohn and Dr. Radin agreed with Singh about the availability of IoT data to predict the spread of Covid-19.

“We did have enough signals before March that we could have seen it coming, if we were paying attention to the information that we had available to us,” Mendelsohn said. “At the same time, because Covid-19 is by definition so novel, to date no tech gadget has been found to be the magic bullet for tracking or monitoring Covid-19.”

Mendelsohn pointed out that pulse oximetry, which uses an electronic device to measure the level of oxygen in a person’s blood, is another type of data that can predict illness in a population. This measurement can be tracked by wearables such as a Fitbit or an Apple Watch. A potential problem with using this kind of data, however, is that researchers may not be comparing apples to apples.

Mendelsohn recommends four key considerations when using biometric monitoring technology to predict illness:

• Does the technology record accurate measurements?


• Is the device measuring relevant information?


• Are devices being used ubiquitously enough to spot a trend? In some cases, for example, devices may be available to only a small subset of the population.


• Are tools measuring in the same way? For example, a pulse oximeter in a hospital setting may work differently or be more sensitive than one that is incorporated in a wearable device.

Dr. Radin is conducting research to improve disease prediction and prevention by incorporating digital devices, sensors and platforms. As part of an ongoing study of Fitbit users, her team has discovered that changes in resting heartrate can also be a predictor of illness in a population.

“When someone gets sick, their resting heart rate typically increases compared to their average resting heart rate,” she said, adding that sick people are also typically are less active and experience disrupted sleep.

“So, if we’re able to harness kind of this large-scale data from wearables, we can look at population level changes… We found that that can help us predict real time influenza-like illness activity levels.”

What about privacy?

While the possibilities for tracking disease with biometric monitoring are exciting, they also immediately spark concerns about privacy. Simply put: People are unlikely to participate without reassurance that their data is being protected.

Mendelsohn noted that in the US people often think that HIPAA (the Health Insurance Portability and Accountability Act) protects all their health data, but it does not. Data collected by a Kinsa thermometer, for example, is not covered under HIPAA.

“There are ways that your health information can hurt you,” she explained. “It can hurt a person in the financial sector: You may have trouble getting life insurance, getting disability insurance, and it could affect you in the employment context. What we need is our lawmakers to come together and create comprehensive data protection, so that individuals can participate in early-monitoring programs and know that their contribution to the public health is not going to create an individual harm.”

Dr. Radin’s study is opt-in and allows people to choose how much data they share, while Singh noted that Kinsa provides only population-level information as part of its HealthWeather™ tracking.

“You can have both,” Singh said. “You can have perfect personal privacy protections, and you can have access to information on what's going around your community. It is not a balancing act; it is not an equation. You can have 100% of both – we have the ability to design these technologies today.”

Mendelsohn agreed. “This is why it’s about data rights and not about privacy,” she said. “Individuals need to know this. Some companies are going to create data rights as part of their product, and other companies aren’t.”

As part of the TM Forum Digital Ecosystem Management Project, communications service providers and their partners are studying privacy issues and the potential for using IoT and other technologies such as 5G to address health emergencies like Covid-19.

“Architectural design best practice and the embedding of the citizen at the center of the design still needs to happen,” says Joann O’Brien, VP of Digital Ecosystems, TM Forum. “When this happens, meeting privacy requirements becomes exponentially easier to achieve. In many cases relaxing any privacy policy due to impacts on innovation is really playing into the hands of lazy architectures and exploitative technologies. We advocate continuing and upholding the privacy rules as the long-term consequences of not doing so will have a negative impact on society and potentially run the risk of citizens loosing trust in technology.”

She adds: “In order to live with the virus, I would like to see us move on towards a more citizen-empowered model. In doing so, it makes designing privacy from the beginning much simpler and could help manage the balance between epidemiology and privacy.”

You can watch the discussion between Mendelsohn, Dr. Radin and Singh in its entirety below:

Proving the concept

An upcoming TM Forum Catalyst proof of concept championed by China Mobile, China Telecom and China Unicom aims to show how the integration of telco data and other public data – via a trust-based data platform – can help cities foster better collaboration and a speedier, coordinated response to Covid-19.

Another project called Skynet, which was supported by 11 large telcos (BT, Chunghwa Telecom, Deutsche Telekom, Du, NTT Group, Orange, Verizon, Vodafone, Telenet Group, Telecom Italia and Telus) has demonstrated how 5G could help tackle pandemics. The team developed a portal for hospitals worldwide to order a variety of services, including basics like voice and video along with more advanced offerings such as remote robotic surgery, advanced diagnostic/IoT sensors, and drone and disaster management – all made possible through 5G network slicing.

Watch this video to learn more about the Skynet Catalyst:


To learn more about TM Forum’s Digital Ecosystem Management Project or to find out how you can get involved in a Catalyst proof of concept project, please contact Joann O’Brien. You can also listen to an interesting discussion about the impact of Covid-19 on telecoms by clicking below.