At the outbreak of the COVID-19 pandemic, technology workers are trying their best to develop the new technology to help stop the spread of the virus. One of the ways is to monitor the people contact by tracking the location. It raises the concern of the privacy.
Smartphone app to track the spread of the virus at USC
At the USC Michelson Center for Convergent Biosciences, Peter Kuhn is working on an app to monitor a person’s symptoms and location and cross-reference that with information about others the individual may have crossed paths.
“We’ve teamed with a Bay Area company to make a phone app to record and analyze coughs and symptoms and compare it to an individual’s social interactions using GPS,” he said. “It’s all about using data from individuals that becomes a source we can use to help stop the spread of coronavirus.”
The data can help identify sick people and prevent the spread of disease. It would have built-in privacy protection measures that will be included in the app. The origin of the app is based on previous research at USC’s Convergent Science Institute in Cancer (CSI-Cancer), which tracks health performance across populations. CSI-Cancer is partnering with San Francisco-based HealthMode to develop the app.
In a parallel project, experts at USC Viterbi are developing a smartphone app to alert people when they’ve been near an infected person.
Behind that project is Bhaskar Krishnamachari, a professor of electrical engineering and computer science and director of the Center for Cyber-Physical Systems and the Internet of Things.
“We have to find a way to identify specific groups of people that should be practicing social distancing or get tested because we don’t have resources to test everyone and it may not be economically feasible to keep everyone at home for a long time. We need more precise instruments to see who should stay home or get tests, and a privacy-sensitive smartphone app for contact is one such instrument,” he said.
He said the app would alert its owner so the person can act by seeing a doctor or staying indoors. Balancing the need to protect public health and the right to privacy is a challenge, which encryption and anonymization technologies can solve.
Better tracking and testing for COVID-19 could help allocate scarce resources, achieve more targeted treatment and gain better health protection.
Experts say that old-fashioned public health approaches, such as widespread testing and manually tracing the contacts of people with newly discovered infections, probably will remain the most effective way to control the pandemic. But with few signs that the United States is assembling the army of health workers needed to track coronavirus infections, technology may be called on to fill the gaps.
Already technological tools are helping authorities fine-tune their public directives, and data derived from individual smartphones may soon play an important role in mapping webs of potential new infections and alerting people at particularly high risk of developing covid-19 that they need to be tested immediately.
“Smartphone contact tracing is a way of using technology to automate and augment some of the techniques that public health agencies have used,” J. True Merrill, a GTRI senior research scientist said. “Technology can enable us to do this, but for people in the United States to adopt it, privacy will really have to be locked down. Everything we’re doing in this project aims at providing privacy first. Manual contact tracing is still critically important, but digital contact tracing and alerting can significantly assist these efforts.” Beyond protecting privacy, large-scale adoption of smartphone contact tracing will need a social component that appeals to supporting the common good.
“To be successful, we’ll need to turn participation in this into a socially good thing, perhaps like the Ice Bucket Challenge,” Merrill said. “We’ll need people to voluntarily opt-in, and to get that, users would need to have full knowledge and control over where their data is stored and with whom they choose to share it.”
How contact tracing works?
The contact tracing component of the system would work something like this.
Each user opting into the service would install an app that would generate personal keys – long strings of letters and numbers unique to that specific smartphone, which are in turn used to generate randomized temporary contact numbers. The phones of users opting in would then communicate those temporary numbers with each other when they were nearby, using low-energy Bluetooth, a short-distance protocol widely used on mobile devices. Signal strength could provide a measure of how close the phones are to assess the risk of virus transmission when those people crossed paths.
“The idea is to log close interactions,” said Michael Brown, a GTRI research scientist who is the Georgia Tech technical lead of the project. “We’ll want to eliminate as many false positives as possible. For example, it’s highly unlikely that person-to-person transmission would occur across a large room.” For each interaction, the system could also record the duration of proximity, another factor in assessing potential risk.
Each phone would periodically generate new anonymous unique keys, and use those to generate new temporary contact numbers each time it crossed paths with another phone running similar apps. It would record those keys in a database that would be kept on the phone for a short period of time determined by the incubation period of the virus.
If a CoEpi user developed symptoms, they would share their symptoms in their app. In future versions, the CoEpi developers envision that the sick user would be presented with a series of options such as anonymously notifying public health authorities. For now, the symptoms are sent to the CoEpi system, which would add the anonymous key and symptom report from the sick user’s phone.
Each user’s phone would periodically download the list of keys associated with known symptom reports and check the temporary numbers generated by those keys against those of the phones it had been near. A match between each phone’s database and the numbers generated from the server’s key list would generate a notification of the exposure, and the app would then help the user decide whether the match likely represented a real exposure, and if so, decide what to do: self-quarantine, be tested, and/or notify public health authorities.
“Everyone would be pinged when they get tied to a known case, but only over a time range that really could have created a risk of transmission,” Merrill said. “There would be no identification information exchanged between the phones or the phones and the server.”