Smartphone Application for Coronavirus Contact Tracing

Researchers at the University of California, Irvine have developed a free, open-source smartphone application that permits contact tracing for potential coronavirus infections while preserving privacy. The team's project is detailed in a paper published recently in JMIR mHealth and uHealth.

"Contact tracing is the process of tracking down and isolating people who may have been exposed to an infectious disease after someone has tested positive," said lead author Tyler Yasaka, a software engineer and junior specialist in otolaryngology at the UCI School of Medicine. "This process has traditionally been slow and inefficient, and current technology-based solutions have privacy concerns because they require continuous tracking of everyone's location."

TrackCOVID works in a different way, he said, by creating an anonymous graph of interactions. Every time a person gathers with others or goes to a public place, he or she can use the app to log contacts by either hosting or joining a checkpoint, which allows possible paths of virus transmission to be discovered. The first person to register as a checkpoint host is given a Quick Response code; others subsequently join the checkpoint by scanning this QR code.

As people congregate with others over time, their interactions are linked to each other anonymously. Anyone who tests positive for COVID-19 can report it through the app without revealing his or her identity. Using the graph of interactions, the app will notify users who may be at elevated risk of exposure.

"We built a simplified simulation model that showed the app is more effective - that it flattens the curve of infections - when more people use it," said co-author Dr. Ronald Sahyouni, a biomedical engineer in UCI's joint M.D./Ph.D. Medical Scientist Training Program and an incoming neurosurgery resident at UC San Diego.

How could this be encouraged? Co-author Brandon Lehrich, who earned a B.S. in biomedical engineering at UCI in 2018, suggested that endorsement by local, state and national government entities would be beneficial - as would enlisting the help of grocery stores and other "essential" gathering places.

The establishments could post signs displaying their QR code, which visitors could scan with their smartphones. TrackCOVID would open automatically in their device browsers, and they'd be anonymously checked into that specific location.

"If the customer happens to be at an elevated risk level, they'll see an alert on their screen," Lehrich said. "If enough public places are doing this, then a lot of contact tracing will happen without any users making a conscious effort other than scanning a QR code when they go shopping. From there, I think people will start to see the value of the app and begin using it to create checkpoints for their private interactions as well."

Yasaka added, "We hope our app goes viral before too many more people come in contact with the more dangerous virus."

Yasaka TM, Lehrich BM, Sahyouni R.
Peer-to-Peer Contact Tracing: Development of a Privacy-Preserving Smartphone App.
JMIR Mhealth Uhealth 2020. doi: 10.2196/18936

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

Improved Cough-Detection Tech can Help w…

Researchers have improved the ability of wearable health devices to accurately detect when a patient is coughing, making it easier to monitor chronic health conditions and predict health risks such...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...