A New Model for Contact Tracing Can Result in Fewer Infections

Contact tracing can be a powerful tool for public health officials seeking to stop disease spread. But it’s generally seen as the standard protocol—someone displays symptoms and gets diagnosed. After interviewing individuals about their recent interactions, you reach out to those contacts to quarantine and monitor for symptoms.

But what happens when presymptomatic or asymptomatic transmission is the norm? A global pandemic with over 45 million cases and counting.

Why? Because in the early days of the pandemic, it became clear that the standard protocol for contact tracing was less effective in halting COVID-19. Several factors contributed to the problem: Imperfect and inconsistent testing. Low participation rates. And, most notably, frequent pre-/asymptomatic transmission of the virus.

Halting the spread of extremely infectious diseases among highly mobile populations requires finding new techniques, tools, and protocols to help reduce transmission. A small team of MITRE researchers took on that challenge with an eye toward improving the effectiveness of contact tracing.

The team’s solution was to build a more proactive contact tracing strategy—one that addresses gaps in traditional contact tracing protocols. It aims to better allocate the limited testing and contact tracing resources available in small communities.

How Target Tracking Translates into Contact Tracing

The initial idea was the brainchild of MITRE’s Joshua Stadlan, an early-career engineer who usually worked in defense-related projects. To move faster, Stadlan formed a team with colleagues Ryan Frazho and Christian Minor. They later consulted with several subject matter experts, including an epidemiologist, as they experimented with different strategies and evaluated them with a computer model.

So how does an engineer working on military radar tracking algorithms develop a contact tracing strategy?

Tracking algorithms and disease control strategies require answering similar questions. For example, how do you balance focusing on a currently known subject of interest—whether a threatening object or a local virus outbreak—while also monitoring for new threat sources, such as another object or interstate infection spread?

In the context of sensor tracking, how does someone determine if they’re seeing the actual subject of interest and not a false alarm, such as another object or a different disease?

“In speaking to MITRE colleagues in healthcare, I noticed that some of the challenges we’re facing in disease control—especially when signs of contagiousness are not obvious—share similarities to the sensor tracking problems addressed in aerospace engineering over the last half-century,” Stadlan explains.

“With expertise across scientific fields and a cross-government perspective of public challenges, MITRE pollinates this kind of interdisciplinary thinking every day.”

The team developed a novel framework and algorithm for minimizing the number of infections in an epidemic, given fixed resource limits for interviews, tests, and quarantines. Then they created a computer simulation of individuals interacting with one another based on real-life social networks. This illustrated their strategy and enabled them to compare its effect to that of standard contact-tracing protocols.

So far, they’re finding that tracing primary, secondary, and even tertiary contacts of symptomatic individuals—as many as your daily interviewing capacity allows—enables more strategic quarantine recommendations for a fixed limit of quarantines. These quarantine recommendations will result in fewer infections on average over a 10-week period from the first infection, compared to standard contact tracing protocols under the same quarantine limit.

In other words, for contact tracing it pays to “go all-in early.”

Adding to the Public Health Toolkit

MITRE epidemiologist Beth Linas, who collaborated with the team, appreciates that this project offers an added capability for public health officials.

“This project is particularly innovative because it can help find pre- and asymptomatic COVID-19 cases by more closely examining additional social factors. These can include what type of contact someone had, the likelihood the individual would actually isolate or quarantine, their ability to recall all contacts, and the probability of false negative/true negative tests.”

She adds, “Contact tracing on its own, when used properly, can be effective, but this project enhances it by including more data points.”

In addition, the team has had the opportunity to advise the COVID-19 Healthcare Coalition Modeling & Simulation Working Group’s university campus simulation collaboration, The Artificial University (TAU): Campus Pandemic Management.

Andreas Tolk, who leads MITRE’s work on TAU, says, “We’ve seen that social groups and interactions, network structures, and local distribution are often more important for the spread of the disease than infection parameters. Knowing this, we integrated some of these proactive contact tracing strategies in the open source simulations we released.”

Incubating Ideas, MITRE-style

At MITRE, our priority is to make our nation stronger and our citizens safer. We’ve found that our people often have great ideas on how to approach a tough problem from different angles. COVID-19 was no exception.

Stadlan’s idea is a great example. “When the first stay-at-home orders came out in March, I started thinking we were in this for the long haul, and that COVID-19 was going to be one of the biggest threats our nation has ever faced,” he says. It led to several informal brainstorming sessions on a MITRE Slack channel on how cross-domain engineering expertise could be used to address the COVID-19-specific challenges.

Shortly thereafter, MITRE launched a corporate-wide COVID-19 idea challenge. Our staff quickly responded and submitted 241 proposals. Over 20 received immediate funding from MITRE’s independent research and development program, including the one Stadlan initiated.

“I feel privileged to work at MITRE,” he says. “I love that we were encouraged to collaborate across teams and disciplines to find practical solutions that could help right away.”

—by Kay M. Upham