University Counts on Data Modeling to Track, Contain COVID-19 Outbreaks

University of California San Diego launches an ambitious Return to Learn program that aims to provide self-testing kits to 65,000 students, faculty, and staff on campus on a recurring basis for COVID-19. It also plans to use data modeling, contact tracing, and wastewater testing to create a tailored map of any virus outbreaks so it can quickly stop the spread.

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Image credit: UC San Diego Newsroom

As COVID-19 infections continue to escalate, small and large institutions collectively continue to balance the short- and long-term ramifications of the pandemic, while juggling differing legal guidelines for closures and maintaining “as safe as possible” openings. This fall, universities, high schools, and elementary schools are determining whether students will have fully remote, partially remote, or fully in-person classes for this semester and beyond, depending on the availability of a future vaccine.

One university is setting up a comprehensive testing and tracing initiative with the goal of testing every student and faculty member on campus. The University of California, San Diego (UCSD) intends to have a combination of in-person and remote classes, spurring the creation of its Return to Learn Program to test all students, faculty, and staff on a recurring basis for COVID- 19 this fall.

UCSD’s Return to Learn Program taps into its on-campus network of scientists and doctoral professionals who plan to test and gather data that will help map virus outbreaks in the community and on campus. Natasha Martin, Associate Professor of Medicine and an infectious disease modeler, will spearhead the program in partnership with Cheryl Anderson, Professor and Interim Chair of the Department of Family Medicine and Public Health, and Robert Schooley, Professor in the Department of Medicine, and others. 

According to UCSD’s Chancellor Pradeep K. Khosla, “this effort will leverage the ingenuity and expertise of UCSD’s clinicians, molecular biologists, epidemiologists, bioinformaticians, and others to work toward a tailored map of where the virus is, and where it isn’t.”

Self-Administered VirusTest Kits

The program’s rollout will occur in several phases. The university designed the initiative to be quickly responsive in tracking virus outbreaks as well as scalable to regularly test everyone on campus. The initial phase began on May 11, with the distribution of self-administered, nasal COVID-19 swab tests to undergraduate and graduate students living on campus, along with concurrent testing for the virus in on-campus surface and residential wastewater.

During this initial phase, the university planned for up to 5,000 students to receive the nasal test. By the end of June, the pilot program had screened 1,578 students, and not one student tested positive. The program will scale testing to approximately 65,000 people, including students, faculty, and staff, on a monthly basis as soon as September. Feedback to researchers from the pilot indicated the need to transition to saliva testing if possible, due to students’ test preferences.

The self-test model works like this: after a student enrolls in the testing program, they collect the test and specimen collection container from one of numerous designated sites on campus. Each container contains a unique barcode which students scan using a downloaded barcode-reader app on their phones. This automated process links an individual number to the student’s test and simultaneously creates a time stamp for it.

gloved hand holding clear bag with biohazard symbol

Image credit: UC San Diego Newsroom

Once they swab the inside of their nose, they drop their swab into its container and leave it inside a collection box, where it will be picked up by program coordinators. All swab testing will take place at UC San Diego Health’s Center for Advanced Laboratory Medicine. Test results will be delivered directly to the individual’s mobile phone through the MyChart app, and under most circumstances the results will be available within 24 hours, according to Martin.  

Looking for Data Patterns

COVID-19 data collected during the initial phase, and beyond if successful, would help inform an epidemiological model for the campus, including facilities, housing configurations, transportation infrastructure, and how its community interacts within and around the campus’ infrastructure. University leaders could then use those patterns to strategize further about early detection of the virus and decrease the risk of virus transmission. The models will also inform critical decisions about class sizes along with housing and classroom configurations.

Natasha Martin, the Return to Learn Program’s leader, reiterates that the program’s purpose is not just about testing. She notes in a recent article that “the secondary component, which is really critical, is what we do once we identify an outbreak. That's where we're going to rely heavily on measures such as contact tracing, isolation and quarantine, and social distancing interventions.”

She adds that if the university sees a viral rebound, it needs to be able to act quickly, adapting social distancing and recommendations to appropriately respond to any growing threats. If a student tests positive for the virus, they will be alerted immediately. The program’s Case Finding and Contact Tracing will additionally notify anyone who has been in close proximity to the infected student within the last few days for exposure notification. San Diego County Public Health will also receive positive case notifications.

Aggregated Medical Records

The scale of the Return to Learn Program is made possible by UCSD’s existing health data structure.The campus’ student health services and UC San Diego Health are the first in the UC system to share an integrated system for aggregating electronic medical records, streamlining processes for ordering tests, participant notification, and patient care.

Medical records and specimens will be tied by barcode and an associated alphanumeric code to ensure confidentiality for test participants. The program’s researchers and data modeling teams will only receive aggregate data, with no personal identification details included.

For additional information about UCSD’s Return to Learn Program, check out this video.

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