Network assessment and modeling the management of an epidemic on a college campus with testing, contact tracing, and masking
Authors: Hartvigsen Gregg 
Published: April 2021

There remains a great challenge to minimize the spread of epidemics. This may be particularly true on densely populated, residential college campuses. To construct class and residential networks I used data from a four-year, residential liberal arts college with 5539 students. Equal-sized random networks also were created for each day. Different levels of compliance with mask use (none to 100%), mask efficacy (50% to 100%), and testing frequency (daily, or every 2, 3, 7, 14, 28, or 105 days) were assessed. Tests were assumed to be only 90% accurate and positive results were used to isolate individuals. I also tested the effectiveness of contact tracing and subsequent quarantining of neighbors of infectious individuals.

I used class enrollment and residence data from a college with 5539 students to analyze network structure and test the epidemic potential of the infectious disease agent SARS-CoV-2. Average path lengths were longer in the college networks compared to random networks. Students in larger majors generally had shorter average path lengths. Average transitivity (clustering) was lower on days when students most frequently were in class (MWF). Degree distributions were generally large and right skewed, ranging from 0 to 719.

Simulations began by inoculating twenty students (10 exposed and 10 infectious) with SARS-CoV-2 on the first day of the fall semester and ended once the disease was cleared. Transmission probability was calculated based on an R0 = 2.4. Without interventions epidemics resulted in most students becoming infected and lasted into the second semester. On average students in the college networks experienced fewer infections, shorter duration, and lower epidemic peaks that occurred compared to dynamics on equal-sized random networks. The most important factors in reducing case numbers were the proportion masking and the frequency of testing, followed by contact tracing and mask efficacy. The paper discusses further high-order interactions and other implications of non-pharmaceutical interventions for disease transmission on a residential college campus.

[Model and network data files are available at https://github.com/GreggHartvigsen/Network-epidemic-model-college-campus]

Author summary

I built and analyzed daily networks for a college with 5539 students based on class enrollment and residence data over two academic semesters (fall 2019 - spring 2020). I then introduced an infectious disease agent similar to SARS-CoV-2 and tested a variety of non-pharmaceutical interventions to minimize the spread. The structure of these networks actually resulted in fewer students becoming infected when compared to random networks. Most important, however, was the level of masking and testing that was used to mitigate the spread. I found that with moderate levels of testing and contact tracing and/or masking the number of COVID-19 cases was well contained. Without any of these non-pharmaceutical interventions most students contracted COVID-19. Additionally, larger majors were at a slightly elevated level of risk of infection and students in classes over 40 students also were at a great risk of infection. The results suggest that college campuses should be able to contain infectious diseases, such as COVID-19, through the effective use of moderate levels of masking and testing, with resulting isolation of infectious individuals.