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.
Network assessment and modeling the management of an epidemic on a college campus with testing, contact tracing, and masking