Epidemiological Modeling (2020 and 2021)

As Cornell returned to residential instruction in fall 2020 and subsequent semesters, the university relied on numerous evidence-based sources, including epidemiological modeling by the Cornell COVID-19 modeling team, to protect the health of our campus community and the greater Ithaca area.

Fall 2021 Classroom COVID-19 Transmission: Follow-up Analysis

With a highly vaccinated campus population and indoor mask wearing and surveillance testing measures in place, Cornell returned to full-capacity in-person classroom seating in fall 2021. Applying data from that semester, Operations Research and Information Engineering Professor Peter Frazier and partners on the Cornell COVID-19 modeling team found that the risk of infection in classrooms was small. By avoiding all classes with COVID-positive classmates, their analysis estimates that a typical student would reduce their chance of testing positive for SARS-CoV-2 over that semester from 13.8% to 13.6%, a 0.2 percentage point decrease. This analysis complements and confirms the team’s earlier analysis done in August 2021, demonstrating that classrooms with mandatory masking are a low-risk environment, even with full-density seating.

Report: Fall 2021 Classroom COVID-19 Transmission: Follow-up Analysis (PDF) (June 2023)

Booster Effectiveness Against Omicron

In order to study the effectiveness of booster shots against Omicron infections, Frazier and partners (the Cornell COVID-19 modeling team) investigated a total of 18,102 Cornell students fully vaccinated with Pfizer, Moderna or Johnson & Johnson vaccines that were PCR tested at least once between Dec. 2, 2021 and Dec. 31, 2021. Their modeling estimates that receiving a booster shot reduces the odds of being infected by the Omicron variant by 54% (95% confidence interval [45%, 62%]). This complements other studies showing that boosters provide substantial additional protection against infection and severe disease caused by the Omicron variant, beyond the protection offered by a first course of vaccination. Moreover, this roughly 50% reduction in susceptibility to infection can reduce infection at the population level by much more than 50%.

Report: Booster Effectiveness Against Omicron (PDF) (February 1, 2022)

Analysis of Fall 2021 Classroom COVID-19 Transmission

In this analysis, Frazier and partners (the Cornell COVID-19 modeling team) used a theoretical model and data published in the scientific literature to estimate the probability faced by an individual of becoming infected with COVID-19 due to classroom interaction over the course of the fall 2021 semester. Their analyses of the risks to undergraduate students, faculty instructors and graduate student teaching assistants incorporated the effect of masking in class, physical distancing and ventilation. The nominal estimate of this probability for vaccinated faculty instructors is 0.017%, or about 1 in 6,000.

Report: Analysis of Fall 2021 Classroom COVID-19 Transmission (PDF) (October 2021)

Modeling for Cornell’s Fall 2021 Semester

Frazier and partners (the Cornell COVID-19 modeling team) performed modeling at the start of the fall semester to incorporate new information to study the impact of new interventions brought to bear against cases in the student population. Interventions included more frequent surveillance testing for students affiliated with Greek Life organizations; stronger measures that improved compliance with student surveillance testing; increased staffing allocated toward contacting positive individuals and performing contact tracing; and a more robust adaptive testing program. Case trajectories since these interventions were put into place tracked between the nominal and optimistic scenarios developed at the time.

Report: Modeling for Cornell’s Fall 2021 Semester (PDF) (updated September 19, 2021)

Mathematical Modeling for Cornell’s Spring 2021 Semester

Cornell’s pandemic modeling team updated a mathematical model of the spread of COVID-19, originally developed for the 2020 fall semester, to incorporate information on student and employee COVID-19 cases at Cornell during the fall semester; rising prevalence in the Southern Tier and the country as a whole; and the evolution of faster-spreading variants of SARS-CoV-2 from the United Kingdom, Brazil and South Africa. Based on this, the team then identified likely scenarios for what might unfold over the spring semester and studied proposed modifications to Cornell’s COVID-19 measures. This supported Cornell’s preparation for the spring, and showed that modifications to the surveillance testing program, new contact tracing and supplemental testing programs for employees, travel restrictions and other modifications positioned Cornell to address the possible challenges of the spring semester.

Report: Mathematical Modeling for Cornell’s Spring Semester (PDF) (published February 16, 2021)

Mathematical Modeling for Cornell’s Fall 2020 Semester

In an initial analysis (June 2020), Frazier and partners (the Cornell COVID-19 modeling team) found that residential instruction, when coupled with a robust virus screening program, would allow Cornell to provide more thorough safeguards for public health than a fully online semester. Student surveys revealed that many Cornell students would choose to return to Ithaca, even if classes were fully online, and they would live together and socially interact. Offering in-person instruction would allow Cornell to impose mandatory virus screening tests and behavioral requirements for students.

Report: COVID-19 Mathematical Modeling for Cornell’s Fall Semester (PDF) (published June 15, 2020)

Addendum: COVID-19 Mathematical Modeling for Cornell’s Fall 2020 Semester

The Cornell COVID-19 modeling team updated its analysis in July 2020 after examining feedback on its initial report and in light of the changing progression of the virus nationally. This analysis studied numerous alternative parameters, including ways of calculating the number of contacts per day among members of the campus community, the effects of greater numbers of contacts per day, the effects of community members failing to comply with testing and the effect of offering testing to students who are taking classes online only.

Report: Addendum: COVID-19 Mathematical Modeling for Cornell’s Fall Semester (PDF) (published July 17, 2020)

Gateway Testing and Quarantine Capacity

Another updated analysis carried out by the Cornell COVID-19 modeling team in August 2020 studied the effectiveness of gateway testing (“arrival testing”) for addressing the rising prevalence of COVID-19 in parts of the United States, a potential lack of test access for some Cornell students in their home location, and the requirement that individuals traveling to New York state from states where the COVID-19 prevalence is high must self-quarantine upon arrival.

Report: Gateway Testing and Quarantine Capacity (PDF) (published August 11, 2020)

Update for Assemblywoman Lifton

The following document was prepared by the Cornell COVID-19 modeling team to update New York State Assemblywoman Barbara Lifton on two points of importance: the rise in national COVID-19 cases during the month of July and the projected impact of the Cornell reopening decision on the greater Ithaca community. This follows a broader discussion between President Martha Pollack and Assemblywoman Lifton and reflects questions asked by others.

Report: Update for Assemblywoman Lifton (PDF) (published August 9, 2020)