When you're doing everything right—keeping six feet of social distance, wearing a mask, washing your hands—how risky is attending class in person? Duke researchers have created tools to help you find out.
Professor of Environmental Chemistry Prasad Kasibhatla developed an online risk calculator for COVID-19 transmission through aerosols in the classroom. But Duke’s emergency coordinator disagrees with professors on the risk calculator’s inputs, such as the fraction of infected individuals in the community and how efficient students’ masks really are.
"It probably captures at least 50%, if not more, of the risk," Kasibhatla said of the calculator. "Especially in the kind of classroom settings we're talking about, which are very controlled classroom settings, with social distancing and masks and hygiene.”
Risk in Duke Classes
According to the Duke COVID-19 testing tracker, 0% of faculty and staff tests and 0.09% of student tests were positive for the coronavirus from Aug. 29 to Sept. 4. But William Pan, an associate professor of global environmental health who worked on the model, said infected rates could be higher.
Pan lives in Orange County, where the NCDHHS reported a positivity rate of 6.3% as of Wednesday, and 10.1% the previous week. Some faculty commute, and he said it's difficult to know the extent to which students interact with the Durham community.
Pan recommended using an upper estimate of 4.06% infected for students and 4.41% for faculty in the model, combining Durham’s average positivity rate according to the North Carolina Department of Health and Human Services dashboard since Aug. 31 with the rates in Orange and Wake counties. This assumes most students live in Durham, but that faculty may be split evenly between the three counties.
"It's a ballpark estimate," Kasibhatla said of the model's predictions.
The Chronicle used Duke’s published rates as lower bounds and Pan’s recommendations as upper bounds in Kasibhatla's model.
However, given Duke's testing procedures and regulation of students on campus, Vice President of Administration Kyle Cavanaugh, Duke's emergency coordinator, disputed these numbers.
“With every undergrad being tested multiple times, we have a highly detailed view of infection prevalence and there is no evidence for numbers that match the local community predictions,” Cavanaugh wrote in an email.
Pan said that since Duke’s pool testing is not random but targets outbreaks and at-risk students, it provides an uncertain gauge of the number of infected individuals in the community, and it’s best not to underestimate.
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Economics 101 brings together 80 students three times a week. With rough estimates for the size of Griffith Film Theater and percent of faculty and student-aged people in the community who are infectious, the risk of infection probability for a student taking the course is 0.6% over the course of the semester, according to Kasibhatla's model.
For a 12-student section of Writing 101 held in Classroom Building room 114, their model's best estimate for student infection probability lands higher, at 2.3% over the semester.
To obtain these numbers, The Chronicle used square footage measurements from the Duke University Space Management Dashboard and room height estimates based on measurements of Grainger Hall provided by Hien Nguyen, administrative assistant at Duke Facilities Management, in the model.
Cavanaugh said Duke’s data doesn’t show that students are catching coronavirus in the classroom, and that required masking should take the edge off any risk.
“We have been in close contact with peer universities and have been monitoring our own data from contact tracing and there is currently no data to support transmission in the University classroom setting,” Cavanaugh wrote. “The bulk of transmission appears to take place in social gatherings where masks are not worn.”
The Aerosol Debate
The atmospheric science and medical communities disagree over aerosol versus contact transmission and the relative dangers they pose, Kasibhatla said. But he believes aerosols, or tiny airborne droplets, can carry COVID-19 much further than six feet.
Kasibhatla said there is increasing evidence of the importance of airborne transmission, something the Centers for Disease Control and Prevention and the World Health Organization seem to have missed “because of their misunderstanding of the physics of aerosols.”
In their FAQ on COVID-19 transmission, the WHO states that aerosol transmission becomes a definite risk only during certain medical procedures but aerosol transmission in crowded, poorly-ventilated indoor spaces like restaurants or nightclubs “cannot be ruled out.” They recommend that more studies are needed to understand these spreading events, but do not list aerosols under common methods of transmission, or even “other” methods of transmission.
Although Kasibhatla had formerly expressed concerns that Duke has not publicly released a quantitative analysis of the risks students, faculty and staff regularly take on its campus—like Cornell did—he said that after a meeting with the official Duke modeling team Sept. 4, he does feel the administration is aware of and committed to assessing aerosol risk.
When Kasibhatla and Pan set out to look at where coronavirus aerosols go, they worked with John Fay, instructor in the Nicholas School of the Environment; Elizabeth Albright, assistant professor in environmental science and policy; and Jose-Luis Jimenez, a chemistry professor at the University of Colorado Boulder.
Other Duke experts are tackling the same inhalation issue. Lucas Rocha-Melogno, a fourth-year civil and environmental engineering doctoral student, worked with Marc Deshusses, professor of civil and environmental engineering, and Gregory Gray, infectious disease epidemiologist and professor of medicine, to create another model for infection via aerosols.
Their team sampled the air in patients’ rooms at Duke Hospital to better understand aerosol transmission, and they plan to publish their results this month and an interactive web app within weeks.
Rocha-Melogno said ventilation, or air changes per hour, is the most important factor in reducing risk for aerosol transmission beyond six feet—followed closely by the length of exposure time.
Opening windows can improve natural ventilation to reduce risk, as can high-efficiency particulate filters.
"As long as you pass them through these filters that have an efficiency rating of MERV-13 or higher, you're in pretty good shape," Kasibhatla said. The MERV scale, or minimum efficiency reporting value, describes how effectively filters remove particles of varied sizes.
What to Assume
Rocha-Melogno's model takes a different tack than Kasibhatla’s, assuming one infected person is present in the space and looking at one-time events instead of repeated ones.
“If you leave the model at the assumption of having only one person that is contagious, you provide a scenario that the user can evaluate easily and say, interesting, my risk goes up x times just by staying an extra hour in the room with someone that has COVID-19,” Rocha-Melogno said.
Rocha-Melogno said it is important to have an accurate count of infected individuals in the community before relying on this to calculate risk.
“For example, in my country, Bolivia, there is far less testing going on compared to the U.S., and the proportion of infected individuals may be far greater than the one reported. Thus, if you include these parameters, you may underestimate the risk of infection,” he said.
Both models assume strict adherence to social distancing. Plug in ten people and a 230-square-foot dorm room to these tools, and you'll fail to estimate the true value of risk.
“If you are in a crowded place where physical distancing is not in compliance, then the risk of infection will be higher as people will be closer to each other’s ‘aerosol plumes.’ Think of when someone smokes a cigarette and exhales—the cloud starts small and disperses over distance. This is what happens when all of us exhale,” Rocha-Melogno said.
He wants people to understand their risk of infection is not a single value—it’s highly variable.
Rocha-Melogno’s preliminary model, which is still in development, estimates the median probability of contracting COVID-19 via aerosol after attending one session of Writing 101 in Classroom Building 114 with an infected person in the room to be 1%.
In addition to the presence of one infected individual, this assumes that the air in the classroom changes one to four times an hour, and that the students are standing and speaking. However, since the model parameters have a range of possible values, the risk could run as high as 2.7% and as low as 0.3%.
Learning in Person
All but one of Joe Laforet Jr.'s classes are in person. He's a first-year in Engineering 101 and Genetics and Genomics Focus classes, and he attends only multivariable calculus online. He said he feels safe in class and thinks students suffer academically in online settings.
"I go to class and I sit in the uncomfortable chair and I know I need to focus, I’m in a learning environment now,” Laforet said. He said he wonders why more classes aren't in person, given Duke's precautions.
"If we’re doing all of this stuff, why are we doing online classes at all?” he said.
For one of the largest in-person lectures on campus, Economics 101, attendance is optional. Connel Fullenkamp, professor of the practice of economics, who teaches the class, said about 40 of the 278 enrolled students are online-only, so students can attend one of three lectures a week in-person.
"There is a bit of a musical chairs angle to this, since I will have to ask late-arriving students not to attend, once [Griffith Film Theater] reaches capacity. But that hasn't happened yet. And I promised to compensate students who are affected by this, partly with exempting them from a class assignment, and by buying them a coffee drink (or equivalent)," Fullenkamp wrote in an email.
First-year Grace Wei said attendees follow social distancing guidelines.
“They have the max capacity of 80 people set for right now, but there’s definitely enough space for everyone to social distance,” Wei said.