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Two weeks ago, a meme circulated with two pictures, labeled “My Fall Plans” and “The Delta Variant.” Usually the former image was cheerful and the latter considerably more dark. I saw most of these posted by my professor friends, asking a very good question: How can professors be expected to write a syllabus in this context where plans could shift so drastically?

Like a virus, these memes proliferated, replicated, then waned. These little pieces of knowledge did some good as they prodded me to think about writing my own syllabus (no, it’s not ready yet). But, ­driven as they are by social media’s algorithmic focus, these memes subtly reinforced my own problems. I need to decenter my own perspective and deliberately listen to other voices.

The natural world has a voice that can be measured through testing and collected as data. My first impulse as a scientist is to test more and gather more data, which is necessary but not entirely sufficient. Tests may be knowledge, but deciding what to do with them is wisdom.

As I survey the data, I’m reminded of the book of James, which is so quotable and pithy that it sounds like social media. But where social media relentlessly centers my self and my problems, James decenters.

James is clearly relevant to our situation, repeatedly discussing conflicts, plans, and wisdom: “If any of you lacks wisdom, you should ask God, who gives generously to all without finding fault, and it will be given to you.”1 Asking requires patience to wait for an answer, and patience is also implied when James says, “be swift to hear, slow to speak, slow to wrath.”2

It’s difficult for me to make plans – or even complete this essay — because of the impatient pace of the torrent of new data. By the time this is published, more positive tests will emerge, and outbreaks will happen at other schools, shutting down in-person instruction or other aspects of campus life. Last Friday Liberty University had an outbreak,3 and on Tuesday, Duke suspended indoor dining and student activities 4 Each situation requires local information contextualized to a flood of information, with a myriad of voices to sift and consider.

On August 20, some disruptive data were swiftly spoken and heard on my social media feed. At Rice University in Texas, an outbreak of the Delta variant of SARS-CoV-2 was found before classes even started. Positive tests on campus returned abnormally high numbers, in-person meetings were canceled, and classes were brought online for two weeks.5

After 18 months of data-watching, I was dismayed by this news. Almost everyone at Rice was vaccinated, which should have blunted this outbreak. If Rice had to close in-person instruction, what other schools would follow? How should I plan?

For the next few days, I searched for other outbreaks and closures, but found none of similar magnitude. Most schools were yet to open, so there wasn’t much data to see. My only course of action was to wait, and to try not to worry.

Then, on August 22, plans changed back. Rice University announced, “Dozens of people whose initial tests showed them to be COVID-positive have been retested twice and all but one of those have turned out to be negative.”6 Students could move in to dorms, but classes could not shift so quickly, and it was decided that they would remain online until Labor Day.

Students who tested falsely positive were needlessly isolated and stigmatized. Social media algorithms didn’t give me their stories, so I had to search for them. One student reported the extra measures they took above and beyond the requirements: “I waited until 9 o’clock at night to walk over because, if I had COVID, I didn’t want to give it to anybody.”7

Though the student went above and beyond, those serving her did not. The student reported, “They said the food was going to be delivered to me. Food was not delivered to me. I had to ask my friends to bring me food. I was really worried because I felt like there wasn’t going to be anybody to help me out.” That last sentence reveals the emotional toll of being an infected student; for all my worries as a professor, I have a lot of people to help me out, but this student did not.

Why were so many tests wrong? The false-positive rate of a properly run COVID-19 test is very low, but when an error happens, it tends to be systematic, affecting many samples in one batch. This is what happened at Rice: “Over 90% of the positive infections came from a single test provider; … and over 90% of the reported infections were for people who were fully vaccinated.”

In my chemistry lab, if one pH meter out of three in the lab gives anomalous values, then that pH meter needs to be recalibrated. Likewise, if one COVID test provider out of three returns far more positives, I suspect the provider. This is what happened at Rice. One lab made a mistake that prevented students from learning (through their own mistakes in lab) for two weeks.

Anomalous patterns of positives aren’t evident until the data are looked at as a whole. By the time such data were available at Rice, the university was already committed to online instruction. The mistake was in an off-campus facility, but the burdens fell on the campus community. Professors had to scramble to plan online classes and cancelled labs, but we’ve been through this before and could recycle last fall’s plans.  The students with false positive tests bore heavier burdens.

To me, this says we need more tests, not fewer, because we need to test enough to see patterns of false positives. The other side of this is that our policies must account for having more tests, including the noise and uncertainty in the data once a positive test comes back. Individual scientific studies, like individual COVID test providers, can be wrong, but it takes a lot of studies with a lot of subjects to provide the needed context and wisdom.

This is true at the widest level of understanding this virus. Big studies that select subjects randomly are the hardest to run but give the most solid data, and the United Kingdom may be the best in the world at these. Large studies out of the UK have given clear conclusions both in testing drugs against COVID-19 (the RECOVERY randomized controlled trials8 , which established the efficacy of dexamethasone9) and in testing people for COVID-19 (real-life vaccine effectiveness and mass testing surveillance from the ONS, the Office for National Statistics).

ONS survey data is powerful because it is impartial, consistently and randomly testing across the country–at all times, in sickness and in health. With a stealthy virus like SARS-CoV-2, this approach avoids pitfalls that smaller studies can fall into.10 On August 19, the day before the initial reports from Rice, I found a detailed report using ONS data on UK Delta wave infections.11 The power of vaccination shown by these data is part of why I was so puzzled by the initial reports out of Rice – the vaccine was working in almost 400,000 individuals tested in the UK, so I was expecting it to work in a few thousand students tested in Texas.

This August PNS study shows that vaccines still work well, even against the Delta variant (see Figure 2 in the report). Three months after the second dose, the odds of testing positive remain improved by around 60% for those vaccinated with AstraZeneca, to 75% for Pfizer, with even better odds against severe disease.

The real-life correlate from the states is the Lollapalooza festival in Illinois, which was a series of packed outdoor concerts requiring vaccination or a negative test for entry.12 About one-tenth of attendees were unvaccinated, but after the festival, they accounted for one-third of the infections.13 This too shows that the vaccine improves your odds of testing negative by about 70%.

These large studies set the context within which smaller studies should be interpreted. Detailed debates, about transmission from the vaccinated or the value of natural immunity, require a lot of smaller studies to reach the level of certainty of the ONS data.14

And campus policies should flex as well. For example, many are still isolating the infected for 14 days, but since the vaccine shortens the time table for infection, the time table of isolation may be shortened in response.15 Policies on isolation of contacts can be rethought in the light of the effectiveness of vaccines in preventing the worst outcomes.

As faculty, we are involved in planning and the decision to teach in-person vs. online, advocating for ourselves to administration. Spelman College faculty gave us an example of this when they chose to cancel their in-person instruction in protest of policies such as inadequate testing.16 After the policies were changed, the faculty returned to the classroom. This situation is different from that of Rice, but the result was about the same for the students: a week or two of online instruction.

When I heard this story, I put myself in the place of the professors by default. Then, by chance, I encountered a Spelman senior, and her story had elements I didn’t expect. She told me that as a junior, last fall, she had to arrange off-campus housing because a surplus of first-year students filled the on-campus dorms. In fact, she was living in a hotel when we spoke last week. As a professor, I covet high enrollments, but they come with their own problems, especially for the enrolled students.

This student decentered my perspective. She wasn’t angry or worried about missing classroom instruction – she was tired and focused on the next steps. Balancing her concerns with faculty concerns, while balancing the budget, requires both wisdom and the humility.

As a scientist, I’m used to listening to the natural world, to hear God speak through data, despite the messy noise of real-world complexity. As a professor, I listen to my colleagues when we make plans together (or post memes). Through an internet search and a chance encounter, I heard how hard this time was for Rice and Spelman students as well. The students’ stories surprised me, which is a sign that I’ve been centering my own story and perspective too much.

As we transition from pandemic to endemic situations, our policies must transition as well. As James says, “you ought to say, ‘If it is the Lord’s will, we will live and do this or that.’”17 This wouldn’t make a catchy meme, but if I imagine a picture on the left labeled not “My” but “Our Fall Plans,” and one on the right labeled “The Lord’s Will,” then my anxiety drops a notch and I find myself able to listen to those who aren’t professors, trying to receive wisdom from above and beyond the impatient rush of ephemeral information.


  1. James 1:5 (NIV)
  2. James 1:19b (KJV)
  5. Stephanie Saul and Sophie Kasakove, “Rice University Turns to Online Classes.” The New York Times, August 20, 2021.
  9. The RECOVERY Collaborative Group. “Dexamethasone in hospitalized patients with Covid-19—preliminary report.” The New England Journal of Medicine (2021).384:693-704 DOI: 10.1056/NEJMoa2021436
  10. Some specific advantages are listed at
  11. Pouwels, Koen B., et al. “Impact of Delta on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK.” medRxiv (2021).
  14. If you’re curious, it looks like the vaccinated can transmit but at lower rate even if symptomatic, and there’s already a two-thirds or more reduction in them even becoming symptomatic; and natural immunity can be as protective as immunization (and may be more lasting), but both together add up to the best protection possible. I’m not as certain on these as I am of the ONS data, so I put them in a footnote. See for data on natural immunity that predates the recent Science article found here:

  15. One recent study shows that symptomatic breakthrough infections have similar viral loads but clear a few days faster, so that a week of isolation may be sufficient. See Figure 3E in the preprint Kissler, Stephen M. et al. “Viral dynamics of SARS-CoV-2 variants in vaccinated and unvaccinated individuals.” doi:
  17. James 4:15 (NIV)

Benjamin J. McFarland

Benjamin J. McFarland, Professor of Chemistry and Biochemistry, Seattle Pacific University.