Email may have tainted Stanford coronavirus antibody study

Wife's email may have tainted Stanford coronavirus antibody study

By Eric Ting, SFGATE and Matthew Tom

Published 8:14 pm PDT, Friday, April 24, 2020

• An employee holds up an antibody test cartridge of the ichroma COVID-19 Ab testing kit used in diagnosing the coronavirus for a photograph on a production line of the Boditech Med Inc. in Chuncheon, South Korea, Friday, April 17, 2020. Boditech Med recently started exporting its antibody-based virus test kits to various countries.

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  An employee holds up an antibody test cartridge of the ichroma COVID-19 Ab testing kit used in diagnosing the coronavirus for a photograph on a production line of the Boditech Med Inc. in Chuncheon, South

  ... more

  Photo: Lee Jin-man, AP

An employee holds up an antibody test cartridge of the ichroma COVID-19 Ab testing kit used in diagnosing the coronavirus for a photograph on a production line of the Boditech Med Inc. in Chuncheon, South Korea, Friday, April 17, 2020. Boditech Med recently started exporting its antibody-based virus test kits to various countries.

less

An employee holds up an antibody test cartridge of the ichroma COVID-19 Ab testing kit used in diagnosing the coronavirus for a photograph on a production line of the Boditech Med Inc. in Chuncheon, South

... more

Photo: Lee Jin-man, AP

Wife's email may have tainted Stanford coronavirus antibody study

The wife of a Stanford professor solicited parents via email in Los Altos to join her husband's coronavirus antibody study, falsely claiming that the tests were "FDA approved" and would tell participants whether they were immune, potentially comprising the study's findings, according to BuzzFeed News.

The email was sent April 2 to parents with children attending Ardis G. Egan Junior High School with the subject line, "COVID-19 antibody testing - FREE." It went on to say, gain “peace of mind” and “know if you are immune." The email was sent by Catherine Su, a radiation oncologist married to Jay Bhattacharya, who was co-leading the Stanford study with Dr. Eran Bendavid. The email obtained by BuzzFeed News went on to say: "If you have antibodies against the virus, you are FREE from the danger of a) getting sick or b) spreading the virus. In China and U.K. they are asking for proof of immunity before returning to work. If you know any small business owners or employees that have been laid off, let them know -- they no longer need to quarantine and can return to work without fear.”

“The email you reference was sent out without my permission or my knowledge or the permission of the research team,” Bhattacharya wrote in an email responding to BuzzFeed News.

In early April, Stanford researchers conducted an antibody test of 3,300 residents, with participants selected based on their age, race, gender and ZIP code to put together a sample that was representative of the county's population.

The results of the study were released April 17, and a number of outside researchers have had time to review the preliminary study and its methodology. While all agree with the general takeaway that coronavirus infections are vastly underreported, most believe that the underreporting is not off by a factor as high as 50 to 85, which is what the study found. Researchers also found a raw, unadjusted antibody prevalence of 1.5 percent, which was scaled up to 2.5-4.2 percent when adjusting for population and test performance characteristics.

News of the email would further put into question the study's findings. While Bhattacharya acknowledged that the makeup of the study's participants was thrown off by the email, he said the research team corrected the issue.

“Our tracking of signups very strongly suggests that this email attracted many people from the wealthier and healthier parts of Santa Clara County to seek to volunteer for the study,” he told BuzzFeed News. “We took immediate steps to slow the recruitment from these areas and open up recruitment from all around Santa Clara County.”

Soon after the study was released, a number of experts and researchers questioned the study's methodology.

Dr. George Rutherford, an epidemiologist at UCSF, highlighted the fact that the antibody test the researchers used was not FDA-approved, as very few antibody tests have received approval to this point. The Stanford researchers acknowledged as much in the study and used test performance weights to scale results, but Rutherford was skeptical of these weights, as well as the population weights the researchers used. Instead, Rutherford believes we should just look at the raw antibody prevalence percentage of 1.5 percent.

"At end of day, the percent positive for antibodies was 1.5 percent," he said. "I don’t know what to make of the original sample, I don't know what to make of their adjustments for laboratory tests or the general population weight. I walk away thinking they found 1.5 percent of people have antibodies. They're smart as whips but felt crushed to get this out quickly, which is understandable."

Rutherford added that a 1.5 percent antibody prevalence is in line with what he would have expected.

"In the medical community, the thought is that 1 percent of people have been exposed in the Bay Area, and it's a little higher in Santa Clara County," he said.

Rutherford was not alone in questioning the validity of the weights the researchers used. Dr. Natalie E. Dean, a professor of biostatistics at the University of Florida, tweeted that she had concerns with the adjustments made for clustering (some participants brought children and other household members with them to the test) and test characteristics (researchers assume no false positives but some false negatives).

"Having had experience with these types of weighted surveys, I am always a little skeptical when the weighted result is very different from the unweighted result," she wrote in a Twitter thread. "Here, nearly double. This can be due to a few highly influential observations. Weights can be wonky."

When using the unweighted antibody prevalence of 1.5 percent, that translates to a total of 28,920 residents in the county that have been infected. Since the county had reported just under 1,000 cases at the time the study was conducted, the unweighted antibody number suggests infections are underreported by a factor of 30, and not the factor of 50 to 85 the weighted figures suggest.

Underreporting by a factor of 30 is still significant, as it once again substantially lowers the mortality rate. When using the researchers' estimates for deaths through April 22 (100) and the unweighted antibody figures, the true mortality rate in Santa Clara County becomes 0.35% — a figure almost identical to the "true" mortality rate calculated following antibody tests in a hard-hit German town. A 0.35% mortality rate is still nothing to sniff at, however, as it is three to four times deadlier than the seasonal flu (with a mortality rate of 0.1%) and can be significantly higher for elderly residents and individuals with underlying conditions.

However, many question if the 1.5 percent prevalence of antibodies was the result of a sampling bias that led to a disproportionate number of individuals with COVID-19 symptoms participating in the study.

In a peer review of the antibody study published to Medium, former Stanford lecturer Balaji Srinivasan, who specializes in statistics and computational biology, argued the selection methods could have overstated the prevalence of the disease in the county.

"What if their group of participants was enriched for positives relative to the general population?" He writes. "What if their participants had a much higher rate of COVID-19 than normal? As a reductio ad absurdum, if you went to a hospital and tested all recovering patients for COVID-19 antibodies, you’d probably get a very high percentage of positives. You wouldn’t be able to generalize from that to say that much of the general population had already gotten the illness."

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Matthew Tom is a Homepage Editor at SFGATE. Email: mtom@sfgate.com.

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