From the Miami Herald:
Miami-Dade has tens of thousands of missed coronavirus infections, UM survey finds
BY BEN CONARCK AND DANIEL CHANGAPRIL 24, 2020
About 6 percent of Miami-Dade’s population — about 165,000 residents — have antibodies indicating a past infection by the novel coronavirus, dwarfing the state health department’s tally of about 10,600 cases, according to preliminary study results announced by University of Miami researchers Friday.
Miami-Dade county is up to 287 deaths in total today, giving a crude Infection Fatality Rate of 0.17% so far, much lower than the 0.9% seen in New York City in yesterday’s new serological results, but more in line with California results.
One way to explain the bafflingly heterogeneous results we are constantly being confronted with is to posit Viral BioDiversity: there could be different strains in different places. For example, VBD could potentially account for why there are so many more deaths per person with antibodies in New York City than in Miami: it could be that there’s a New York City variant that is more lethal than the variant prevalent in Miami.
One problem with this explanation is that it’s unfalsifiable. You can use it to explain away any anomaly, which might lead you to overlook something that you could do something about. For example, maybe New York City is doing something wrong that Miami is doing right, which would be useful to figure out.
The study, spurred by Miami-Dade County officials, will be an ongoing weekly survey based on antibody testing — randomly selecting county residents to volunteer pinpricks of their blood to be screened for signs of a past COVID-19 infection, whether they had tested positive for the virus in the past or not. …
Friday’s results, based on two weeks of countywide antibody testing and about 1,400 participants, found that about half of the people who tested positive for antibodies reported no symptoms in the 14-17 days before being tested. …
Gimenez said the UM survey of Miami-Dade reflects a national trend showing African Americans are disproportionately impacted by the novel coronavirus. “African Americans are more than twice as likely to be infected with COVID-19 than other racial groups,” he said.
The survey findings also indicate that Miami-Dade is far from the 60% or higher infection rate needed to reach herd immunity, when enough people are infected to stop the spread of the virus by slowing transmission. …
UM researchers used statistical methods to account for the limitations of the antibody test, which is known to generate some false positive results. The researchers say they are 95% certain that the true amount of infection lies between 4.4% and 7.9% of the population, with 6% representing the best estimate.
The results are similar but not identical to other serological surveys in California, but indicate far less infections than a recent survey in New York, which found a nearly 14% infection rate statewide and upwards of 20% in New York City. …
UM researchers say their findings are more robust than most because they used Florida Power & Light to generate phone numbers in targeted demographic areas, leading to a more randomized selection of participants.
On the other hand, scientists are only now starting to get a good handle on how many false positives and false negatives are generated by antibody tests. From the NYT today:
Coronavirus Antibody Tests: Can You Trust the Results?
A team of scientists worked around the clock to evaluate 14 antibody tests. A few worked as advertised. Most did not.
By Apoorva Mandavilli
April 24, 2020… For the past few weeks, more than 50 scientists have been working diligently to do something that the Food and Drug Administration mostly has not: Verifying that 14 coronavirus antibody tests now on the market actually deliver accurate results.
Here’s the organization’s website and draft preprint.
These tests are crucial to reopening the economy, but public health experts have raised urgent concerns about their quality. The new research, completed just days ago and posted online Friday, confirmed some of those fears: Of the 14 tests, only three delivered consistently reliable results. Even the best had some flaws. …
In the new research, researchers found that only one of the tests never delivered a so-called false positive — that is, it never mistakenly signaled antibodies in people who did not have them.
Two other tests did not deliver false-positive results 99 percent of the time.
But the converse was not true. Even these three tests detected antibodies in infected people only 90 percent of the time, at best.
The false-positive metric is particularly important. The result may lead people to believe themselves immune to the virus when they are not, and to put themselves in danger by abandoning social distancing and other protective measures.
False positives are important when infection rates are in the single digits. Last week’s Stanford test found about 50 positives among 3300 tested individuals, or a raw percentage of 1.5%. On the other hand, the New York City 21% finding is less likely to be highly inflated by false positives.
… Other scientists were less sanguine than Dr. Marson. Four of the tests produced false-positive rates ranging from 11 percent to 16 percent; many of the rest hovered around 5 percent.
“Those numbers are just unacceptable,” said Scott Hensley, a microbiologist at the University of Pennsylvania. “The tone of the paper is, ‘Look how good the tests are.’ But I look at these data, and I don’t really see that.”
The proportion of people in the United States who have been exposed to the coronavirus is likely to be 5 percent or less, Dr. Hensley said. “If your kit has a 3 percent false-positive, how do you interpret that? It’s basically impossible,” he said. “If your kit has 14 percent false positive, it’s useless.” …
New tests also usually compete with an established gold standard. Lacking such a standard, the team instead compared all the tests in a “head-to-head bake-off to see who’s the winner,” Dr. Hsu said.
Each test was evaluated with the same set of blood samples: from 80 people known to be infected with the coronavirus, at different points after infection; 108 samples donated before the pandemic; and 52 samples from people who were positive for other viral infections but had tested negative for SARS-CoV-2.
Tests made by Sure Biotech and Wondfo Biotech, along with an in-house Elisa test, produced the fewest false positives.
A test made by Bioperfectus detected antibodies in 100 percent of the infected samples, but only after three weeks of infection. None of the tests did better than 80 percent until that time period, which was longer than expected, Dr. Hsu said.
The lesson is that the tests are less likely to produce false negatives the longer ago the initial infection occurred, he said.
The tests were particularly variable when looking for a transient antibody that comes up soon after infection, called IgM, and more consistent in identifying a subsequent antibody, called IgG, that may signal longer-term immunity.
“You can see that antibody levels rise at different points for every patient,” Dr. Hsu said. The tests performed best when the researchers assessed both types of antibodies together. None of the tests could say whether the presence of these antibodies means a person is protected from reinfection, however.
The results overall are promising, Dr. Marson added. “There are multiple tests that have specificities greater than 95 percent.” …
Dr. Krammer said false positives are less of an issue for assessing how widely the virus has spread in the population. If a test has a known false-positive rate, scientists can factor that into their calculations, he said.
Assuming you know the false positive and false negative rates.
But false positives become dangerous when making policy and personal decisions about who can go back to work. “You don’t want anybody back to work who has a false positive — that’s the last thing you want to do,” Dr. Krammer said.
Unfortunately, this article doesn’t mention which tests were used in the various results we are now getting in from around the world.
