Two new studies using antibody tests to assess how many people have been infected with the coronavirus have turned up numbers higher than some experts had expected.
Both studies were performed in California: one among residents of Santa Clara County, south of San Francisco, and the other among residents of Los Angeles County. In both cases, the estimates of the number of people infected in those counties were far higher than the number of confirmed cases.
The studies, conducted by public health officials and scientists at Stanford University and the University of Southern California, have earned the ire of critics who questioned both the recruitment methods and the analyses.
In the Santa Clara County study, researchers tested 3,330 volunteers for antibodies indicating exposure to the virus. Roughly 1.5 percent were positive.
That means that 48,000 to 81,000 people were infected with the coronavirus in Santa Clara County by early April, the investigators concluded.
In Los Angeles County, researchers conducted tests at drive-through sites and at participants’ homes and estimated that 2.8 percent to 5.6 percent of the county’s adult population carried antibodies to the coronavirus. There are 10.4 million people in Los Angeles County.
If accurate, that would mean that 220,000 to 442,000 residents had been exposed. By comparison, only 8,000 cases had been confirmed in the county by early April, when the testing was done.
While finding volunteers was not difficult, it’s not clear how representative they were of the populations at large.
To find participants in the Los Angeles County study, researchers used a random sample of email addresses and telephone numbers of residents to invite people to participate in what they said would be a Covid-19 survey.
The scientists set limits on participation, based on factors like ethnicity and age, in an effort to ensure the sample represented the county’s population. About 1,100 people signed up to be tested.
The study in Santa Clara County found participants by advertising on Facebook. Most of the first volunteers were in wealthy ZIP codes, so the investigators also recruited from poorer areas. As in the Los Angeles County study, the goal was to get a representative sample of the population.
“It’s not perfect, but it’s the best science can do,” said Dr. John Ioannidis, a professor of medicine at Stanford University and an author of the Santa Clara County report.
Antibody studies in other countries have produced similar figures, he noted.
If the numbers prove accurate, the coronavirus may be much less deadly than originally expected, with a fatality rate more closely resembling that of a seasonal flu strain than a pandemic of profound lethality.
But there are questions about who was tested. Among them: Were people who had reason to think they had been infected overrepresented among the volunteers?
“We tried to look into the possibility of bias influencing the results,” Dr. Ioannidis said. “We asked for symptoms recently and in the last few months, and were very careful with our adjustments. We did a very lengthy set of analyses.”
That data will be published in a forthcoming appendix, he said. In any event, bias also can work to lower the numbers if the healthiest people were the ones inclined to be tested, a real possibility.
“Nobody knows the truth — let’s be honest,” Dr. Ioannidis said of the prevalence figures. “But if I had to guess, I would say it is probably higher than our estimate.”
www.nytimes.com
twitter.com
