In a startling finding, new Stanford research reveals between 48,000 and 81,000 people in Santa Clara County alone may already have been infected by the coronavirus by early April — that’s 50 to 85 times more than the number of official cases at that date.

The estimate comes from a first-in-the-nation community study of newly available antibody tests that suggest how widespread the invisible — and perhaps benign — companion has been in the Bay Area’s hardest-hit county. Not only do the numbers show how the U.S.’s severe shortage of testing led to a profound undercount of COVID-19 cases, they indicate the virus is far less deadly than believed.

Just how much of an undercount? Stanford’s low-end estimate of Santa Clara County cases is nearly double the confirmed total — 28,000 — for the entire state of California. The study estimated 2.5% to 4.2% of residents here carry antibodies to the pathogen, a marker of past infection that suggests it may be safe for them to go back to work and school.

“The most important implication is that the number of infections is much greater than the reported number of cases,” concludes the research paper, published Friday morning in the online report medRxiv.

Santa Clara County, home to Stanford University and 1.9 million residents, was one of the first hot spots for the coronavirus in the country. As of Friday, it officially had recorded 1,833 cases and 69 deaths related to coronavirus.

The new Stanford study comes at a time when health experts and elected officials look to immunity as one way to blunt the impact of the pandemic. It is not yet known if antibodies prevent future infection. If so, antibody protection could offer people a safe route out of strict “sheltering.”

The research also implies that the death rate is far lower than believed. At the time of research, 39 county residents had died — a fatality rate, based on estimated infections, of only 0.12 to 0.2%. California’s assumed death rate, based only on confirmed cases, is 3%.

The study also showed how Santa Clara County’s hospitals appeared to have dodged the long-feared surge of patients: Unlike New York, Santa Clara County’s hospitals have yet to be overwhelmed. Fewer than 600 people are being treated for the virus at hospitals throughout the Bay Area.

The Stanford study, led by Dr. Eran Bendavid, an infectious disease specialist and professor of medicine with Stanford Health Policy, shows whether someone has been infected by the virus in the past. They recruited participants by placing targeted advertisements aimed at Santa Clara County on Facebook. They used Facebook because it allows for targeting by zip code and sociodemographic characteristics.

In contrast, COVID-19 virus testing only tests people with significant symptoms. It does not measure the true number of people who have been infected by the virus, many of whom have no symptoms or very mild symptoms.

Several other teams worldwide also have started testing population samples. Like Stanford, they’ve found that there’s a large underestimate of infections.

Reports from the town of Robbio, Italy, where the entire population was tested, suggest at least 10% rate of infections. A survey in the western Germany municipality of Gangelt, highly affected by illness, found a 14% positive rate.

In the U.S., a multiyear project supported by the Centers for Disease Control and Prevention already is collecting samples from blood donors in six major urban areas to create a picture of nationwide antibody prevalence.

The Stanford researchers tested 3,330 people on April 3 and April 4 at three locations spaced across Santa Clara County — two county parks in Los Gatos and San Jose and a church in Mountain View — to gain a snapshot of how many people in the county already had been infected but weren’t seriously sick and didn’t realize it.

“This is critical information,” said principal investigator Bendavid, in an April 3 interview.

The wide range in estimates — 2.5% to 4.2% — is based on what’s known about the performance of the test kit, made by Minnesota’s Premier Biotech. Its sensitivity and specificity would push the number higher or lower.

Because volunteers were disproportionately white and female, relative to the county’s demographics, the team’s data scientists had to make statistical adjustments. Those imbalances were addressed by giving less computational “weight” to white women. Latino and Asian volunteers, who were underrepresented, got greater “weight.”

There are other potential biases. The research may have favored people in good health who could drive to a testing site or those with prior COVID-like illnesses who wanted antibody confirmation.

Like all other emerging COVID-19 research papers, the work has not been peer reviewed. (Conventional publication can take as long as a year.)

“This is a good first step,” said infectious disease epidemiologist George Lemp, former director of the University of California’s HIV/AIDS Research Program, who was not part of the study. “I applaud them for trying to get at some quick estimate.”

“It tells you there is a lot of virus out there – that there are many-fold more infections out there than diagnosed cases,” he said.

The results might be an overestimate, he said, because such testing attracts people who recall being sick and want testing. A better approach, he said, would be to conduct testing at ‘essential’ locations, such as post offices and groceries.

“Given what going on around the country and what we have always seen with other diseases, it is always higher among disenfranchised populations. What’s going on in Vallejo and Stockton?” Lemp asked.

UC San Francisco epidemiologist Dr. George Rutherford raised another concern: The team used a test that is already outdated, he said. And they didn’t take a random sample, although they tried to statistically adjust for that.

“It’s a little too high,” he said of the number of infections Stanford estimated. “We’ll get a closer estimate. Tests are getting better all the time. But, right now, that’s too high.”

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Coronavirus glossary: Terms that became part of our daily dialogue in the past 6 months The test Stanford used measures so-called “neutralizing antibodies,” which are proteins that prevent infection by binding to the part of a virus that latches onto and enters a person’s cell.

These are the same cells that COVID-19 survivors are donating to Bay Area blood banks in an effort to save sick patients.

Now researchers are scrambling to answer questions: Do these antibodies protect against reinfection? Are particular types of antibodies key? What level of antibodies is required for immunity? And how long do they persist?

In an ideal world, the antibodies for COVID-19 would act like those for chicken pox, providing lifetime immunity.

Early research suggests a more complicated picture, clarified by time, global cooperation — and more Stanford-like tests.

Read the study: https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1