The second kind of test is serology, which detects the presence of antibodies to the virus in the bloodstream. Antibodies are evidence of the body’s reaction to an infection, of the fact that a person was previously infected; their presence might also suggest that the person is now immune to the virus. We say “might” and “suggest,” not “prove,” because the notion that immunity to SARS-CoV-2 can be acquired through infection is only, for now, an assumption based on past experience with other viruses. No scientific studies have confirmed this hypothesis yet.

Scientists worldwide are working to determine if in the case of SARS-CoV-2, too, infection confers immunity, and if so, how effectively and for how long. But the first serological studies made public to date have been flawed or too easy to misinterpret.

In a much-discussed study of 3,330 residents of Santa Clara County, Calif., conducted in early April, 2.5 percent to 4.2 percent of the subjects tested positive for antibodies to SARS-CoV-2 — a finding suggesting that some 50 to 85 times more people in the community had been infected than the official figures stated. The study, which had not been peer-reviewed before publication, came under fire for various methodological flaws, including selection bias: Recruitment for the study was conducted via social media, and some subjects might have volunteered in order to get tested because they had reason to believe they had been infected.

One question that debate has highlighted is whether a study conducted in a suspected hot spot of infection — in Santa Clara County or anywhere — can hope to say something useful about the population as a whole or any other group beyond its own subjects. Consider also this serological study conducted in the town of Gangelt, Germany: Some 15 percent of residents tested were found to have SARS-CoV-2 antibodies — but the town was the site of a carnival thought to have been a super spreader of infection.

As for the blood work itself, serological tests, like RT-PCR tests, have inherent limitations to do with accuracy. Even the most precise antibody tests don’t produce neat, binary results.

Measuring antibodies isn’t like determining if a light has been switched on or off; it’s more like gauging the intensity of a bulb controlled by a rheostat. One example: In the early days of an infection, while a patient’s immune system is still revving up, their antibody levels might be too low to detect.