By Andrew Bogan | The Wall Street Journal
The Covid-19 shutdowns have been based on the premise that the disease would kill more than two million Americans absent drastic actions to slow its spread. That model assumed case fatality rates—the share of infected people who die from the disease—of 1% to 3%. The World Health Organization’s estimated case-fatality rate was 3.4%.
Some experts—including in these pages—have questioned this assumption. They argue that known cases are likely only a small portion of the true number of infections, and thus high case-fatality rates could be off by orders of magnitude. We don’t know what portion of infections have gone undetected for a lack of tests, restrictive qualifications to get tested, and a potentially large incidence of mild illness or asymptomatic infection.
New data support the skeptics’ view—a preliminary study by a Stanford team, released Friday. They conducted a seroprevalence study of Santa Clara County, Calif., on April 3 and 4. They studied a representative sample of 3,300 residents to test for the presence of antibodies in their blood that would show if they had previously been infected with the novel coronavirus.
CORONAVIRUS ANTIBODY TESTING FINDS BAY AREA INFECTIONS MAY BE 85 TIMES HIGHER THAN REPORTED: RESEARCHERS
The county, where I live, is home to about two million people in the heart of Silicon Valley, including San Jose, the state’s third-largest city. It has the largest known number of cases in Northern California and saw some of the earliest cases of community spread in the U.S.
