Herd Immunity Won't Happen Soon To Stop COVID-19 Says Indian Origin Stanford Researcher
Jay Bhattacharya, professor of medicine at Stanford University has been looking at herd immunity in California, however, they discovered that the state was nowhere close to herd immunity.
With every passing day, we hope for some solution to come out that would put an end to this COVID-19 mess. We hear new vaccines being developed every day, the success of plasma therapy, but nothing concrete has been put forth as of now.
Reuters
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One way some scientists think that would help in getting rid of COVID-19 is through herd immunity. Basically, hoping with more number of people in a community getting the virus, and recovering from it will develop antibodies in their body that would make them immune, and with them being immune, people who never got COVID-19 would automatically get saved from contracting the novel coronavirus.
Jay Bhattacharya, professor of medicine at Stanford University has been looking at herd immunity in California, however, they discovered that the state was nowhere close to herd immunity.
Stanford University
The study reveals that approximately 2.49 percent to 4.16 percent in Santa Clara County have been infected with COVID-19 -- whereas the threshold for herd immunity needs to be at 50 percent or higher, to be able to slow down the transmission of disease.
The study also reveals that 50 to 85 percent more people had COVID-19 in early April than actually were reported by county.
Researchers targeted people for recruiting in the study using Facebook ads. It collected a total 3,330 blood samples at drive-up test sites in Santa Clara County on a weekend. These samples were then looked for antibodies of COVID-19.
They employed antibody testing to look for missed out cases while understanding a better picture of the spreading of the disease throughout communities.
Reuters
According to Prof Jay Bhattacharya, this information could be beneficial to improve projections and disease modelling. Even though epidemiologists have stated that there are more infected people present compared to the people who are tested, but there is no clarity on the number of infections yet.
"It just helps us plan better. Before, we were making policy in the dark. If I get the infection, how likely is it I'm going to die? That number depends on knowing how many people have had the infection, not just actively have it now, but have had it and recovered from it."
The study is yet to be peer-reviewed.
