Scientists from Stanford University, California, are being accused of tipping the scale on research which resulted in implications about the fatal spread of COVID-19.
The study was conducted by Jayanta Bhattacharya, John Ioannidis, and Eran Bendavid, who tested 3,300 people in Santa Clara county for coronavirus antibodies, the same county where the first coronavirus death was recorded in February. The team concluded that 66 people out of the 33,000 were infected with the virus.
Bhattacharya said that 'this [was] a really inexpensive way to get an incredible amount of information.' By this time, similar commercial antibody kits were being released in other places around the globe for mass-testing.
Further calculations were made estimating that around 48,000 to 82,000 out of the nation's 2 million population had become infected by April. The official case count that month was only around 1,000 people.
Why were the Estimates so Off?
Experts opposing the study said that the antibody test Bhattacharya and his team used were not approved by the US Food and Drug Administration. Moreover, the Facebook recruitment of the volunteers meant that 'the participants were not random nor representative of the county.'
Since multiple accusations, the university is currently investigating the accuracy of the research to make sure it was not inaccurate, politically motivated, nor misleading. Julie Greicius from the university said,' the integrity of Stanford Medicine's research is core to our mission. When we receive concerns such as this, they are taken extremely seriously. This matter is being reviewed by the appropriate oversight mechanisms at Stanford.'
Premier Biotech in Minneapolis, Minnesota designed the commercial antibody test kits. Performance data recorded two false positives out of every 136 true negative results. Marm Kilpatrick from the University of California Santa Cruz noted that the positive cases, 66 out of 3300, could possibly be false positives.
'Panic Science'
Consequently, various other parallel data was released from research facilities around the world in what is being called as weaponized research or 'panic science'. In a German village, 500 people were tested and one out of every seven was positive for, estimating a 15% infection rate for the whole town. Virologist Christian Drosten explained that the high infection rate in this area was due to a carnival in February, a 'big point source outbreak' within the village.
Professor Arthur Caplan at NYU School of Medicine said that 'until something is, if you will, reconfirmed, it's just interesting but it's not definitive.' This was a response to the work not being peer-reviewed and was not revised or under the scrutiny of other researchers while the team continues to defend their work and claim that all relevant guidelines had been followed without any political biases.
Statistician Andrew Gelman, a professor at Columbia University, suggested that the authors should 'apologize for wasting everyone's time,' not because of the mistakes they made, but because 'they're the kind of screw-ups that happen if you want to leap out with an exciting find.'
Caplan also added that an inaccurate and hastened research structure result in 'lower quality, too much speed, partial results getting results, no peer review, early pre-print publication.'
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