This article caught my attention since so much of what we do today is based on big data. This coronavirus situation is no different. In the article John P.A. Ioannidis – professor of medicine, of epidemiology and population health, of biomedical data science, and of statistics at Stanford University – argues that as the coronavirus pandemic takes hold, we are making decisions without reliable data adding that the consequences of extreme measures of social isolation in the long term are completely unknown and that, at present, there no reliable statistics that justify them.
The unknown obviously creates a bunch of uncertainty, and the need to know true statistics becomes critically important for decision making. I would venture to say we agree with some of what Dr. Ioannidis writes. But it’s also true that it’s impossible to figure out the denominator and the virus could infect up to 70% of the world’s population, as Marc Lipsitch from Harvard University expert warns in this interview from CBS News. Definitely worth reading.
Dr. Ioannidis writes, “One of the bottom lines is that we don’t know how long social distancing measures and lockdowns can be maintained without major consequences to the economy, society, and mental health. Read the complete article here.
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