Assumptions assumptions assumptions
Good:
“ Since February—which was either three weeks or a lifetime ago—epidemiologists have been trying to get the full scope of the number of infections here in the US. Mostly, that’s meant designing mathematical models. Flawed models, as Andrew Lover, an epidemiologist at the University of Massachusetts-Amherst, readily admits. “We were breaking all kinds of rules,” he says of the early efforts. But the need was urgent. So researchers made do with limited data on the virus’s transmission rate in places like China and Singapore, and from just a few identified cases in the US. Lover, for example, extrapolated from a single case at the CPAC conference in late February. Others looked at cases caught after travel abroad, at deviations from the expected death rate, or at the genetic variation of viral samples.”
Researchers Push for Mass Blood Tests as a Covid-19 Strategy | WIRED
Bad:
“But this mathematical narrative rests on several key assumptions that are not backed by real-world data, experts told Wired.”
Has half the UK already caught COVID-19? Probably not. | Live Science
And getting the important information requires going “maverick”:
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