Government officials and policymakers attempted to rely on numbers to analyze the impact of COIVD-19 on the nation.
Figures like the quantity of hospitalization or deaths are part of the burden of clearly identifying the outcome or status of the pandemic.
No figure can describe a real pervasiveness of the ongoing pandemic by releasing the number of people that are genuinely infected at any particular time – a significant figure that helps specialists understand if herd immunity can be obtained, even with vaccinations, Scitechdaily reported.
Currently, two scientists from the University of Washington developed a statistical framework incorporating significant COVID-19 dat, like the case counts and deaths provoked by the novel coronavirus, to predict the true prevalence of the disease in the country and individual states.
The approach was made public in the week of July 26 in the Proceedings of the National Academy of Sciences, and it says that in the U.S., roughly 60% of the COVID-19 cases went undetected as of March 7, 2021. That is the last date for which the dataset they used is available.
The newly developed framework may help officials figure out the true impact of the disease in their region, both undiagnosed and diagnosed alike, and thus channel the available resources accordingly, the researchers said.
Adrian Raftery, a U.W. professor of sociology and of statistics, said:
There are all sorts of different data sources we can draw on to understand the COVID-19 pandemic — the number of hospitalizations in a state or the number of tests that come back positive. But each source of data has its own flaws that would give a biased picture of what’s really going on.”
