COVID-19 Cases Have Been 'Severely Undercounted,' Study Says medscape.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from medscape.com Daily Mail and Mail on Sunday newspapers.
World health experts have long suspected that the incidence of COVID-19 has been higher than reported. Now, a machine-learning algorithm developed at UT Southwestern estimates that the number of COVID-19 cases in the U.S. since the pandemic began is nearly three times that of confirmed cases.
Severe undercounting of Covid cases worldwide: Study
February 09, 2021
Over 20 per cent of UK, US population already infected
Researchers at the University of Texas Southwestern Medical Center used a new machine learning technique to estimate the actual number of coronavirus cases within 50 US States and 50 countries.
The study, published in the journal
PLOS One, revealed that during the ongoing pandemic, US States and many countries have reported daily counts of Covid-19 infections and deaths confirmed by testing.
However, many infections have gone undetected, resulting in under-counting of the total number of people currently infected at any given point in time. The authors of the study believe that this is an important metric to guide public health efforts.
DALLAS - Feb. 8, 2021 - World health experts have long suspected that the incidence of COVID-19 has been higher than reported. Now, a machine-learning algorithm developed at UT Southwestern estimates that the number of COVID-19 cases in the U.S. since the pandemic began is nearly three times that of confirmed cases.
A new machine-learning framework uses reported test results and death rates to calculate estimates of the actual number of current COVID-19 infections within all 50 U.S. states and 50 countries. Jungsik Noh and Gaudenz Danuser of the University of Texas Southwestern Medical Center present these findings in the open-access journal