Model Estimates US COVID-19 Infections 3 Times Greater Than Reported
In most areas tested, the algorithm's estimates of infections corresponded to the percentage of people who had tested positive for antibodies.
Investigators from the University of Texas Southwestern have developed a machine-learning algorithm that estimates coronavirus disease 2019 (COVID-19) incidence in the United Sates is 3 times larger than the number of confirmed cases. Data from the study was published in the journal PLOS ONE.
"The estimates of actual infections reveal for the first time the true severity of COVID-19 across the U.S. and in countries worldwide," Jungsik Noh, first author on the study and an assistant professor in the Lydia Hill Department of Bioinformatics at UT Southwestern said.
The algorithm provides how many people are infected across the 50 countries hit hardest by the pandemic, as well as updated, daily estimates of total infections. It uses the number of reported deaths, a 0.66 infection fatality rate, and other factors like average number of days from the onset of symptoms to death or recovery and confirmed cases to calculate a ratio of confirmed-to-estimated infections.
Investigators behind the study analyzed the current available information from the algorithm and found that 71 million people in the US, 21.5 percent of the population, had contracted the disease. This is in contrast to the 26.7 million cases that have been publicly reported. Based on calculations completed this past September, it was estimated that 25 of the 50 countries had a 5 to 20 times greater number of confirmed cases than was reported.
Though the death rate, among other information, is still uncertain about COVID-19, the investigators believe the model’s estimates leave out fewer cases and is more accurate, providing a more comprehensive disease prevalence estimate than current reports.
"These are critical statistics about the severity of COVID-19 in each region. Knowing the true severity in different regions will help us effectively fight against the virus spreading," Noh said "The currently infected population is the cause of future infections and deaths. Its actual size in a region is a crucial variable required when determining the severity of COVID-19 and building strategies against regional outbreaks."
