UNIVERSITY PARK, Pa. — It’s already widely speculated by medical professionals and pundits alike that the initial U.S. coronavirus infection rate was grossly undercounted. Now, a new study concludes that the country’s infection rate early on may have been over 80 times greater than originally reported. Moreover, infections across the U.S. likely doubled almost twice as fast as initially estimated.
How did this happen? In all likelihood there isn’t one main culprit, researchers believe. Instead, a combination of a lack of tests, asymptomatic carriers, and people not recognizing their own symptoms may be to blame.
Mystery flu-like illnesses suggest nearly 9 million COVID-19 cases?
The study, led by scientists at Penn State University, uses data provided by the CDC’s influenza-like illnesses (ILI) surveillance accounting for three weeks in March 2020.
“We analyzed each state’s ILI cases to estimate the number that could not be attributed to influenza and were in excess of seasonal baseline levels,” says Justin Silverman, assistant professor in Penn State’s College of Information Sciences and Technology and Department of Medicine, in a release. “When you subtract these out, you’re left with what we’re calling excess ILI – cases that can’t be explained by either influenza or the typical seasonal variation of respiratory pathogens.”
It’s was quickly noted that all of that extra ILI correlated almost precisely with the spread of COVID-19 all over the United States. “This suggests that ILI data is capturing COVID cases, and there appears to be a much greater undiagnosed population than originally thought,” Silverman explains.
Officially, during the last three weeks of March around 100,000 confirmed coronavirus cases were documented. That falls in line with 8.7 million new ILI cases during that period, which researchers say may very well signal undiagnosed COVID cases.
“At first I couldn’t believe our estimates were correct,” Silverman comments. “But we realized that deaths across the U.S. had been doubling every three days and that our estimate of the infection rate was consistent with three-day doubling since the first observed case was reported in Washington state on January 15.”
The team at Penn State also used their approach to analyze infections rates among individual states. They say that states with a higher per-person rate of infection also show a higher per person rate of ILI. This just further validates that the ILI data is linked to COVID-19 infections.
‘An alternative explanation’
While the per-state infections estimated by researchers are higher than initial official stats, those estimations are fairly close to what states started reporting once extensive antibody testing started. For example, the research team estimates that 9% of the state of New York’s entire population was infected with COVID-19 by the end of March. When New York State tested 3,000 locals, they noted a 13.9% (2.7 million people) infection rate.
For what’s worth, excess ILI appears to have peaked back in March. Since then, states and communities put containment measures in place, and far fewer people with mild symptoms are visiting hospitals or seeking treatment.
“Our results suggest that the overwhelming effects of COVID-19 may have less to do with the virus’ lethality and more to do with how quickly it was able to spread through communities initially,” Silverman concludes. “A lower fatality rate coupled with a higher prevalence of disease and rapid growth of regional epidemics provides an alternative explanation of the large number of deaths and overcrowding of hospitals we have seen in certain areas of the world.”
The study is published in Science Translational Medicine.