Recognizing that many data sets are needed to tell the full story of the COVID-19 pandemic and understand if herd immunity can be achieved, two scientists from the University of Washington have created a statistical model of key COVID-19 data to model the disease’s true prevalence in the United States.
“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,” Adrian Raftery, senior author and a UW professor of sociology and of statistics, said. “But each source of data has its own flaws that would give a biased picture of what’s really going on. What we wanted to do is to develop a framework that corrects the flaws in multiple data sources and draws on their strengths to give us an idea of COVID-19’s prevalence in a region, a state, or the country as a whole.”
This model draws from three figures, including case counts and deaths due to COVID-19, as well as the number of COVID-19 tests administered daily, allowing researchers to counteract the biases of any one source. Raftery cited the number of positive test results in a given area as one often misleading data point since it is highly affected by access to tests and the population’s willingness to be tested.
“It can depend on the severity of the pandemic and the amount of testing in that state,” Nicholas Irons, lead author and a UW statistics doctoral student, said. “If you have a state with severe pandemic but limited testing, the undercount can be very high, and you’re missing the vast majority of infections that are occurring. Or, you could have a situation where testing is widespread, and the pandemic is not as severe. There, the undercount rate would be lower.”
As published in the Proceedings of the National Academy of Sciences this month, the report projected that as many as 60 percent of COVID-19 cases may have gone undetected as of March 7, 2021. That same research, funded by the National Institutes of Health, stated that an estimated 19.7 percent of U.S. residents — some 65 million people — had been infected by COVID-19, meaning the nation is unlikely to reach herd immunity without continuing its vaccination campaign.
Irons and Raftery added that some 60 percent of U.S. COVID-19 cases may not have been counted or tracked at all, based on existing figures.
“We think this tool can make a difference by giving the people in charge a more accurate picture of how many people are infected and what fraction of them are being missed by current testing and treatment efforts,” said Raftery.