The rapid development and deployment of COVID-19 tests in the United States prevented approximately 1.4 million deaths and 7 million hospitalizations during the pandemic, according to new research from Johns Hopkins Applied Physics Laboratory published in The Lancet Public Health.
Between January 2020 and December 2022, the U.S. produced 6.7 billion COVID-19 tests through public-private partnerships, including 1.5 billion laboratory tests, 1.9 billion point-of-care tests, and 3.2 billion at-home tests. Of these, approximately 2.7 billion tests were performed during this period.
“The analysis found that the early development, manufacturing and distribution of tests significantly reduced severe COVID-19 outcomes,” said Gary Lin, a computational epidemiologist at Johns Hopkins APL and study co-author. “Through modeling and simulation, we’ve shown how national coordination can effectively leverage resources and capabilities.”
The research team used a digital twin prototype – a virtual simulation environment – to compare what actually happened against scenarios with fewer tests or delayed testing programs. The simulation found that a six-month delay in scaling up testing would have led to about 150,000 hospitalizations and 25,000 deaths per week during the winter surge of 2020-2021.
“The digital twin helps us quantitatively understand the impact and consequences of disruptions and changing infection levels on test availability,” explained Elizabeth Currier, the APL digital twin project manager. “It can also evaluate the impact of policies and investments and be used in planning and evaluating supply needs, aiding in response and ensuring a secure supply chain for future medical crises.”
The study demonstrates that timing was crucial – early availability of testing had more impact than the total number of tests available. The researchers found that having even 20% of the actual number of tests, if deployed quickly, would have been more effective than having full testing capacity delayed by six months.
The digital twin modeling tool has since expanded beyond COVID-19 and is now being used to monitor nationwide testing for influenza, respiratory syncytial virus (RSV), and other public health threats, preparing the nation for future pandemics.