A new computational analysis suggests that a vaccine or medication that could shorten the infectious period of COVID-19 may potentially prevent millions of cases and save billions of dollars. The study was led by Bruce Lee along with colleagues in the Public Health Informatics, Computational, and Operations Research (PHICOR) team headquartered at the CUNY Graduate School of Public Health and Health Policy and the Lundquist Research Institute at Harbor-UCLA Medical Center, and publishes in the open-access journal PLOS Computational Biology.
While much of the public conversation surrounding COVID-19 vaccines and medications has focused on preventing or curing the infection, the vaccines and medications that may emerge could have subtler effects. Those that can’t necessarily prevent or cure may still reduce how long someone is contagious.
To clarify the potential value of shortening the infectious period, Lee and colleagues created a computational model that simulates the spread of SARS-CoV-2, the virus that causes COVID-19. They used the model to explore how a vaccine or medication that can reduce the contagious period might alleviate the clinical and economic impact of the disease.
The simulations suggest that reducing the contagious period by half a day could avert up to 1.4 million cases and over 99,000 hospitalizations, saving $209.5 billion in direct medical and indirect costs—even if only a quarter of people with symptoms were treated—and incorporating conservative estimates of how contagious the virus may be. Under the same circumstances, cutting the contagious period by 3.5 days could avert up to 7.4 million cases. Expanding such treatment to 75 percent of everyone infected could avert 29.7 million cases and