New Pooled Testing Strategies can Better Identify COVID-19
Pooled testing allows multiple samples to be processed at once and help increase testing efficiency.
A recent study conducted by investigators at the Harvard T.H. Chan School of Public Health and the Broad Institute of MIT and Harvard have discovered that a novel approach to pooled COVID-19 testing can be a significant tool to help curb the ongoing pandemic, despite the widespread infections in communities. Results from the study were published in the online journal Science Translational Medicine.
"Our work helps quantify pooled testing's tradeoffs between losses in sensitivity from sample dilution and gains in efficiency," Brian Cleary, a co-corresponding author with on the study said. "We show how to identify simple strategies that require no expertise to implement and that result in the greatest number of infections identified on a fixed budget."
Although testing for COVID-19 is one of the most powerful tools to use so that we can safely reopen schools and businesses, the limited and costly nature of them has hampered diagnosing those with an infection and has impacted public health efforts aiming to halt its spread.
The investigators behind the study thought to identify ways to make pooled testing more useful during outbreaks that become more widespread. The team developed a model for how quantities of vial RNA vary across those who are infected during an outbreak. This gave the investigators a detailed idea of how test sensitivity is impacted by pool size and COVID-19 prevalence.
The team then employed the model to identify the optimal pooled testing strategies un varying scenarios. With the model, the testing could be tailored to the recourses that are available in a given community so that the number of infections would be maximized using a few tests as possible.
The team was able to create simple pooled testing schemes that identified as many as 20 times more infected people a day compared with individual testing, even in laboratories with recourse constraints.
"Our research adds another tool to the testing and public health toolbox," Michael Mina, assistant professor of epidemiology at Harvard Chan School said. "For public health agencies and clinical laboratories that are performing testing under resource limitations--which for COVID-19 is nearly every nation--this new research demonstrates that we can gain much more testing power for both medical and public health use with the same or even fewer resources than are currently being utilized."