Online tool estimates effectiveness of COVID-19 pooled testing
An online tool utilizes SARS-CoV-2 data to aid policymakers in understanding the benefits of pooled testing in different populations, according to study results published in JAMA.
“It goes without saying that there continues to be an unprecedented demand for testing that is beyond any of our historic ability to meet it — and even our current ability to meet it,” Christopher R. Polage, MD, MAS, medical director of the clinical microbiology laboratory and associate professor of pathology at Duke University School of Medicine, told Healio.
“There is a need to develop ways to expand our testing dramatically,” Polage said. “There has been a lot of interest from public health experts and mathematicians in pooling. People have utilized pooling in other scenarios in the past, but it has not really been applied clinically yet.”
Polage and colleagues used PCR “to count SARS-CoV-2 copy numbers in patient samples and create quantitative curves” for three SARS-CoV-2 tests authorized for emergency use by the FDA. They used the curves to develop an online tool that allows researchers to define pool and sample size, positivity rates and other relevant characteristics to compare pooled testing with sing-sample testing. The tool also creates random virtual pools using positive samples from SARS-CoV-2 virus copy data that reflects the expected positivity rate, and then estimates pooled virus copy data with the expected amount of dilution, the researchers explained.
During analysis, pooled testing was found to increase the number of false-negative cases per 1,000 patients — an effect that decreased as pool sizes increased — and to decrease the sensitivity of SARS-CoV-2 detection. Polage and colleagues said that the method “can extend SARS-CoV-2 test supplies and increase the number of patients tested and cases detected, making it useful for population screening and resource-constrained settings.”
“The idea that we are aiming for with this paper, is that this would allow others to explore how pooled testing would work for them using our viral load data,” Polage said. “They could inject their test criteria, their positivity rate locally and their intended use and it would help them make decisions about how they could use pooled testing clinically, for population screening, for school screening, etc., in their own location or region.”
Christopher D. Pilcher, MD, professor in the University of California, San Diego’s division of HIV, infectious diseases and global medicine, wrote in an accompanying editorial that efficient pooling algorithms are sometimes difficult to implement, and lab speed may not translate to fast turnaround times for patients unless programs can properly receive, log and prepare for a large number of new specimens.
“Although these challenges are very real, they are exactly what state, regional and national
public health programs know how to do best. Countries that are facing new waves of SARS-CoV-2 infection need ways to multiply their existing capacity and to do so quickly,” Pilcher wrote. “With reliable data to guide implementation of highly efficient algorithms, the laboratories that already have pooled testing capability need only the right directives, funding, support, and regulation. A new mass screening solution is at hand and it is past time to act.”