New study highlights efficiency in detecting infectious diseases

In an effort to make large-scale disease testing faster and more affordable, researchers have developed an optimized approach to pooled testing, which could transform public health screening for infectious diseases.

Researchers Dr. Md S. Warasi, Assistant Professor of Mathematics and Statistics at Radford University in Virginia and Dr. Kumer P. Das, Assistant Vice President for Research and Innovation at the University of Louisiana at Lafayette, found that by strategically grouping specimens in pools, testing costs can be slashed without compromising accuracy—a breakthrough that comes as health systems grapple with high demand for screening across diseases like HIV, gonorrhea, and COVID-19.

Their findings were published in a new study, titled “Optimizing Disease Surveillance Through Pooled Testing with Application to Infectious Diseases.” The study, recently published in the Journal of Agricultural, Biological, and Environmental Statistics, evaluates the advantages of using pooled testing for infectious disease detection, particularly when prevalence rates are low.

Traditional individual testing methods can be resource-intensive, especially in large-scale screenings. Pooled testing, however, allows multiple specimens to be tested together, reducing both cost and time. This method has been widely recognized for applications where disease prevalence is low, such as in early screenings or monitoring for outbreaks of diseases like HIV and chlamydia.

Warasi and Das developed a comprehensive framework to determine the ideal pool size for various infectious diseases, considering both cost and testing efficiency. Their research used data from the Louisiana Department of Health on diseases such as HIV, gonorrhea, chlamydia, and SARS-CoV-2. The authors showed that, by tailoring pool sizes to specific infection prevalence rates, public health agencies could achieve significant savings while maintaining the accuracy of prevalence estimates.

“Our findings suggest that careful design and optimization of pooled testing can yield substantial benefits for disease surveillance efforts, particularly in resource-limited settings,” said Warasi. The study provides a new software package and a user-friendly software application to aid health departments and researchers in implementing these optimized testing protocols.

“The ability to efficiently detect and monitor infectious diseases is crucial for timely interventions. By refining how pooled testing is conducted, we hope to empower health departments worldwide to improve their screening processes and respond faster to potential outbreaks,” said Das.

The software tools developed in this study are now available for download, offering practical solutions for public health officials and researchers worldwide.

For more information or to access the software tools, please visit the official study page at https://mdwarasi.shinyapps.io/optimizeGT-app/.