April 21, 2020

As researchers across the globe scramble to develop and improve testing for the novel coronavirus (SARS-CoV-2) that causes COVID-19 disease, preliminary research from Drexel University suggests they have their work cut out for them.

Results from two studies, recently published online prior to acceptance in a peer-reviewed journal, suggest that lack of data on the sensitivity of current tests could significantly skew the numbers of cases that are being diagnosed.

Igor Burstyn, PhD, an associate professor, and Neal D. Goldstein, PhD, an assistant research professor, both in the Dornsife School of Public Health, are collaborating with Prof. Paul Gustafson, chair of the Department of Statistics at the University of British Columbia in Canada.

Their work stresses the urgent need to understand just how accurate the current polymerase chain reaction (PCR) diagnostic test is. And their statistical modeling approach estimates a number of cases of COVID-19 could have been misclassified among people who are tested for it in Philadelphia. The methods that they developed can be replicated to estimate the effects of inaccuracy of testing in other cities.

Burstyn and Goldstein provided some additional insight on their work and the importance of having accurate testing for both mitigation efforts and recovery from the pandemic.

Read the full Q&A with Burstyn and Goldstein on the Drexel News Blog: As Coronavirus Cases Grow, New Drexel Research Cautions About Impact From Inaccuracies in COVID-19 Testing