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Re-testing as a method of implementing external quality assessment program for COVID-19 real time PCR testing in
Erick Jacob Okek1,2,3, Fredrick Joshua Masembe2, Jocelyn Kiconco1
1Department of Arbovirology, Uganda Virus Research Institute, Entebbe, Uganda.
Plos One
|January 24, 2024
Summary
False positive COVID-19 results were identified in Ugandan laboratories. External quality assessment revealed discrepancies, highlighting the need for standardized molecular testing and improved laboratory quality management systems.
Area of Science:
- Molecular diagnostics
- Public health
- Infectious disease surveillance
Background:
- COVID-19 diagnostics have seen significant advancements.
- The Uganda Virus Research Institute (UVRI) was tasked with ensuring diagnostic quality.
- Re-testing of samples was implemented by UVRI for external quality assessment of COVID-19 molecular diagnostics.
Purpose of the Study:
- To assess the performance agreement of COVID-19 molecular diagnostics in Ugandan laboratories.
- To evaluate the accuracy of primary testing laboratories against the national reference laboratory.
- To identify discrepancies in COVID-19 testing and inform quality improvement strategies.
Main Methods:
- Participating laboratories submitted archived nasopharyngeal samples and metadata to UVRI.
- Samples were re-tested at UVRI using the WHO Berlin protocol.
- Results were compared to primary laboratories, with analysis using Ms Excel and GraphPad Prism.
Main Results:
- 45% of primary laboratories showed 100% performance agreement with UVRI for final test results.
- Differences in Cycle Threshold (CT) values were observed even with concordant results.
- False positives were detected in 55% of laboratories, originating from public, private not-for-profit, and private sectors.
Conclusions:
- False positives were found across different types of testing laboratories in Uganda.
- There is a critical need for standardization of molecular testing platforms nationwide.
- Improvements in laboratory quality management systems are essential to reduce testing discrepancies.

