Economic Impact of Testing Algorithms for Respiratory Viruses
Author Information
Author(s): Lee Bonita E, Mukhi Shamir N, May-Hadford Jennifer, Plitt Sabrina, Louie Marie, Drews Steven J
Primary Institution: University of Alberta
Hypothesis
What is the relative economic impact of different molecular-based laboratory algorithms for respiratory viral pathogen detection?
Conclusion
Testing costs will vary depending on the test volume and prevalence of influenza A strains, and a more costly algorithm may be chosen to ensure quicker test results.
Supporting Evidence
- Scenario A provided more information about mixed respiratory virus infection compared to Scenario B.
- Scenario D was the least expensive method throughout both waves of the pandemic.
- Testing costs will vary depending on the prevalence of influenza A and other circulating viruses.
- An ideal pandemic plan should allow for effective shifts between different testing algorithms.
Takeaway
This study looked at different ways to test for viruses that cause respiratory illnesses and found that some methods are cheaper but take longer to get results.
Methodology
Historical data was collected from two waves of the pandemic using a secure web-based platform, and four proposed molecular testing scenarios were generated.
Potential Biases
Potential biases in decision-making due to reliance on cost alone without considering other factors.
Limitations
The study does not account for overhead costs and assumes negligible false-positive and false-negative results.
Participant Demographics
Population of Alberta, Canada, approximately 3.7 million.
Statistical Information
Confidence Interval
98.6% (CI 96.5-99.6%) for CDC-M and 77.3% (CI 72.1-82.1%) for RVP.
Digital Object Identifier (DOI)
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