Comparative Analysis of Molecular Detection Algorithms for Enhanced Dengue Surveillance: A Field Case Evaluation

Area of Science:

• Clinical diagnostics
• Infectious disease surveillance
• Molecular biology

Background:

• The BioFire® Global Fever Panel (GFP) is a multiplex assay for pathogen detection, including dengue virus (DENV).
• Real-world performance data for the GFP, especially in endemic regions, is limited.
• Accurate and timely diagnosis of DENV is crucial for patient management and public health.

Purpose of the Study:

• To evaluate the real-world performance of the BioFire® Global Fever Panel (GFP) for dengue virus (DENV) detection.
• To compare the GFP with real-time reverse transcriptase polymerase chain reaction (qRT-PCR) using surveillance data.
• To assess different testing algorithms combining qRT-PCR and GFP for optimal diagnostic utility.

Main Methods:

• Dengue surveillance data from 224 individuals with acute fever in the Peruvian Amazon were analyzed.
• DENV RNA was detected using both qRT-PCR (serum) and the GFP (whole blood).
• Two reference standards were developed: composite reference standards (CRS) and latent class analysis (LCA), with the best LCA model including a viral load surrogate.

Main Results:

• Using qRT-PCR or LCA as reference, the GFP demonstrated 94.5% sensitivity and 75.7% specificity for DENV detection.
• Using CRS as reference, the GFP showed 95.6% sensitivity and 100% specificity.
• A sequential testing algorithm (qRT-PCR followed by GFP for negatives) achieved 99.3-100% sensitivity and 75.7-100% specificity, offering the best performance-cost-time balance.

Conclusions:

• The BioFire® Global Fever Panel is a reliable and high-performing tool for DENV detection in real-world clinical settings.
• The sequential testing algorithm combining qRT-PCR and GFP provides an effective strategy for DENV diagnosis.
• The cost of the GFP may be a barrier to its widespread use in resource-limited areas, despite its diagnostic advantages.