Detecting epidemic outbreaks with routine blood tests: A comparison of surveillance methods using COVID-19 simulations and real-world seasonal disease data

AIC-based epidemic outbreak detection from routine CRP and inflammatory biomarkers performs best under low test volumes, while CRP-only and basic statistical methods degrade faster.

• Why it matters: Timely outbreak detection is needed to trigger interventions, especially when a new pathogen emerges and no direct testing is available.
• What they did: The study built the BloodCovasim agent-based model to simulate CRP trajectories and evaluated multiple detectors on synthetic data, then applied the same methods to Russian CRP data during back-to-school seasonal infections.
• The result: With large data streams, detectors show similar outbreak-detection probabilities; with fewer tests, moving-average methods outperform basic statistical tests, and composite CBC biomarker sets improve detection versus CRP alone.

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