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Public Health (PH) surveillance of disease outbreaks is slowed by delays in reporting and testing, potentially leading to increased morbidity and mortality. We propose a two-tier human sentinel network (HSN) of wearable sensors with algorithms processing physiological data generating alerts in response to infections. Individuals would be prompted to seek testing and alerts/results would be reported to a secure platform. Agent-Based Modeling results comparing detection timelines for traditional PH surveillance and the HSN indicate that an HSN covering ~5% of the population can identify the onset of the influenza season 5 – 14 days earlier than current surveillance approaches.
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Ivan Stanish, Jane E. Valentine, Damon Duquaine, Joe Warfield, Ariel Greenberg, James Howard, "Agent-based modeling for evaluation of a wearable-sensor-based disease surveillance network (Conference Presentation)," Proc. SPIE PC12548, Smart Biomedical and Physiological Sensor Technology XX, PC1254807 (14 June 2023); https://doi.org/10.1117/12.2663848