Survey to Assess the Feasibility of Implementing a Human Sentinel Disease Surveillance Network Using Privately Owned Wearable Devices

Current public health surveillance practices exhibit delays in outbreak onset detection due to time lags associated with symptom manifestation, diagnosis, and case reporting and aggregation. To accelerate disease outbreak detection, a 2-tier Human Sentinel Network (HSN) concept was proposed, consisting of wearable physiological sensors capable of detecting presymptomatic illnesses (Tier 1) that prompt individuals to enter a diagnostic testing stage (Tier 2). In the envisioned HSN concept, both wearable alerts and test results are reported automatically and immediately to a secure online platform via a dedicated application. Given the capabilities of smart wearable devices and over-the-counter test kits in the consumer market, along with advances in data analytics and computing power, the HSN represents an information stream that could complement existing surveillance tools. To assess the adoptability of the HSN, a national survey was conducted among urban and suburban centers (6,616 total adult respondents) to quantify several factors tied to recruiting and motivating HSN participation. This paper provides statistical HSN characteristics regarding demographics (age, race, education, income); smart device ownership (57% of respondents); current smart device usage patterns (47.5% of respondents with smart devices report wearing their devices at least 12 hours every day); expected participation and willingness to share data (41.2% or higher depending upon the organization managing the HSN program); compliance (88.5% of HSN participants likely to undergo testing); and methods by which survey respondents might be incentivized to participate. This survey supports a joint probability of HSN design factors that exceeds the minimum modeled coverage requirements of 0.05 (5% population coverage) to achieve a multiday detection advantage relative to traditional public health surveillance.