Estimating the Burden of Influenza on Daily Activity at Population Scale Using Commercial Wearable Sensors

Abstract

The severity of viral infections can vary widely, from asymptomatic cases to complications leading to hospitalizations and death. Milder cases, despite being more prevalent, often go undocumented and their public health impact unaccounted for. We estimated the burden of influenza-like-illness (ILI) by leveraging the widespread use of commercial activity trackers. Analysing data from 15,382 US participants who reported ILI symptoms during the 2018-2019 flu season (before the COVID-19 pandemic) and who had high-density wearable sensor data at symptom onset, we estimated an overall nationwide reduction in mobility equivalent to 257 billion steps lost due to ILI symptoms. This finding reflects significant changes in routines, mobility, and employment and is equivalent to 15% of the active US population becoming completely immobilized for 1 day. Moreover, ~60% of this impact occurred among individuals who sought no medical care, who would otherwise be invisible to healthcare and public health reporting systems. We validated our measure against self-reported measures of disease severity. We believe this method has applications for public health, healthcare, and clinical research, from estimating costs of lost productivity at population scale, to measuring effectiveness of anti-ILI treatments, to monitoring recovery after acute viral syndromes, such as during long COVID.