Acute infections can cause an individual to have an elevated resting heart rate (RHR) and change their routine daily activities due to the physiological response to the inflammatory insult. Consequently, we aimed to evaluate if population trends of seasonal respiratory infections, such as influenza, could be identified through wearable sensors that collect RHR and sleep data.
Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health. By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital to enact timely outbreak response measures to prevent further transmission of influenza cases during outbreaks.
急性感染會導致個體的靜息心率（RHR）升高，並且由於對炎症的生理反應而改變了他們的日常活動。因此，這個研究旨在評估是否可以通過收集RHR和睡眠數據的可穿戴傳感器來識別季節性呼吸道感染（例如流感）的人口趨勢。
活動和生理監測器在美國和全球範圍內越來越多地用於監視個人健康。通過使用這些數據，有可能改善實時和地理精確的流感監測。該資訊對於製定及時的暴發應對措施以防止在暴發期間進一步傳播流感病例至關重要。
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