Your smartwatch can probably tell that you are sick before you can—and if everyone followed their watch's advice to self-isolate, incipient epidemics could be stopped in their tracks, according to a study.
During the early days of COVID-19, research showed that 44% of infections were spread before people even felt sick, making early detection critical for stopping outbreaks. Recent studies have demonstrated that smartwatches can detect infections before symptoms appear by picking up subtle physiological changes, such as shifts in heart rate, sleep patterns, activity levels, and skin temperature. Using machine learning, these signals can help identify infections early and prompt individuals to reduce contact with others, slowing disease spread. To explore the potential impact, Dan Yamin and colleagues developed a mathematical model to estimate how smartwatch-based detection could help control the spread of COVID-19 and influenza. Their findings suggest that if smartwatch detection led infected individuals to reduce their social contacts by 66%, transmission risk could be reduced by nearly 50% for COVID-19 and pandemic influenza. In some scenarios, if social contact was reduced even further, certain COVID-19 variants and influenza strains could be eliminated entirely. The model indicated that earlier detection played a greater role than contact reduction alone in limiting outbreaks. According to the authors, the research highlights the potential of smartwatches in managing infectious diseases. By identifying infections sooner and prompting timely action, wearable technology could help contain future outbreaks, reduce the need for lockdowns, and even prevent pandemics before they start, the authors suggest.
