Mass disease surveillance by wearable devices could make a big difference in poor countries, where there are not enough specialists
Save time by listening to our audio articles as you multitaskWhen it comes to disease surveillance, the most useful biomarker is fever, a direct sign of infection. But most wearables do not measure temperature, because accurate readings are hard to do. So a proxy had to be created using the standard things they do measure, such as heart rate, sleep and activity level.
One thing researchers now need to work out is whether the disease-surveillance algorithms based on wearable devices might systematically miss what is happening with some types of people, says Leo Wolansky from the Rockefeller Foundation’s Pandemic Prevention Institute. For example, algorithms might unwittingly be optimised for spotting outbreaks in wealthy areas where people are more likely to have been using high-end wearables for longer.
Activity measures, such as step count, for example, are a formal outcome in drug trials for asthma, arthritis, heart failure, Parkinson’s disease and cystic fibrosis. Measuring how much a person walks can provide a more objective, or at least complementary, picture of a drug’s effect on pain or mood than the standard practice of asking people to give a rating on a scale.
They would choose a treatment that might promise fewer extra days but a greater chance that they would be able to do what matters to them, such as being able to lift up their grandchildren. Pharmaceutical companies are starting to include such metrics among the goalposts they set for new drugs.
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