The app launched in late March has millions of users in the U.S. and U.K.
it doesn't trace or track users"so it alleviates any privacy concerns." However, it under-represents those in very deprived areas, some ethnic minorities, and the over 70s, he said, adding that a new feature enabling users to track the symptoms of others has been introduced to tackle this.
testing because the infection may be missed if swabs are taken too late."TheSymptom Study app would be able to pick up these cases where early testing was not possible," he said. "There are issues with all the tests both viral and antibody and that's why we need other methods like this symptom algorithm to help clinics and researchers,"a base level indicator by officials who are on the look-out for emerging outbreaks."That's why it's important that high numbers of people in a population are logging daily so the data is as accurate as possible," he said, adding:"This approach will work well in the absence of conventional testing." The app is also accurate enough to help leaders decide on when to re-open an economy, he said."When it comes to using the app to decide whether it is safe to lift lockdown [measures], it's about following the data curve downwards and checking it against hospital data and other data to get the full picture of the virus in the population."paper, but said the app can't replace traditional testing methods.Institute, said in a statement that although the level of accuracy was too low to replace testing, the model would potentially be useful for rapidly alerting someone who reports that they have symptoms indicative of, emeritus professor of applied statistics at The Open University, said:"Sometimes such a model will track too closely the characteristics of the people who provided the data for it, and therefore not work well in different groups of people—but the researchers checked this by seeing how good the predictions were for app users in the U.S. The model passed this validation test pretty well." Peter Bannister, a biomedical engineer and Executive Chair of the Institution of Engineering and Technology, said the authors acknowledged that the algorithm could overestimate the number of users who are infected, as RT-testing is only carried out when a person has clear symptoms or is at high risk of exposure to the"A more comprehensive program of testing would need to be in place to validate such an algorithm for widespread use and to handle the inevitable false alerts raised by the algorithm given its reported accuracy," he said.at the U.K.'s University of Sheffield, said:"The performance of their diagnostic model is still quite poor compared to genetic tests that achieve >95 percent accuracy, however, the symptoms highlighted in their model can be used by the government to
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