Contact-tracing apps ineffective on their own, study suggests
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Contact-tracing apps are probably not effective enough to prevent the spread of Covid-19 without broad uptake from the population and in conjunction with numerous other measures, a study has concluded.
Researchers from University College London (UCL) analysed the available evidence of the use of the contact-tracing apps that have been put into use thus far.
They found that manual contact tracing on a large scale “is still likely to be required in most contexts” and that “there is a clear need for further research to strengthen the evidence base for automated contact tracing”.
The UCL team said that further research was needed to assess the effects of apps on disease transmission in addition to the technical aspects of contact-tracing apps such as the possible reduction in privacy for users.
“The effectiveness of automated contact tracing in reducing disease transmission depends on both population uptake and timeliness of intervention (e.g. quarantining contacts),” they said.
“As with manual contact tracing, automated contact tracing also relies on accurate and reliable identification of encounters during which transmission occurs.”
The research suggests that even under “optimistic” assumptions of uptake, such as at least 75 per cent of a population downloading the app, automated contact tracing appears unlikely to control the spread of Covid-19 without additional measures.
In local areas or countries with low smartphone ownership, implementing an automated system becomes even more difficult to pull off successfully.
Lead author Dr Isobel Braithwaite, of the UCL Institute of Health Informatics, said: “Although automated contact tracing shows some promise in helping reduce transmission of Covid-19 within communities, our research highlighted the urgent need for further evaluation of these apps within public health practice, as none of the studies we found provided real-world evidence of their effectiveness, and to improve our understanding of how they could support manual contact-tracing systems.”
The researchers looked at more than 4,000 studies on automated and partially automated contact tracing and found 15 relevant research papers.
Most of these studies were either based on modelling, or were observational or case studies, or did not include the full information needed to assess the effectiveness of contact-tracing apps.
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