A study published in the journal Lancet Digital Health has claimed that contact tracing apps that are being employed to contain and reduce the spread of the novel coronavirus infection are not very likely to be successful without adequate support and uptake from simultaneous control measures.
Isobel Braithwaite, lead author of the study, said in a statement: "The review shows that, at present, there is insufficient evidence to justify reliance on automated contact tracing approaches without additional extensive public health control measures."
Understanding Potential Impact of Tools
The study said that it has found evidence around the effectiveness of automated contact tracing systems is currently very limited. The researchers stressed that large-scale manual contact tracing alongside other public health control measures - such as physical distancing and closure of indoor spaces such as pubs - is likely to be required in conjunction with automated approaches.
The team found 15 relevant studies by reviewing more than 4,000 papers on automated and partially-automated contact tracing and analyzed these to understand the potential impact these tools could have in controlling the COVID-19 pandemic.
Reviewing and Identifying Useful Data
In total, 4,033 papers were reviewed, which allowed researchers to identify 15 papers with useful data. The seven studies that addressed automated contact tracing directly were modeling studies that all focused on COVID-19.
Five studies of partially-automated contact tracing were descriptive observational studies or case studies, and three studies of automated contact detection looked at a similar disease context to COVID-19 but did not include subsequent tracing or contact notification.
"Partially-automated systems may have some automated processes, for instance in determining the duration of follow-up of contacts required, but do not use the proximity of smartphones as a proxy for contact with an infected person".
Promise of Automated Contact Tracing
Analysis of automated contact tracing apps generally suggested that high population uptake of relevant apps is required alongside other control measures, while partially-automated systems often had better follow-up and slightly more timely intervention.
"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, Dr. Braithwaite said.
"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," Dr. Braithwaite noted.
(With inputs from agencies)
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