We showed that the best-case scenario for uptake requires between 90% and 95% of the entire population for infection containment. 2020) conducted a systematic review of recent literature proposing CTA solutions for COVID19, highlighting issues relating to privacy and confidentiality and identifying the sweet-spot for the uptake of CTA at which it becomes clinically useful. The first of these studies ( Scott McLachlan, Lucas, Dube, Hitman, et al.
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This paper is part of a set of studies conducted by a multidisciplinary team of researchers that suggest that any standalone contact tracing approach, manual or automated, is unlikely to contain, a high-prevalence highly contagious disease like COVID19 (McLachlan et al, 2020b McLachlan et al 2020c). For this purpose, the only data needed to be centrally collected is the probability the user has COVID19 and the GPS location.Ĭentral to many governmental measures to contain the current COVID19 infection and reduce the impact of potential subsequent waves, are the use of manual and smartphone-based contact tracing methods, referred to as Contact Tracing Apps (CTA). When the model is embedded in a smartphone app, it can be used to detect new outbreaks in a monitored population and identify outbreak locations as early as possible. The model then provides them feedback about the likelihood of the presence of asymptotic, mild or severe COVID19 (past, present and projected). Users of the model can provide as much or little personal information as they wish about relevant risk factors, symptoms, and recent social interactions.
We present a causal probabilistic model (a Bayesian network) that provides the basis for a practical CTA solution that addresses some of the concerns and which has the advantage of minimal infringement of privacy. Concerns about the practicality and effectiveness of using Contact Tracing Apps (CTA) to reduce the spread of COVID19 have been well documented and, in the UK, led to the abandonment of the NHS CTA shortly after its release in May 2020.
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