The fundamental limitations of COVID-19 contact tracing methods and how to resolve them with a Bayesian network approach

Many digital solutions mainly involving Bluetooth technology are being proposed for Contact Tracing Apps (CTA) to reduce the spread of COVID-19. Concerns have been raised regarding privacy, consent, uptake required in a given population, and the degree to which use of CTAs can impact individual behaviours. The introduction of a new CTA alone will not contain COVID-19. The best-case scenario for uptake requires between 90 and 95% of the entire population for containment. This does not factor in any loss due to people dropping out or device incompatibility or that only 79% of the population own a smartphone, with less than 40% in the over-65 age group. Hence, the best-case scenario is beyond that which could conceivably be achieved. We propose to build on some of the digital solutions already under development, with the addition of a Bayesian network model that predicts likelihood for infection supplemented by traditional symptom and contact tracing. When combined with freely available COVID-19 testing with results in 24 hours or less, an effective communication strategy and social distancing, this solution can have a very beneficial effect on containing the spread of this pandemic.