Currently, many countries are considering the introduction of tracing software on mobile smartphones with the main purpose to inform and alarm the mobile app user. Here, we demonstrate that, in addition to alarming and informing, mobile tracing can detect nearly all individuals that are infected by SARS-CoV-2 , including the notorious asymptomatic infections. Besides voluntary reports of the infectious health status, our algorithm requires the location information of an overwhelming part of the population and then guarantees that almost all SARS-CoV-2 infections in that closed population can be detected. Our algorithm is based on a hidden Markov epidemic model and recursive Bayesian filtering. The potential that mobile tracing apps, in addition to medical testing and quarantining, can eradicate COVID-19 may persuade citizens to trade-off privacy against public health.
Currently, many countries are considering the introduction of tracing software on mobile smartphones with the main purpose to inform and alarm the mobile app user. Here, we demonstrate that, in addition to alarming and informing, mobile tracing can detect nearly all users that are infected by SARS-CoV-2 . Our algorithm BETIS (Bayesian Estimation for Tracing Infection States) makes use of self-reports of the user's health status. Then, BETIS guarantees that almost all SARS-CoV-2 infections of the group of users can be detected. Furthermore, BETIS estimates the virus prevalence in the whole population, consisting of users and non-users. BETIS is based on a hidden Markov epidemic model and recursive Bayesian filtering. The potential that mobile tracing apps, in addition to medical testing and quarantining, can eradicate COVID-19 may persuade citizens to trade-off privacy against public health.
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, including the notorious asymptomatic infections. Besides voluntary reports of the infectious health status, our algorithm requires the location information of an overwhelming part of the population and then
. Our algorithm BETIS (Bayesian Estimation for Tracing Infection States) makes use of self-reports of the user's health status. Then, BETIS
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in that closed population
of the group of users
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Our algorithm
Furthermore, BETIS estimates the virus prevalence in the whole population, consisting of users and non-users. BETIS