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• W3197449341 abstract "In our model of the COVID-19 epidemic, infected individuals can be of four types, according whether they are asymptomatic ( A ) or symptomatic ( I ), and use a contact tracing mobile phone application ( Y ) or not ( N ). We denote by R 0 the average number of secondary infections from a random infected individual. We investigate the effect of non-digital interventions (voluntary isolation upon symptom onset, quarantining private contacts) and of digital interventions (contact tracing thanks to the app), depending on the willingness to quarantine, parameterized by four cooperating probabilities. For a given ‘effective’ R 0 obtained with non-digital interventions, we use non-negative matrix theory and stopping line techniques to characterize mathematically the minimal fraction y 0 of app users needed to curb the epidemic, i.e. , for the epidemic to die out with probability 1. We show that under a wide range of scenarios, the threshold y 0 as a function of R 0 rises steeply from 0 at R 0 = 1 to prohibitively large values (of the order of 60−70% up) whenever R 0 is above 1.3. Our results show that moderate rates of adoption of a contact tracing app can reduce R 0 but are by no means sufficient to reduce it below 1 unless it is already very close to 1 thanks to non-digital interventions." @default.
• W3197449341 created "2021-09-13" @default.
• W3197449341 creator A5043927899 @default.
• W3197449341 date "2021-01-01" @default.
• W3197449341 modified "2023-10-11" @default.
• W3197449341 title "A mathematical assessment of the efficiency of quarantining and contact tracing in curbing the COVID-19 epidemic" @default.
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• W3197449341 doi "https://doi.org/10.1051/mmnp/2021042" @default.
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