Vía Zoom

Abstract: In this talk, we will discuss two studies performed by the speaker and his research team (SMILE, Collège de France/Sorbonne Université) in the beginning of the pandemic. (1) We study a model where infected individuals can be symptomatic or asymptomatic, use a contact tracing mobile app or not. 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. We show that moderate rates of adoption of a contact tracing app can reduce R0 but are by no means sufficient to reduce it below 1 unless it is already very close to 1 thanks to non-digital interventions. (2) We present a general and tractable framework for modeling and "nowcasting" the epidemic at a national scale. Our approach is based on a fairly general stochastic model for complex diseases using an arbitrarily large number of types (e.g., infective stage, clinical state, risk factor class). We show how structuring the infected population by its infection age, i.e., time elapsed since infection, allows us to decouple dependencies between stages and to time. In the large population limit (obtained either by assumption or as a spontaneous effect of the outbreak), the global scale of the epidemic is well captured by a deterministic McKendrick-Von Foerster 1-d PDE, and such an approximation allows us to make robust predictions on the fate of the epidemic.