Mechanistic-statistical SIR modelling for early estimation of the actual number of cases and mortality rate from COVID-19

Lionel Roques; Etienne Klein; Julien Papaix; Samuel Soubeyrand

On the hypotheses underlying the model. The data used here contain a limited amount of information, especially since the observation period considered is short and corresponds to the initial phase of the epidemic dynamics, which can be strongly influenced by discrete events. This limit led us to use a particularly parsimonious model in order to avoid problems of identifiability for the parameters. The assumptions underlying the model are therefore relatively simple and the results must be interpreted with regard to these assumptions. For instance, the date of the introduction t 0 must be seen as an efficient date of introduction for a dynamics where a single introduction would be decisive for the outbreak and the other (anterior and posterior) introductions would have an insignificant effect on the dynamics.