The observational model: a data-driven parameter estimation technique for dynamical systems #

James Van Yperen, Eduard Campillo-Funollet, Anotida Madzvamuse

14:50 Tuesday in 2Q50/51.

Part of the Modelling and inference in public health session.

Abstract #

Compartmental models are popular in the mathematics of epidemiology for their simplicity and wide range of applications. Although they are solved as initial value problems for a system of ordinary differential equations, the observed data is typically akin of a boundary value type problem: we observe some of the dependent variables at given times, but we do not know the initial conditions. In this talk, we will demonstrate how to reformulate the famous susceptible-infected-recovered model in terms of the data, we will demonstrate well-posedness of the resulting boundary value problem, discuss issues with parameter identifiability, and show results using real-life datasets.