A renewal equation model for disease transmission dynamics with contact tracing

I will present a deterministic model for disease transmission dynamics including diagnosis of symptomatic individuals and contact tracing. The model is structured by time since infection and formulated in terms of the individual disease rates and the parameters characterising diagnosis and contact tracing processes. By incorporating a mechanistic formulation of the processes at the individual level, we obtain an integral equation (delayed in calendar time and advanced in time since infection) for the probability that an infected individual is detected and isolated at any point in time. This is then coupled with a renewal equation for the total incidence to form a closed system describing the transmission dynamics involving contact tracing. After presenting the derivation of the model, I will conclude with some applications of public health relevance, especially in the context of the ongoing COVID-19 pandemic.

Joint work [1] with Lorenzo Pellis (University of Manchester), Nicholas H. Ogden (PHAC, Public Health Agency of Canada) and Jianhong Wu (York University).

This seminar is part of the Oberseminar Dynamics at Technische Universität München.