Contact tracing is an important disease intervention measure that targets contacts. It is a challenge for traditional random mixing models because such models do not track contacts. Contact network models track contacts, and are thus suitable for modeling contact tracing. However, they require statistical information of the contact network that is usually not readily available. In this talk, we present a new approach that borrows the edge dynamics idea from the network models to track contacts, and models an SIR epidemic spreading in a randomly mixed population. This model allows us to study the effect of contact tracing on the basic reproduction number and final epidemic size. We also estimate the effects of tracing coverage and capacity on the effectiveness of contact tracing. Our approach can be extended to more realistic models that incorporate latent and asymptomatic patients.

Bios

Tanya Philippsen is a master’s student in Applied Mathematics at the University of Victoria under the supervision of Dr. Junling Ma and Dr. Pauline van den Driessche. She also holds a Master’s degree in Public Health from the University of Waterloo and has previously worked in global disease surveillance and outbreak detection. Some of her research interests include: infectious disease modelling, emerging and re-emerging diseases, and the social determinants of health.

Manting Wang is a PhD student in Applied Mathematics at the University of Victoria under the supervision of Dr. Junling Ma. She received an MSc in Applied Mathematics from Donghua University, China. Her research interests include disease modelling and control and disease dynamics on contact networks.