A model for an epidemic with contact tracing and cluster isolation, and a detection paradox

TL;DR

This paper models an epidemic incorporating contact tracing and cluster isolation, deriving distributions of key variables, and reveals a paradox where the size distribution of isolated clusters differs from that of typical detected clusters.

Contribution

It provides explicit calculations of cluster size distributions and uncovers a detection paradox in epidemic modeling with contact tracing.

Findings

Explicit asymptotic distribution of isolated cluster sizes

Identification of a detection paradox in cluster size distributions

Application of super-critical branching process theorems

Abstract

We determine the distributions of some random variables related to a simple model of an epidemic with contact tracing and cluster isolation. This enables us to apply general limit theorems for super-critical Crump-Mode-Jagers branching processes. Notably, we compute explicitly the asymptotic proportion of isolated clusters with a given size amongst all isolated clusters, conditionally on survival of the epidemic. Somewhat surprisingly, the latter differs from the distribution of the size of a typical cluster at the time of its detection; and we explain the reasons behind this seeming paradox.