Epidemics with asymptomatic transmission: Sub-critical phase from recursive contact tracing

TL;DR

This paper investigates how recursive contact tracing can help contain epidemics with high asymptomatic transmission, analyzing the epidemic threshold and providing theoretical and simulation results for network models.

Contribution

It introduces a recursive contact tracing model that extends standard methods, showing its effectiveness in controlling epidemics with significant asymptomatic spread.

Findings

Recursive contact tracing can contain epidemics with high asymptomatic transmission.

Standard contact tracing fails above a certain asymptomatic fraction.

Theoretical analysis and simulations demonstrate the impact of recursion depth and asymptomatic rate.

Abstract

The challenges presented by the COVID-19 epidemic have created a renewed interest in the development of new methods to combat infectious diseases. A prominent property of the SARS-CoV-2 transmission is the significant fraction of asymptomatic transmission. This may influence the effectiveness of the standard contact tracing procedure for quarantining potentially infected individuals. However, the effects of asymptomatic transmission on the epidemic threshold of epidemic spreading on networks are largely unknown. Here we study the critical percolation transition in a simple epidemic network model in the presence of a recursive contact tracing algorithm for instant quarantining. We find that, above a certain fraction of asymptomatic transmission, standard contact tracing loses its ability to suppress spreading below the epidemic threshold. However, we also find that recursive contact tracing opens a possibility to contain epidemics with a large fraction of asymptomatic or presymptomatic transmission. In particular, we calculate the required fraction of network nodes participating in the contact tracing for networks with arbitrary degree distributions and for varying recursion depths and discuss the influence of recursion depth and asymptomatic rate on the epidemic percolation phase transition. We test and illustrate our theoretical results using numerical simulations on infection trees and networks. We anticipate recursive contact tracing to provide a basis for digital, app-based contact tracing tools that extend the efficiency of contact tracing to diseases with a large fraction of asymptomatic transmission.