Effect of diagnostic testing on the isolation rate in a compartmental model with asymptomatic groups

TL;DR

This paper extends classical epidemiological models to include testing and asymptomatic groups, showing that increased testing reduces the need for high isolation rates and that infection dynamics are more sensitive to asymptomatic parameters.

Contribution

It introduces two models incorporating testing and asymptomatic individuals, demonstrating how testing impacts isolation strategies and infection control.

Findings

Massive testing reduces required isolation rates.

Infection dynamics are more sensitive to asymptomatic parameters.

Testing enables better control with lower isolation efforts.

Abstract

We present two epidemiological models, which extend the classical SEIR model by accounting for the effect of indiscriminate quarantining, isolation of infected individuals based on testing and the presence of asymptomatic individuals. Given a constraint that limits the maximal number of simultaneous active cases, we demonstrate that the isolation rate, which enforces this constraint, decreases with the increasing testing rate. The models predict that massive testing allows to control the infection spread using a much lower isolation rate than in the case of indiscriminate quarantining. We also show that dynamics of infection are more sensitive to the parameters of the asymptomatic groups than the corresponding parameters of the symptomatic groups.