Covid-19 epidemic under the K-quarantine model: Network approach

TL;DR

This paper models the spread of COVID-19 under South Korea's local quarantine strategy using a network-based SEIR model, capturing dynamic link changes and reproducing case patterns.

Contribution

It introduces a network approach with dynamic links to simulate COVID-19 spread under quarantine, incorporating empirical data and analyzing quarantine effectiveness.

Findings

Quarantine links are effectively modeled by disconnecting and reconnecting network edges.

The model reproduces the temporal pattern of confirmed cases.

Asymptomatic patients are detected through quarantine measures.

Abstract

The Covid-19 pandemic is ongoing worldwide, and the damage it has caused is unprecedented. For prevention, South Korea has adopted a local quarantine strategy rather than a global lockdown. This approach not only minimizes economic damage, but it also efficiently prevents the spread of the disease. In this work, the spread of COVID-19 under local quarantine measures is modeled using the Susceptible-Exposed-Infected-Recovered model on complex networks. In this network approach, the links connected to isolated people are disconnected and then reinstated when they are released. This link dynamics leads to time-dependent reproduction number. Numerical simulations are performed on networks with reaction rates estimated from empirical data. The temporal pattern of the cumulative number of confirmed cases is then reproduced. The results show that a large number of asymptomatic infected patients are detected as they are quarantined together with infected patients. Additionally, possible consequences of the breakdowns of local quarantine measures and social distancing are considered.