Optimal test-kit based intervention strategy of epidemic spreading in heterogeneous complex networks

TL;DR

This paper develops a deterministic model for epidemic control using test-kits, analyzing their impact on outbreak size and peak infection in heterogeneous networks, and identifies optimal intervention strategies validated on real-world networks.

Contribution

It introduces a novel deterministic model incorporating test-kits and network heterogeneity, providing analytical and simulation insights for optimal epidemic intervention strategies.

Findings

Test-kits significantly reduce outbreak size and peak infection when targeted at high-degree nodes.

Implementation in real networks confirms effectiveness of strategic test-kit deployment.

Critical transmission thresholds are derived analytically for epidemic onset.

Abstract

We propose a deterministic compartmental model of infectious disease which considers the test-kits as an important ingredient for the suppression and mitigation of epidemics. A rigorous simulation (with analytical argument) is provided to reveal the effective reduction of final outbreak size and peak of infection as a function of basic reproduction number in a single patch. Further, to study the impact of long and short-distance human migration among the patches, we have considered heterogeneous networks where the linear diffusive connectivity is determined by the network link structure. We numerically confirm that implementation of test-kits in the fraction of nodes (patches) having larger degrees or betweenness centralities can reduce the peak of infection (as well as final outbreak size) significantly. A next-generation matrix based analytical treatment is provided to find out the critical transmission probability in the entire network for the onset of epidemics. Finally, the optimal intervention strategy is validated in two real networks: global airport networks and transportation networks of Kolkata, India.