Unlinking super-linkers : the topology of epidemic response (Covid-19)

Tools

Nagaraja, Shishir (2020) Unlinking super-linkers : the topology of epidemic response (Covid-19). Preprint / Working Paper. arXiv.org.

[thumbnail of Nagaraja-arXiv2020-Unlinking-super-linkers-topology-epidemic-response-Covid-19]
Preview
 Text. Filename: Nagaraja_arXiv2020_Unlinking_super_linkers_topology_epidemic_response_Covid_19.pdf
License: Creative Commons Attribution 4.0 logo
Download (578kB)| Preview

Abstract

A key characteristic of the spread of infectious diseases is their ability to use efficient transmission paths within contact graphs. This enables the pathogen to maximise infection rates and spread within a target population. In this work, we devise techniques to localise infections and decrease infection rates based on a principled analysis of disease transmission paths within human-contact networks (proximity graphs). Experimental results of disease transmission confirms that contact tracing requires both significant visibility (at least 60\%) into the proximity graph and the ability to place half of the population under isolation, in order to stop the disease. We find that pro-actively isolating super-links -- key proximity encounters -- has significant benefits -- targeted isolation of a fourth of the population based on 35\% visibility into the proximity graph prevents an epidemic outbreak. It turns out that isolating super-spreaders is more effective than contact tracing and testing but less effective than targeting super-links. We highlight the important role of topology in epidemic outbreaks. We argue that proactive innoculation of a population by disabling super-links and super-spreaders may have an important complimentary role alongside contact tracing and testing as part of a sophisticated public-health response to epidemic outbreaks.

CORE (COnnecting REpositories)