In:
PLOS ONE, Public Library of Science (PLoS), Vol. 18, No. 7 ( 2023-7-13), p. e0288394-
Abstract:
A preemptive multi-hop contact tracing scheme that tracks not only the direct contacts of those who tested positive for COVID-19, but also secondary or tertiary contacts has been proposed and deployed in practice with some success. We propose a mathematical methodology for evaluating this preemptive contact tracing strategy that combines the contact tracing dynamics and the virus transmission mechanism in a single framework using microscopic Markov Chain approach (MMCA). We perform Monte Carlo (MC) simulations to validate our model and show that the output of our model provides a reasonable match with the result of MC simulations. Utilizing the formulation under a human contact network generated from real-world data, we show that the cost-benefit tradeoff can be significantly enhanced through an implementation of the multi-hop contact tracing as compared to traditional contact tracing. We further shed light on the mechanisms behind the effectiveness of the multi-hop testing strategy using the framework. We show that our mathematical framework allows significantly faster computation of key attributes for multi-hop contact tracing as compared to MC simulations. This in turn enables the investigation of these attributes for large contact networks, and constitutes a significant strength of our approach as the contact networks that arise in practice are typically large.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0288394
DOI:
10.1371/journal.pone.0288394.g001
DOI:
10.1371/journal.pone.0288394.g002
DOI:
10.1371/journal.pone.0288394.g003
DOI:
10.1371/journal.pone.0288394.g004
DOI:
10.1371/journal.pone.0288394.g005
DOI:
10.1371/journal.pone.0288394.g006
DOI:
10.1371/journal.pone.0288394.g007
DOI:
10.1371/journal.pone.0288394.g008
DOI:
10.1371/journal.pone.0288394.g009
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10.1371/journal.pone.0288394.g010
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10.1371/journal.pone.0288394.g011
DOI:
10.1371/journal.pone.0288394.g012
DOI:
10.1371/journal.pone.0288394.g013
DOI:
10.1371/journal.pone.0288394.g014
DOI:
10.1371/journal.pone.0288394.g015
DOI:
10.1371/journal.pone.0288394.g016
DOI:
10.1371/journal.pone.0288394.t001
DOI:
10.1371/journal.pone.0288394.t002
DOI:
10.1371/journal.pone.0288394.s001
DOI:
10.1371/journal.pone.0288394.s002
DOI:
10.1371/journal.pone.0288394.r001
DOI:
10.1371/journal.pone.0288394.r002
DOI:
10.1371/journal.pone.0288394.r003
DOI:
10.1371/journal.pone.0288394.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2267670-3
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