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Dynamics of new strain emergence on a temporal network

Dynamics of new strain emergence on a temporal network
Dynamics of new strain emergence on a temporal network
Multi-strain competition on networks is observed in many contexts, including infectious disease ecology, information dissemination or behavioral adaptation to epidemics. Despite a substantial body of research has been developed considering static, time-aggregated networks, it remains a challenge to understand the transmission of concurrent strains when links of the network are created and destroyed over time. Here we analyze how network dynamics shapes the outcome of the competition between an initially endemic strain and an emerging one, when both strains follow a susceptible-infected-susceptible dynamics, and spread at time scales comparable with the network evolution one. Using time-resolved data of close-proximity interactions between patients admitted to a hospital and medical health care workers, we analyze the impact of temporal patterns and initial conditions on the dominance diagram and coexistence time. We find that strong variations in activity volume cause the probability that the emerging strain replaces the endemic one to be highly sensitive to the time of emergence. The temporal structure of the network shapes the dominance diagram, with significant variations in the replacement probability (for a given set of epidemiological parameters) observed from the empirical network and a randomized version of it. Our work contributes towards the description of the complex interplay between competing pathogens on temporal networks.
Chakraborty, Sukankana
f0a805bd-745b-48ab-b7cd-b054ab0a67d3
Hoffman, Xavier
bfd7d97f-0d9e-4d71-93ba-c7f2fd41c9c8
Leguia, Marc
842cada4-f9aa-49ca-8843-f783f4a631d4
Nolet, Felix
674105de-c9d1-4d08-a1a0-4a23baad9551
Ortiz, Elisenda
b18d0d4c-4bd4-433e-8fc8-4ca36d990f36
Prunas, Ottavia
f687d84a-9d40-4c0b-9fb7-0ef4618bf4b9
Zavojanni, Leonardo
45e673f9-85d1-4ddd-83ab-fcf375ccf859
Valdano, Eugenio
74d8e3ac-ee73-4009-81fe-414cf3d1d585
Poletto, Chiara
6dfafd78-471a-4ae6-b298-73a237417a28
Chakraborty, Sukankana
f0a805bd-745b-48ab-b7cd-b054ab0a67d3
Hoffman, Xavier
bfd7d97f-0d9e-4d71-93ba-c7f2fd41c9c8
Leguia, Marc
842cada4-f9aa-49ca-8843-f783f4a631d4
Nolet, Felix
674105de-c9d1-4d08-a1a0-4a23baad9551
Ortiz, Elisenda
b18d0d4c-4bd4-433e-8fc8-4ca36d990f36
Prunas, Ottavia
f687d84a-9d40-4c0b-9fb7-0ef4618bf4b9
Zavojanni, Leonardo
45e673f9-85d1-4ddd-83ab-fcf375ccf859
Valdano, Eugenio
74d8e3ac-ee73-4009-81fe-414cf3d1d585
Poletto, Chiara
6dfafd78-471a-4ae6-b298-73a237417a28

Chakraborty, Sukankana, Hoffman, Xavier, Leguia, Marc, Nolet, Felix, Ortiz, Elisenda, Prunas, Ottavia, Zavojanni, Leonardo, Valdano, Eugenio and Poletto, Chiara (2018) Dynamics of new strain emergence on a temporal network.

Record type: Conference or Workshop Item (Paper)

Abstract

Multi-strain competition on networks is observed in many contexts, including infectious disease ecology, information dissemination or behavioral adaptation to epidemics. Despite a substantial body of research has been developed considering static, time-aggregated networks, it remains a challenge to understand the transmission of concurrent strains when links of the network are created and destroyed over time. Here we analyze how network dynamics shapes the outcome of the competition between an initially endemic strain and an emerging one, when both strains follow a susceptible-infected-susceptible dynamics, and spread at time scales comparable with the network evolution one. Using time-resolved data of close-proximity interactions between patients admitted to a hospital and medical health care workers, we analyze the impact of temporal patterns and initial conditions on the dominance diagram and coexistence time. We find that strong variations in activity volume cause the probability that the emerging strain replaces the endemic one to be highly sensitive to the time of emergence. The temporal structure of the network shapes the dominance diagram, with significant variations in the replacement probability (for a given set of epidemiological parameters) observed from the empirical network and a randomized version of it. Our work contributes towards the description of the complex interplay between competing pathogens on temporal networks.

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More information

Published date: 11 October 2018

Identifiers

Local EPrints ID: 451650
URI: http://eprints.soton.ac.uk/id/eprint/451650
PURE UUID: 153c806a-1686-458a-b21b-da7fddae2825

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Date deposited: 18 Oct 2021 16:31
Last modified: 23 Jul 2022 02:22

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Contributors

Author: Sukankana Chakraborty
Author: Xavier Hoffman
Author: Marc Leguia
Author: Felix Nolet
Author: Elisenda Ortiz
Author: Ottavia Prunas
Author: Leonardo Zavojanni
Author: Eugenio Valdano
Author: Chiara Poletto

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