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Disease persistence on temporal contact networks accounting for heterogeneous infectious periods

The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This simplifying assumption is, however, often unrealis...

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Autores principales: Darbon, Alexandre, Colombi, Davide, Valdano, Eugenio, Savini, Lara, Giovannini, Armando, Colizza, Vittoria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366198/
https://www.ncbi.nlm.nih.gov/pubmed/30800384
http://dx.doi.org/10.1098/rsos.181404
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author Darbon, Alexandre
Colombi, Davide
Valdano, Eugenio
Savini, Lara
Giovannini, Armando
Colizza, Vittoria
author_facet Darbon, Alexandre
Colombi, Davide
Valdano, Eugenio
Savini, Lara
Giovannini, Armando
Colizza, Vittoria
author_sort Darbon, Alexandre
collection PubMed
description The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This simplifying assumption is, however, often unrealistic, as hosts may have different infectious periods, due, for instance, to individual host–pathogen interactions or inhomogeneous access to treatment. While previous work accounted for this heterogeneity in static networks, a full theoretical understanding of the interplay of varying infectious periods and time-evolving contacts is still missing. Here, we consider a susceptible-infectious-susceptible epidemic on a temporal network with host-specific average infectious periods, and develop an analytical framework to estimate the epidemic threshold, i.e. the critical transmissibility for disease spread in the host population. Integrating contact data for transmission with outbreak data and epidemiological estimates, we apply our framework to three real-world case studies exploring different epidemic contexts—the persistence of bovine tuberculosis in southern Italy, the spread of nosocomial infections in a hospital, and the diffusion of pandemic influenza in a school. We find that the homogeneous parametrization may cause important biases in the assessment of the epidemic risk of the host population. Our approach is also able to identify groups of hosts mostly responsible for disease diffusion who may be targeted for prevention and control, aiding public health interventions.
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spelling pubmed-63661982019-02-22 Disease persistence on temporal contact networks accounting for heterogeneous infectious periods Darbon, Alexandre Colombi, Davide Valdano, Eugenio Savini, Lara Giovannini, Armando Colizza, Vittoria R Soc Open Sci Mathematics The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This simplifying assumption is, however, often unrealistic, as hosts may have different infectious periods, due, for instance, to individual host–pathogen interactions or inhomogeneous access to treatment. While previous work accounted for this heterogeneity in static networks, a full theoretical understanding of the interplay of varying infectious periods and time-evolving contacts is still missing. Here, we consider a susceptible-infectious-susceptible epidemic on a temporal network with host-specific average infectious periods, and develop an analytical framework to estimate the epidemic threshold, i.e. the critical transmissibility for disease spread in the host population. Integrating contact data for transmission with outbreak data and epidemiological estimates, we apply our framework to three real-world case studies exploring different epidemic contexts—the persistence of bovine tuberculosis in southern Italy, the spread of nosocomial infections in a hospital, and the diffusion of pandemic influenza in a school. We find that the homogeneous parametrization may cause important biases in the assessment of the epidemic risk of the host population. Our approach is also able to identify groups of hosts mostly responsible for disease diffusion who may be targeted for prevention and control, aiding public health interventions. The Royal Society 2019-01-16 /pmc/articles/PMC6366198/ /pubmed/30800384 http://dx.doi.org/10.1098/rsos.181404 Text en © 2019 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Mathematics
Darbon, Alexandre
Colombi, Davide
Valdano, Eugenio
Savini, Lara
Giovannini, Armando
Colizza, Vittoria
Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
title Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
title_full Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
title_fullStr Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
title_full_unstemmed Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
title_short Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
title_sort disease persistence on temporal contact networks accounting for heterogeneous infectious periods
topic Mathematics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366198/
https://www.ncbi.nlm.nih.gov/pubmed/30800384
http://dx.doi.org/10.1098/rsos.181404
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