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EpiMix: A novel method to estimate effective reproduction number

Transmission potential of a pathogen, often quantified by the time-varying reproduction number [Formula: see text] , provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for [Formula: see...

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Detalles Bibliográficos
Autores principales: Jin, Shihui, Dickens, Borame Lee, Lim, Jue Tao, Cook, Alex R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320401/
https://www.ncbi.nlm.nih.gov/pubmed/37416322
http://dx.doi.org/10.1016/j.idm.2023.06.002
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author Jin, Shihui
Dickens, Borame Lee
Lim, Jue Tao
Cook, Alex R.
author_facet Jin, Shihui
Dickens, Borame Lee
Lim, Jue Tao
Cook, Alex R.
author_sort Jin, Shihui
collection PubMed
description Transmission potential of a pathogen, often quantified by the time-varying reproduction number [Formula: see text] , provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for [Formula: see text] estimation, wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework. Using Integrated Nested Laplace Approximation, EpiMix is able to efficiently generate reliable, deterministic [Formula: see text] estimates. In the simulations and case studies performed, we further demonstrated the method's robustness in low-incidence scenarios, together with other merits, including its flexibility in selecting variables and tolerance of varying reporting rates. All these make EpiMix a potentially useful tool for real-time [Formula: see text] estimation provided that the serial interval distribution, time series of case counts and external influencing factors are available.
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spelling pubmed-103204012023-07-06 EpiMix: A novel method to estimate effective reproduction number Jin, Shihui Dickens, Borame Lee Lim, Jue Tao Cook, Alex R. Infect Dis Model Article Transmission potential of a pathogen, often quantified by the time-varying reproduction number [Formula: see text] , provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for [Formula: see text] estimation, wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework. Using Integrated Nested Laplace Approximation, EpiMix is able to efficiently generate reliable, deterministic [Formula: see text] estimates. In the simulations and case studies performed, we further demonstrated the method's robustness in low-incidence scenarios, together with other merits, including its flexibility in selecting variables and tolerance of varying reporting rates. All these make EpiMix a potentially useful tool for real-time [Formula: see text] estimation provided that the serial interval distribution, time series of case counts and external influencing factors are available. KeAi Publishing 2023-06-20 /pmc/articles/PMC10320401/ /pubmed/37416322 http://dx.doi.org/10.1016/j.idm.2023.06.002 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Jin, Shihui
Dickens, Borame Lee
Lim, Jue Tao
Cook, Alex R.
EpiMix: A novel method to estimate effective reproduction number
title EpiMix: A novel method to estimate effective reproduction number
title_full EpiMix: A novel method to estimate effective reproduction number
title_fullStr EpiMix: A novel method to estimate effective reproduction number
title_full_unstemmed EpiMix: A novel method to estimate effective reproduction number
title_short EpiMix: A novel method to estimate effective reproduction number
title_sort epimix: a novel method to estimate effective reproduction number
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320401/
https://www.ncbi.nlm.nih.gov/pubmed/37416322
http://dx.doi.org/10.1016/j.idm.2023.06.002
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