Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains

Abstract Background Co-circulation of influenza strains is common to seasonal epidemics and pandemic emergence. Competition was considered involved in the vicissitudes of co-circulating influenza strains but never quantitatively studied at the human population level. The main purpose of the study wa...

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Main Authors: Bin-Shenq Ho, Kun-Mao Chao
Format: Article
Language:English
Published: BMC 2017-07-01
Series:Journal of Translational Medicine
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12967-017-1269-6
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spelling doaj-f55749098bd343258a0c38c9feccac312020-11-24T22:00:05ZengBMCJournal of Translational Medicine1479-58762017-07-0115111110.1186/s12967-017-1269-6Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strainsBin-Shenq Ho0Kun-Mao Chao1Department of Computer Science and Information Engineering, National Taiwan UniversityDepartment of Computer Science and Information Engineering, National Taiwan UniversityAbstract Background Co-circulation of influenza strains is common to seasonal epidemics and pandemic emergence. Competition was considered involved in the vicissitudes of co-circulating influenza strains but never quantitatively studied at the human population level. The main purpose of the study was to explore the competition dynamics of co-circulating influenza strains in a quantitative way. Methods We constructed a heterogeneous dynamic transmission model and ran the model to fit the weekly A/H1N1 influenza virus isolation rate through an influenza season. The construction process started on the 2007–2008 single-clade influenza season and, with the contribution from the clade-based A/H1N1 epidemiological curves, advanced to the 2008–2009 two-clade influenza season. Pearson method was used to estimate the correlation coefficient between the simulated epidemic curve and the observed weekly A/H1N1 influenza virus isolation rate curve. Results The model found the potentially best-fit simulation with correlation coefficient up to 96% and all the successful simulations converging to the best-fit. The annual effective reproductive number of each co-circulating influenza strain was estimated. We found that, during the 2008–2009 influenza season, the annual effective reproductive number of the succeeding A/H1N1 clade 2B-2, carrying H275Y mutation in the neuraminidase, was estimated around 1.65. As to the preceding A/H1N1 clade 2C-2, the annual effective reproductive number would originally be equivalent to 1.65 but finally took on around 0.75 after the emergence of clade 2B-2. The model reported that clade 2B-2 outcompeted for the 2008–2009 influenza season mainly because clade 2C-2 suffered from a reduction of transmission fitness of around 71% on encountering the former. Conclusions We conclude that interdisciplinary data-driven mathematical modelling could bring to light the transmission dynamics of the A/H1N1 H275Y strains during the 2007–2009 influenza seasons worldwide and may inspire us to tackle the continually emerging drug-resistant A/H1N1pdm09 strains. Furthermore, we provide a prospective approach through mathematical modelling to solving a seemingly unintelligible problem at the human population level and look forward to its application at molecular level through bridging the resolution capacities of related disciplines.http://link.springer.com/article/10.1186/s12967-017-1269-6InfluenzaTransmissionStrain competitionQuantitative modelling
collection DOAJ
language English
format Article
sources DOAJ
author Bin-Shenq Ho
Kun-Mao Chao
spellingShingle Bin-Shenq Ho
Kun-Mao Chao
Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
Journal of Translational Medicine
Influenza
Transmission
Strain competition
Quantitative modelling
author_facet Bin-Shenq Ho
Kun-Mao Chao
author_sort Bin-Shenq Ho
title Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
title_short Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
title_full Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
title_fullStr Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
title_full_unstemmed Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
title_sort data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
publisher BMC
series Journal of Translational Medicine
issn 1479-5876
publishDate 2017-07-01
description Abstract Background Co-circulation of influenza strains is common to seasonal epidemics and pandemic emergence. Competition was considered involved in the vicissitudes of co-circulating influenza strains but never quantitatively studied at the human population level. The main purpose of the study was to explore the competition dynamics of co-circulating influenza strains in a quantitative way. Methods We constructed a heterogeneous dynamic transmission model and ran the model to fit the weekly A/H1N1 influenza virus isolation rate through an influenza season. The construction process started on the 2007–2008 single-clade influenza season and, with the contribution from the clade-based A/H1N1 epidemiological curves, advanced to the 2008–2009 two-clade influenza season. Pearson method was used to estimate the correlation coefficient between the simulated epidemic curve and the observed weekly A/H1N1 influenza virus isolation rate curve. Results The model found the potentially best-fit simulation with correlation coefficient up to 96% and all the successful simulations converging to the best-fit. The annual effective reproductive number of each co-circulating influenza strain was estimated. We found that, during the 2008–2009 influenza season, the annual effective reproductive number of the succeeding A/H1N1 clade 2B-2, carrying H275Y mutation in the neuraminidase, was estimated around 1.65. As to the preceding A/H1N1 clade 2C-2, the annual effective reproductive number would originally be equivalent to 1.65 but finally took on around 0.75 after the emergence of clade 2B-2. The model reported that clade 2B-2 outcompeted for the 2008–2009 influenza season mainly because clade 2C-2 suffered from a reduction of transmission fitness of around 71% on encountering the former. Conclusions We conclude that interdisciplinary data-driven mathematical modelling could bring to light the transmission dynamics of the A/H1N1 H275Y strains during the 2007–2009 influenza seasons worldwide and may inspire us to tackle the continually emerging drug-resistant A/H1N1pdm09 strains. Furthermore, we provide a prospective approach through mathematical modelling to solving a seemingly unintelligible problem at the human population level and look forward to its application at molecular level through bridging the resolution capacities of related disciplines.
topic Influenza
Transmission
Strain competition
Quantitative modelling
url http://link.springer.com/article/10.1186/s12967-017-1269-6
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