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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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 |
work_keys_str_mv |
AT binshenqho datadriveninterdisciplinarymathematicalmodellingquantitativelyunveilscompetitiondynamicsofcocirculatinginfluenzastrains AT kunmaochao datadriveninterdisciplinarymathematicalmodellingquantitativelyunveilscompetitiondynamicsofcocirculatinginfluenzastrains |
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1725845439538790400 |