Data-driven interdisciplinary mathematical modelling quantitatively unveils competition dynamics of co-circulating influenza strains
Journal
Journal of Translational Medicine
Journal Volume
15
Journal Issue
1
Date Issued
2017
Author(s)
Ho, B.-S.
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. ? 2017 The Author(s).
Subjects
Influenza; Quantitative modelling; Strain competition; Transmission
SDGs
Other Subjects
influenza vaccine; oseltamivir; sialidase; adolescent; adult; Article; child; cladistics; controlled study; correlational study; data processing; drug resistance; gene mutation; human; infant; influenza A (H1N1); interdisciplinary research; intraspecific competition; mathematical model; middle aged; newborn; nonhuman; prevalence; quantitative analysis; seasonal variation; simulation; social aspect; Taiwan; virus gene; virus isolation; virus replication; virus strain; virus transmission; basic reproduction number; computer simulation; demography; influenza; Influenza A virus (H1N1); interdisciplinary education; physiology; preschool child; season; theoretical model; transmission; young adult; Adolescent; Adult; Basic Reproduction Number; Child; Child, Preschool; Computer Simulation; Demography; Humans; Infant; Infant, Newborn; Influenza A Virus, H1N1 Subtype; Influenza, Human; Interdisciplinary Studies; Middle Aged; Models, Theoretical; Seasons; Young Adult
Type
journal article