Literature DB >> 19568726

Transmission dynamics of an influenza model with vaccination and antiviral treatment.

Zhipeng Qiu1, Zhilan Feng.   

Abstract

Vaccination and antiviral treatment are two important prevention and control measures for the spread of influenza. However, the benefit of antiviral use can be compromised if drug-resistant strains arise. In this paper, we develop a mathematical model to explore the impact of vaccination and antiviral treatment on the transmission dynamics of influenza. The model includes both drug-sensitive and resistant strains. Analytical results of the model show that the quantities R(SC) and R(RC), which represent the control reproduction numbers of the sensitive and resistant strains, respectively, provide threshold conditions that determine the competitive outcomes of the two strains. These threshold conditions can be used to gain important insights into the effect of vaccination and treatment on the prevention and control of influenza. Numerical simulations are also conducted to confirm and extend the analytic results. The findings imply that higher levels of treatment may lead to an increase of epidemic size, and the extent to which this occurs depends on other factors such as the rates of vaccination and resistance development. This suggests that antiviral treatment should be implemented appropriately.

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Year:  2009        PMID: 19568726     DOI: 10.1007/s11538-009-9435-5

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  11 in total

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5.  Assessment of intensive vaccination and antiviral treatment in 2009 influenza pandemic in Korea.

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Journal:  Osong Public Health Res Perspect       Date:  2014-12-24

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7.  Doing mathematics with aftermath of pandemic influenza 2009.

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8.  Analysis and Numerical Simulations of a Stochastic SEIQR Epidemic System with Quarantine-Adjusted Incidence and Imperfect Vaccination.

Authors:  Fei Li; Xinzhu Meng; Xinzeng Wang
Journal:  Comput Math Methods Med       Date:  2018-02-20       Impact factor: 2.238

9.  An agent-based model simulation of influenza interactions at the host level: insight into the influenza-related burden of pneumococcal infections.

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Journal:  BMC Infect Dis       Date:  2017-06-02       Impact factor: 3.090

10.  Optimizing treatment regimes to hinder antiviral resistance in influenza across time scales.

Authors:  Oscar Patterson-Lomba; Benjamin M Althouse; Georg M Goerg; Laurent Hébert-Dufresne
Journal:  PLoS One       Date:  2013-03-29       Impact factor: 3.240

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