@article{64cc4704d91640f9ad98706812f3ce98,
title = "Interplay between cost and effectiveness in influenza vaccine uptake: A vaccination game approach",
abstract = "Pre-emptive vaccination is regarded as one of the most protective measures to control influenza outbreak. There are mainly two types of influenza viruses-influenza A and B with several subtypes-that are commonly found to circulate among humans. The traditional trivalent (TIV) flu vaccine targets two strains of influenza A and one strain of influenza B. The quadrivalent (QIV) vaccine targets one extra B virus strain that ensures better protection against influenza; however, the use of QIV vaccine can be costly, hence impose an extra financial burden to society. This scenario might create a dilemma in choosing vaccine types at the individual level. This article endeavours to explain such a dilemma through the framework of a vaccination game, where individuals can opt for one of the three options: choose either of QIV or TIV vaccine or none. Our approach presumes a mean-field framework of a vaccination game in an infinite and well-mixed population, entangling the disease spreading process of influenza with the coevolution of two types of vaccination decision-making processes taking place before an epidemic season. We conduct a series of numerical simulations as an attempt to illustrate different scenarios. The framework has been validated by the so-called multi-agent simulation (MAS) approach.",
author = "{Rajib Arefin}, Md and Tanaka Masaki and {Ariful Kabir}, {K. M.} and Jun Tanimoto",
note = "Funding Information: This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan, KAKENHI (grant no. 18K18924), SCAT (Support Center for Advanced Telecommunications Technology) Research Foundation and Pfizer Health Research Foundation awarded to Prof. Tanimoto. Also, the computation was mainly carried out using the computer facilities at Research Institute for Information Technology, Kyushu University. We would like to express our gratitude to them. Funding Information: Data accessibility. All data of this research work have been generated from a series of numerical simulations. The source code (c++) of our numerical simulation has been uploaded as electronic supplementary material in the {\textquoteleft}File Upload{\textquoteright} section. Authors{\textquoteright} contributions. M.R.A. developed the model, performed numerical simulations, analysed results and drafted the manuscript. T.M. carried out the multi-agent simulation (MAS) approach to validate the model and critically revised the manuscript. K.M.A.K. assisted in model formulation, result analyses and critically revised the manuscript. J.T. helped designing the study, coordinated the study, also helped draft the manuscript. All authors gave final approval for publication and agree to be held accountable for the work performed therein. Competing interests. We declare we have no competing interests. Funding. This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan, KAKENHI (grant no. 18K18924), SCAT (Support Center for Advanced Telecommunications Technology) Research Foundation and Pfizer Health Research Foundation awarded to Prof. Tanimoto. Also, the computation was mainly carried out using the computer facilities at Research Institute for Information Technology, Kyushu University. We would like to express our gratitude to them. Publisher Copyright: {\textcopyright} 2019 The Author(s) Published by the Royal Society. All rights reserved.",
year = "2019",
month = dec,
day = "1",
doi = "10.1098/rspa.2019.0608",
language = "English",
volume = "475",
journal = "PROC. R. SOC. - A.",
issn = "0950-1207",
publisher = "Royal Society of London",
number = "2232",
}
