TY - JOUR
T1 - Is subsidizing vaccination with hub agent priority policy really meaningful to suppress disease spreading?
AU - Tanaka, Masaki
AU - Tanimoto, Jun
N1 - Funding Information:
This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan, KAKENHI (grant no. JP 18K18924 ), SCAT (Support Center for Advanced Telecommunications Technology) Research Foundation, Kurata Grant , and Kakihara Foundation awarded to Professor 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:
This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan, KAKENHI(grant no. JP 18K18924), SCAT (Support Center for Advanced Telecommunications Technology) Research Foundation, Kurata Grant, and Kakihara Foundation awarded to Professor 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:
© 2019
PY - 2020/2/7
Y1 - 2020/2/7
N2 - A Multi Agent Simulation (MAS) model that joins evolutionary game theory with epidemiological dynamics is established. Various subsidy policies that encourage vaccination are evaluated quantitatively with the model. The underlying social network topology is based on a scale-free network. Individual subsidies for vaccinations can be directed to hub agents with priority, to efficiently suppress the overall social cost of a vaccination program. These hub agents are more likely to spread both knowledge about vaccination and the disease in question. Our comprehensive simulations showed that this intuitively appealing strategy cannot be effective if the vaccination cost is low and the vaccination budget is small. Thus, we find that the hub agent priority strategy is not always effective.
AB - A Multi Agent Simulation (MAS) model that joins evolutionary game theory with epidemiological dynamics is established. Various subsidy policies that encourage vaccination are evaluated quantitatively with the model. The underlying social network topology is based on a scale-free network. Individual subsidies for vaccinations can be directed to hub agents with priority, to efficiently suppress the overall social cost of a vaccination program. These hub agents are more likely to spread both knowledge about vaccination and the disease in question. Our comprehensive simulations showed that this intuitively appealing strategy cannot be effective if the vaccination cost is low and the vaccination budget is small. Thus, we find that the hub agent priority strategy is not always effective.
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U2 - 10.1016/j.jtbi.2019.110059
DO - 10.1016/j.jtbi.2019.110059
M3 - Article
C2 - 31678271
AN - SCOPUS:85074480080
SN - 0022-5193
VL - 486
JO - Journal of Theoretical Biology
JF - Journal of Theoretical Biology
M1 - 110059
ER -