Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections

Aibin Tang; Yineng Gao; Miao Liu; Yue Peng; Jiming Liu; Benyun Shi

doi:10.1109/WI-IAT59888.2023.00094

Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections

Aibin Tang, Yineng Gao, Miao Liu, Yue Peng, Jiming Liu, Benyun Shi^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

This study investigates the role of mass vaccination in mitigating the impact of infectious diseases, with a focus on the often-overlooked issue of asymptomatic carriers among vaccinated individuals. To accurately capture the occurrence of asymptomatic infections after vaccination, we propose a SEIAQ model that incorporates age-specific contact patterns in a population. Using census data from Shanghai, China, we simulate the potential transmission of the disease in an age-specific structured population. In light of potential constraints on vaccine coverage during the early stages of an epidemic, we also propose a vaccine allocation strategy that prioritizes different age groups based on the next-generation matrix concept. Our simulation results demonstrate that this strategy significantly reduces overall infections and the proportion of symptomatic infections. These findings highlight the effectiveness of the proposed strategy in containing disease spread, particularly when the vaccine may not fully prevent asymptomatic infections.

Original language	English
Title of host publication	Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023
Editors	Javier Gurrola
Publisher	IEEE
Pages	569-575
Number of pages	7
ISBN (Electronic)	9798350309188
ISBN (Print)	9798350309195
DOIs	https://doi.org/10.1109/WI-IAT59888.2023.00094
Publication status	Published - 26 Oct 2023
Event	22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023 - Hybrid, Venice, Italy Duration: 26 Oct 2023 → 29 Oct 2023 https://ieeexplore.ieee.org/xpl/conhome/10350035/proceeding

Publication series

Name	IEEE WIC ACM International Conference on Web Intelligence (WI)
Publisher	IEEE

Conference

Conference	22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023
Country/Territory	Italy
City	Venice
Period	26/10/23 → 29/10/23
Internet address	https://ieeexplore.ieee.org/xpl/conhome/10350035/proceeding

User-Defined Keywords

Age-specific contact patterns
Epidemic model
Next-generation matrix
Vaccination allocation strategy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/WI-IAT59888.2023.00094

Cite this

Tang, A., Gao, Y., Liu, M., Peng, Y., Liu, J., & Shi, B. (2023). Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections. In J. Gurrola (Ed.), Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023 (pp. 569-575). (IEEE WIC ACM International Conference on Web Intelligence (WI) ). IEEE. https://doi.org/10.1109/WI-IAT59888.2023.00094

Tang, Aibin ; Gao, Yineng ; Liu, Miao et al. / Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections. Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023. editor / Javier Gurrola. IEEE, 2023. pp. 569-575 (IEEE WIC ACM International Conference on Web Intelligence (WI) ).

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title = "Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections",

abstract = "This study investigates the role of mass vaccination in mitigating the impact of infectious diseases, with a focus on the often-overlooked issue of asymptomatic carriers among vaccinated individuals. To accurately capture the occurrence of asymptomatic infections after vaccination, we propose a SEIAQ model that incorporates age-specific contact patterns in a population. Using census data from Shanghai, China, we simulate the potential transmission of the disease in an age-specific structured population. In light of potential constraints on vaccine coverage during the early stages of an epidemic, we also propose a vaccine allocation strategy that prioritizes different age groups based on the next-generation matrix concept. Our simulation results demonstrate that this strategy significantly reduces overall infections and the proportion of symptomatic infections. These findings highlight the effectiveness of the proposed strategy in containing disease spread, particularly when the vaccine may not fully prevent asymptomatic infections.",

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author = "Aibin Tang and Yineng Gao and Miao Liu and Yue Peng and Jiming Liu and Benyun Shi",

note = "Funding Information: This work was supported in part by the NSFC/RGC Joint Research Scheme (No. 62261160387, N~HKBU222/22), the Ministry of Science and Technology of the People's Republic of China (2021ZD0112501, 2021ZD0112502), and the General Research Fund of Hong Kong (Nos. RGC/HKBU12202220 and RGC /HKBU12203122). Publisher Copyright: {\textcopyright} 2023 IEEE.; 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023 ; Conference date: 26-10-2023 Through 29-10-2023",

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Tang, A, Gao, Y, Liu, M, Peng, Y, Liu, J & Shi, B 2023, Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections. in J Gurrola (ed.), Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023. IEEE WIC ACM International Conference on Web Intelligence (WI) , IEEE, pp. 569-575, 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023, Venice, Italy, 26/10/23. https://doi.org/10.1109/WI-IAT59888.2023.00094

Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections. / Tang, Aibin; Gao, Yineng; Liu, Miao et al.
Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023. ed. / Javier Gurrola. IEEE, 2023. p. 569-575 (IEEE WIC ACM International Conference on Web Intelligence (WI) ).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections

AU - Tang, Aibin

AU - Gao, Yineng

AU - Liu, Miao

AU - Peng, Yue

AU - Liu, Jiming

AU - Shi, Benyun

N1 - Funding Information: This work was supported in part by the NSFC/RGC Joint Research Scheme (No. 62261160387, N~HKBU222/22), the Ministry of Science and Technology of the People's Republic of China (2021ZD0112501, 2021ZD0112502), and the General Research Fund of Hong Kong (Nos. RGC/HKBU12202220 and RGC /HKBU12203122). Publisher Copyright: © 2023 IEEE.

PY - 2023/10/26

Y1 - 2023/10/26

N2 - This study investigates the role of mass vaccination in mitigating the impact of infectious diseases, with a focus on the often-overlooked issue of asymptomatic carriers among vaccinated individuals. To accurately capture the occurrence of asymptomatic infections after vaccination, we propose a SEIAQ model that incorporates age-specific contact patterns in a population. Using census data from Shanghai, China, we simulate the potential transmission of the disease in an age-specific structured population. In light of potential constraints on vaccine coverage during the early stages of an epidemic, we also propose a vaccine allocation strategy that prioritizes different age groups based on the next-generation matrix concept. Our simulation results demonstrate that this strategy significantly reduces overall infections and the proportion of symptomatic infections. These findings highlight the effectiveness of the proposed strategy in containing disease spread, particularly when the vaccine may not fully prevent asymptomatic infections.

AB - This study investigates the role of mass vaccination in mitigating the impact of infectious diseases, with a focus on the often-overlooked issue of asymptomatic carriers among vaccinated individuals. To accurately capture the occurrence of asymptomatic infections after vaccination, we propose a SEIAQ model that incorporates age-specific contact patterns in a population. Using census data from Shanghai, China, we simulate the potential transmission of the disease in an age-specific structured population. In light of potential constraints on vaccine coverage during the early stages of an epidemic, we also propose a vaccine allocation strategy that prioritizes different age groups based on the next-generation matrix concept. Our simulation results demonstrate that this strategy significantly reduces overall infections and the proportion of symptomatic infections. These findings highlight the effectiveness of the proposed strategy in containing disease spread, particularly when the vaccine may not fully prevent asymptomatic infections.

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KW - Next-generation matrix

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SN - 9798350309195

T3 - IEEE WIC ACM International Conference on Web Intelligence (WI)

SP - 569

EP - 575

BT - Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023

A2 - Gurrola, Javier

PB - IEEE

T2 - 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023

Y2 - 26 October 2023 through 29 October 2023

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Tang A, Gao Y, Liu M, Peng Y, Liu J, Shi B. Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections. In Gurrola J, editor, Proceedings - 2023 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2023. IEEE. 2023. p. 569-575. (IEEE WIC ACM International Conference on Web Intelligence (WI) ). doi: 10.1109/WI-IAT59888.2023.00094

Vaccine Allocation Strategy for Addressing Vaccine-Induced Asymptomatic Infections

Abstract

Publication series

Conference

User-Defined Keywords

UN SDGs

Access to Document

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