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.
KW - Age-specific contact patterns
KW - Epidemic model
KW - Next-generation matrix
KW - Vaccination allocation strategy
UR - http://www.scopus.com/inward/record.url?scp=85182522658&partnerID=8YFLogxK
U2 - 10.1109/WI-IAT59888.2023.00094
DO - 10.1109/WI-IAT59888.2023.00094
M3 - Conference proceeding
AN - SCOPUS:85182522658
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
ER -
