Evaluation of hepatitis B vaccination strategy based on age heterogeneity model

被引:1
作者
Cheng, Kedeng [1 ,2 ]
Xu, Chuanqing [2 ]
Guo, Songbai [2 ]
Zhao, Xiaoyu [3 ]
机构
[1] Beijing Univ Technol, Sch Math Stat & Mech, Beijing 100124, Peoples R China
[2] Beijing Univ Civil Engn & Architecture, Sch Sci, Beijing 102616, Peoples R China
[3] Shandong Univ, Sch Math, Jinan 250100, Peoples R China
基金
奥地利科学基金会;
关键词
Hepatitis B; Heterogeneity model; Sensitivity analysis; Cumulative cases; Vaccine immunization strategy; TRANSMISSION; DYNAMICS; VIRUS; INFECTION;
D O I
10.1007/s12190-025-02475-3
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
China is one of the countries with highest burden of hepatitis B in the world, the number of new infections each year is at a high level and increases year by year. The number of infections in people aged 15 years and older accounts for 97.5% of all cases. Vaccination is the most effective way of reducing the risk of disease transmission. It is essential to assess the role of vaccination or booster vaccination in adult populations. In this paper, the hepatitis B cases data in different age groups were analyzed, an age heterogeneous hepatitis B transmission dynamics model including multiple age groups and vaccination was established. Fitting the cumulative case data of hepatitis B and obtaining the model parameters. Sensitivity analysis of the basic reproduction number R0 shows that vaccination of the population aged 25-70 can significantly reduce the number of hepatitis B cases. Exploring the impact of different vaccination immunization strategies on the number of hepatitis B cases, we get that it is the most effective to vaccinate people aged 15-70, which can reduce the cumulative number of hepatitis B cases by about 60%. Only reducing the contact between people does not help to significantly reduce the number of hepatitis B cases, but vaccination helps to greatly reduce the number of hepatitis B cases.
引用
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页数:22
相关论文
共 47 条
[1]  
Anonymous, 2007, Morbidity and Mortality Weekly Report, V56, P441
[2]  
[Anonymous], 2016, Global Health Sector Strategy on Sexually Transmitted Infections 2016-2021'
[3]  
[Anonymous], About us
[4]   Stochastic Persistence, Extinction and Stationary Distribution in HTLV-I Infection Model with CTL Immune Response [J].
Bera, Sovan ;
Khajanchi, Subhas ;
Kar, Tapan Kumar .
QUALITATIVE THEORY OF DYNAMICAL SYSTEMS, 2024, 23 (SUPPL 1)
[5]   Dynamics of an HTLV-I infection model with delayed CTLs immune response [J].
Bera, Sovan ;
Khajanchi, Subhas ;
Roy, Tapan Kumar .
APPLIED MATHEMATICS AND COMPUTATION, 2022, 430
[6]   Stability analysis of fuzzy HTLV-I infection model: a dynamic approach [J].
Bera, Sovan ;
Khajanchi, Subhas ;
Roy, Tapan Kumar .
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING, 2023, 69 (01) :171-199
[7]  
Cao CL., 2010, Liver Doctor, V4, P17
[8]  
Chinese Center for Disease Control and Prevention, US
[9]   Influence of non-homogeneous mixing on final epidemic size in a meta-population model [J].
Cui, Jingan ;
Zhang, Yanan ;
Feng, Zhilan .
JOURNAL OF BIOLOGICAL DYNAMICS, 2019, 13 :31-46
[10]  
Das D.K., 2019, 2019 8 INT C MOD SIM, P1