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The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China.
Zhao, Ze-Yu; Niu, Yan; Luo, Li; Hu, Qing-Qing; Yang, Tian-Long; Chu, Mei-Jie; Chen, Qiu-Ping; Lei, Zhao; Rui, Jia; Song, Cheng-Long; Lin, Sheng-Nan; Wang, Yao; Xu, Jing-Wen; Zhu, Yuan-Zhao; Liu, Xing-Chun; Yang, Meng; Huang, Jie-Feng; Liu, Wei-Kang; Deng, Bin; Liu, Chan; Li, Zhuo-Yang; Li, Pei-Hua; Su, Yan-Hua; Zhao, Ben-Hua; Huang, Wen-Long; Frutos, Roger; Chen, Tian-Mu.
Afiliação
  • Zhao ZY; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Niu Y; Cirad, UMR 17, Intertryp, Université de Montpellier, Montpellier, France.
  • Luo L; Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.
  • Hu QQ; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Yang TL; Division of Public Health, School of Medicine, University of Utah, Utah, USA.
  • Chu MJ; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Chen QP; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Lei Z; Cirad, UMR 17, Intertryp, Université de Montpellier, Montpellier, France.
  • Rui J; Medical Insurance Office, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, People's Republic of China.
  • Song CL; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Lin SN; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Wang Y; Department of Data Science, College of Natural Sciences, Colorado State University, Fort Collins, CO, USA.
  • Xu JW; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Zhu YZ; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Liu XC; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Yang M; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Huang JF; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Liu WK; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Deng B; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Liu C; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Li ZY; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Li PH; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Su YH; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Zhao BH; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Huang WL; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Frutos R; State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 4221-117 South Xiang'an Road, Xiang'an District, Xiamen, 361102, Fujian, People's Republic of China.
  • Chen TM; Fujian Provincial Center for Disease Control and Prevention, 76 Jintai Road, Gulou District, Fuzhou, Fujian, People's Republic of China. 497528061@qq.com.
Infect Dis Poverty ; 10(1): 140, 2021 Dec 28.
Article em En | MEDLINE | ID: mdl-34963481
BACKGROUND: Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. METHODS: We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (Reff) was used to estimate the transmission interaction in different age groups. RESULTS: A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (Reff = 4.28), followed by group 2 to 3 (Reff = 2.61), and group 2 to 4 (Reff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45-64 years old. CONCLUSIONS: Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15-64 years should first be vaccinated to prevent transmission in China.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Limite: Adolescent / Adult / Aged / Humans / Middle aged País/Região como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Limite: Adolescent / Adult / Aged / Humans / Middle aged País/Região como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article