The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China

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.

Bibliographic Details

Main Authors:	Zhao, Zeyu, Niu, Yan, Luo, Li, Hu, Qingqing, Yang, Tian-Long, Chu, Meijie, Chen, Qiuping, 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, Weikang, Deng, Bin, Liu, Chan, Li, Zhuo-Yang, Li, Pei-hua, Su, Yanhua, Zhao, Benhua, Huang, Wen-long, Frutos, Roger, Chen, Tianmu
Format:	article biblioteca
Language:	eng
Subjects:	transmission des maladies, contrôle de maladies, modèle de simulation, vaccination, covid-19, épidémiologie, vaccin, pandémie, résistance aux maladies, santé publique, coronavirus 2 du syndrome respiratoire aigu sévère, modèle mathématique, facteur de risque, modélisation, http://aims.fao.org/aos/agrovoc/c_2329, http://aims.fao.org/aos/agrovoc/c_2327, http://aims.fao.org/aos/agrovoc/c_24242, http://aims.fao.org/aos/agrovoc/c_15123, http://aims.fao.org/aos/agrovoc/c_4ad07701, http://aims.fao.org/aos/agrovoc/c_2615, http://aims.fao.org/aos/agrovoc/c_8130, http://aims.fao.org/aos/agrovoc/c_f17550ed, http://aims.fao.org/aos/agrovoc/c_2328, http://aims.fao.org/aos/agrovoc/c_6349, http://aims.fao.org/aos/agrovoc/c_365a18ab, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_32668, http://aims.fao.org/aos/agrovoc/c_230ab86c, http://aims.fao.org/aos/agrovoc/c_1556,
Online Access:	http://agritrop.cirad.fr/605913/ http://agritrop.cirad.fr/605913/1/ID605913.pdf
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