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author:

Wei, Fengying (Wei, Fengying.) [1] (Scholars:魏凤英) | Zhou, Ruiyang (Zhou, Ruiyang.) [2] | Jin, Zhen (Jin, Zhen.) [3] | Huang, Senzhong (Huang, Senzhong.) [4] | Peng, Zhihang (Peng, Zhihang.) [5] | Wang, Jinjie (Wang, Jinjie.) [6] | Xu, Ximing (Xu, Ximing.) [7] | Zhang, Xinyan (Zhang, Xinyan.) [8] | Xu, Jun (Xu, Jun.) [9] | Bai, Yao (Bai, Yao.) [10] | Wang, Xiaoli (Wang, Xiaoli.) [11] | Lu, Bulai (Lu, Bulai.) [12] | Wang, Zhaojun (Wang, Zhaojun.) [13] | Xu, Jianguo (Xu, Jianguo.) [14]

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ESCI CSCD

Abstract:

Background: A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination, host, and non-pharmaceutical interventions (NPIs). Herein, we investigated the epidemiological characteristics of all reported symp-tomatic cases by picking Shijiazhuang City, Hebei Province in Northern China as research objective. In addition, we established a with age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios. Methods: All reported symptomatic cases of Shijiazhuang epidemic (January 2-February 3, 2021) were investigated in our study. The cases were classified by gender, age group and location, the distributions were analyzed by epidemiological characteristics. Furthermore, the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios.Results: Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11, 2021, which was implemented with strong NPIs by local government and referred as baseline situation in this study. The research results showed that R0 under baseline situation ranged from 4.47 to 7.72, and Rt of Gaocheng Distinct took 3.72 with 95% confidence interval from 3.23 to 4.35 on January 9, the declining tendencies of Rt under baseline situation were kept till February 3, the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic. This indicated Shijiazhuang epidemic was under control on January 19. However, if the strong NPIs were kept, but remote isolation operated on January 11 was not implemented as of February 9, then the scale of Shijiazhuang epidemic reached 9482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases. The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over (short for G2) under risk-based strategies (Scenario A), 58,048 symptomatic cases for G2 under late quarantine strategies (Scenario B) and 207,124 symptomatic cases for G2 under late quarantine double risk strategies (Scenario C), and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29, 2021. Compared with baseline situation, the dates for controlling Rt below 1 under three scenarios were delayed 10 days.Conclusions: Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China. The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure. However we found that age group profile and NPIs played critical rules to suc-cessfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.(c) 2023 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keyword:

COVID-19 Non-pharmaceutical interventions Shijiazhuang epidemic Transmission dynamics Wild strain

Community:

  • [ 1 ] [Wei, Fengying]Fuzhou Univ, Sch Math & Stat, Fuzhou 350116, Fujian, Peoples R China
  • [ 2 ] [Zhou, Ruiyang]Fuzhou Univ, Sch Math & Stat, Fuzhou 350116, Fujian, Peoples R China
  • [ 3 ] [Wei, Fengying]Fuzhou Univ, Ctr Appl Math Fujian Prov, Fuzhou 350116, Fujian, Peoples R China
  • [ 4 ] [Wei, Fengying]Fuzhou Univ, Key Lab Operat Res & Control Univ Fujian, Fuzhou 350116, Fujian, Peoples R China
  • [ 5 ] [Jin, Zhen]Shanxi Univ, Complex Syst Res Ctr, Taiyuan 030006, Shanxi, Peoples R China
  • [ 6 ] [Huang, Senzhong]Nankai Univ, ZhiYing Res Ctr Hlth Data, Sch Stat & Data Sci, Tianjin 300071, Peoples R China
  • [ 7 ] [Peng, Zhihang]Nanjing Med Univ, Sch Publ Hlth, Dept Biostat, Nanjing 211166, Jiangsu, Peoples R China
  • [ 8 ] [Wang, Jinjie]Nankai Univ, Nankai Inst Econ, Binhai Dev Inst, Tianjin 300071, Peoples R China
  • [ 9 ] [Xu, Ximing]Chongqing Med Univ, Childrens Hosp, Chongqing 400010, Peoples R China
  • [ 10 ] [Zhang, Xinyan]Jinzhou Ctr Dis Control & Prevent, Jinzhou 121000, Liaoning, Peoples R China
  • [ 11 ] [Xu, Jun]Nankai Univ, Sch Stat & Data Sci, Tianjin 300071, Peoples R China
  • [ 12 ] [Wang, Zhaojun]Nankai Univ, Sch Stat & Data Sci, Tianjin 300071, Peoples R China
  • [ 13 ] [Bai, Yao]Xian Ctr Dis Control & Prevent, Xian, Shaanxi, Peoples R China
  • [ 14 ] [Wang, Xiaoli]Beijing Ctr Dis Control & Prevent, Beijing 100013, Peoples R China
  • [ 15 ] [Lu, Bulai]Suzhou Ctr Dis Control & Prevent, Suzhou 215004, Jiangsu, Peoples R China
  • [ 16 ] [Xu, Jianguo]Chinese Ctr Dis Control & Prevent, Natl Inst Communicable Dis Control & Prevent, State Key Lab Communicable Dis Prevent & Control, Beijing 102206, Peoples R China
  • [ 17 ] [Xu, Jianguo]Nankai Univ, Inst Publ Hlth, Tianjin 300071, Peoples R China

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Source :

INFECTIOUS DISEASE MODELLING

ISSN: 2468-0427

Year: 2023

Issue: 4

Volume: 8

Page: 1050-1062

3 . 0

JCR@2023

3 . 0 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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