Literature DB >> 33676420

Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China.

Qinglong Zhao1, Yao Wang2, Meng Yang2, Meina Li3, Zeyu Zhao2, Xinrong Lu1, Bo Shen1, Bo Luan1, Yifei Zhao1, Bonan Cao1, Laishun Yao1, Benhua Zhao2, Yanhua Su4, Tianmu Chen5.   

Abstract

BACKGROUND: Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of measures to control the disease in Jilin Province, China.
METHODS: The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible-Exposed-Infectious-Asymptomatic-Recovered/Removed (SEIAR) model was developed to fit the data, and the effective reproduction number (Reff) was calculated at different stages in the province. Finally, the effectiveness of the measures was assessed.
RESULTS: A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit the reported data well (R2 = 0.593, P < 0.001). The Reff of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would have reached a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would have been 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus's spread.
CONCLUSIONS: COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proven effective; increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease.

Entities:  

Keywords:  COVID-19; Epidemic; Measures; Transmissibility

Year:  2021        PMID: 33676420     DOI: 10.1186/s12879-021-05936-9

Source DB:  PubMed          Journal:  BMC Infect Dis        ISSN: 1471-2334            Impact factor:   3.090


  5 in total

1.  Modelling the Emerging COVID-19 Epidemic and Estimating Intervention Effectiveness - Taiwan, China, 2021.

Authors:  Weikang Liu; Wenjing Ye; Zeyu Zhao; Chan Liu; Bin Deng; Li Luo; Jiefeng Huang; Yao Wang; Jia Rui; Benhua Zhao; Yanhua Su; Shenggen Wu; Kun Chen; Jianming Ou; Tianmu Chen
Journal:  China CDC Wkly       Date:  2021-08-20

2.  Modeling Cross-Regional Transmission and Assessing the Effectiveness of Restricting Inter-Regional Population Movements in Controlling COVID-19 - Xi'an City, Shaanxi Province, China, 2021.

Authors:  Tianlong Yang; Yao Wang; Nankun Liu; Guzainuer Abudurusuli; Shiting Yang; Shanshan Yu; Weikang Liu; Xuecheng Yin; Tianmu Chen
Journal:  China CDC Wkly       Date:  2022-08-05

Review 3.  Compartmental structures used in modeling COVID-19: a scoping review.

Authors:  Lingcai Kong; Mengwei Duan; Jin Shi; Jie Hong; Zhaorui Chang; Zhijie Zhang
Journal:  Infect Dis Poverty       Date:  2022-06-21       Impact factor: 10.485

4.  Computing R 0 of dynamic models by a definition-based method.

Authors:  Xiaohao Guo; Yichao Guo; Zeyu Zhao; Shiting Yang; Yanhua Su; Benhua Zhao; Tianmu Chen
Journal:  Infect Dis Model       Date:  2022-05-24

5.  Assessing the Impacts of Meteorological Factors on COVID-19 Pandemic Using Generalized Estimating Equations.

Authors:  Shengnan Lin; Jia Rui; Fang Xie; Meirong Zhan; Qiuping Chen; Bin Zhao; Yuanzhao Zhu; Zhuoyang Li; Bin Deng; Shanshan Yu; An Li; Yanshu Ke; Wenwen Zeng; Yanhua Su; Yi-Chen Chiang; Tianmu Chen
Journal:  Front Public Health       Date:  2022-07-01
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.