Evidence map›Paper›PMID 37706095›Full record

ArticleInfectious Disease Modelling2023

COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China.

Fengying Wei, Ruiyang Zhou, Zhen Jin, Senzhong Huang, Zhihang Peng, Jinjie Wang, Ximing Xu, Xinyan Zhang, Jun Xu, Yao Bai and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Infectious Disease Modelling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Fengying WeiSchool of Mathematics and Statistics, Fuzhou University, Fuzhou, 350116, Fujian, China.
Ruiyang ZhouSchool of Mathematics and Statistics, Fuzhou University, Fuzhou, 350116, Fujian, China.
Zhen JinComplex Systems Research Center, Shanxi University, Taiyuan, 030006, Shanxi, China.
Senzhong HuangSchool of Statistics and Data Science, ZhiYing Research Center for Health Data, Nankai University, 300071, Tianjin, China.
Zhihang PengDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China.
Jinjie WangNankai Institute of Economics, Binhai Development Institute, Nankai University, Tianjin, 300071, China.
Ximing XuChildren's Hospital of Chongqing Medical University, Chongqing, 400010, China.
Xinyan ZhangJinzhou Center for Disease Control and Prevention, Jinzhou, 121000, Liaoning, China.
Jun XuSchool of Statistics and Data Science, Nankai University, Tianjin, 300071, China.
Yao BaiXi'an Center for Disease Control and Prevention, Xi'an, 710061, Shaanxi, China.
Xiaoli WangBeijing Center for Disease Control and Prevention, Beijing, 100013, China.
Bulai LuSuzhou Center for Disease Control and Prevention, Suzhou, 215004, Jiangsu, China.
Zhaojun WangSchool of Statistics and Data Science, Nankai University, Tianjin, 300071, China.
Jianguo XuState Key Laboratory of Communicable Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 symptomatic 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 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 successfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.

Indexed as

COVID-19Non-pharmaceutical interventionsShijiazhuang epidemicTransmission dynamicsWild strain

Identifiers

PMID37706095
PMCPMC10495604

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.