Evidence map›Paper›PMID 37780420›Full record

ArticleFrontiers in public health2023

Epidemiological and clinical characteristics of COVID-19 reinfection during the epidemic period in Yangzhou city, Jiangsu province.

Yin Wang, Jie Liang, Huimin Yang, Liguo Zhu, Jianli Hu, Lishun Xiao, Yao Huang, Yuying Dong, Cheng Wu, Jun Zhang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

11 authors at 3 institutions in 1 country.

Yin Wang *Yangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Jie Liang *Yangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Huimin Yang *Yangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Liguo ZhuJiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China.
Jianli HuJiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China.
Lishun XiaoDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Yao HuangYangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Yuying DongYangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Cheng WuYangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Jun ZhangYangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Xin ZhouYangzhou Center for Disease Control and Prevention, Yangzhou, Jiangsu, China.
Yangzhou University · CNJiangsu Provincial Center for Disease Control and Prevention · CNXuzhou Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the continuous progress of the epidemic of coronavirus disease 2019 (COVID-19) infection and the constant mutation of the virus strain, reinfection occurred in previously infected individuals and caused waves of the epidemic in many countries. Therefore, we aimed to explore the characteristics of COVID-19 reinfection during the epidemic period in Yangzhou and provide a scientific basis for assessing the COVID-19 situation and optimizing the allocation of medical resources. Methods: We chose previously infected individuals of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reported locally in Yangzhou city from January 2020 to November 30, 2022. A telephone follow-up of cases was conducted from February to March 2023 to collect the COVID-19 reinfection information. We conducted a face-to-face survey on that who met the definition of reinfection to collect information on clinical symptoms, vaccination status of COVID-19, and so on. Data were analyzed using SPSS 19.0. Results: Among the 999 eligible respondents (92.24% of all the participants), consisting of 42.28% males and 57.72% females, the reinfection incidence of females was significantly higher than that of male cases (χ Conclusion: After the epidemic period of COVID-19, the reinfection incidence varied with different types of SARS-CoV-2 strains. The reinfection incidence was influenced by various factors such as virus characteristics, vaccination, epidemic prevention policies, and individual variations. As the SARS-CoV-2 continues to mutate, vaccination and appropriate personal protection have practical significance in reducing the risk of reinfection.

Indexed as

COVID-19AdultCOVID-19 VaccinesFemaleHumansMaleReinfectionSARS-CoV-2COVID-19 Vaccinesclinical characteristicsepidemicepidemiological characteristicsreinfectionSARS-CoV-2

Identifiers

PMID37780420
PMCPMC10535086
OpenAlexW4386698107

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.