Evidence map›Paper›PMID 36483256›Full record

ArticleFrontiers in public health2022

Dynamic characteristics of a COVID-19 outbreak in Nanjing, Jiangsu province, China.

Junjun Wang, Tao Ma, Songning Ding, Ke Xu, Min Zhang, Zhong Zhang, Qigang Dai, Shilong Tao, Hengxue Wang, Xiaoqing Cheng and 16 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 3 pooled it
–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

7 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Evolution of COVID-19 dynamics in Guangdong Province, China: an endemic-epidemic modeling study.Archives of public health = Archives belges de sante publique · 2024
    Article
  5. Article
  6. Article
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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

26 authors.

Junjun WangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Tao MaDepartment of Acute Infectious Diseases Control and Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Songning DingDepartment of Acute Infectious Diseases Control and Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Ke XuDepartment of Acute Infectious Diseases Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Min ZhangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Zhong ZhangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Qigang DaiDepartment of Acute Infectious Diseases Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Shilong TaoJiangning District Center for Disease Control and Prevention, Nanjing, China.
Hengxue WangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Xiaoqing ChengChinese Field Epidemiology Training Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Min HeNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Xuefei DuNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Zhi FengJiangning District Center for Disease Control and Prevention, Nanjing, China.
Huafeng YangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Rong WangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Chaoyong XieNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Yuanyuan XuNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Li LiuNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Xupeng ChenNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Chen LiNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Wen WuNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Sheng YeNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Sheng YangNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Huafeng FanNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Nan ZhouNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.
Jie DingNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.617.2 (also named the Delta variant) was declared as a variant of concern by the World Health Organization (WHO). This study aimed to describe the outbreak that occurred in Nanjing city triggered by the Delta variant through the epidemiological parameters and to understand the evolving epidemiology of the Delta variant. Methods: We collected the data of all COVID-19 cases during the outbreak from 20 July 2021 to 24 August 2021 and estimated the distribution of serial interval, basic and time-dependent reproduction numbers (R Results: A total of 235 cases have been confirmed. The mean value of serial interval was estimated to be 4.79 days with the Weibull distribution. The R Conclusions: The Delta variant is more aggressive and transmissible than the original virus types, so continuous non-pharmaceutical interventions are still needed.

Indexed as

COVID-19SARS-CoV-2Bayes TheoremChinaHumansB.1.617.2 (Delta) variantcoronavirus disease 2019 (COVID-19)reproduction numberSARS-CoV-2serial intervaltransmissibility

Identifiers

PMID36483256
PMCPMC9723226

What OpenQuestion holds

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LicenceCC BY
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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.