Evidence map›Paper›PMID 34986389›Full record

ArticleAmerican journal of infection control2022

Global analysis of the COVID-19 research landscape and scientific impact.

Ying Chen, Shixiang Chen, Bingxin Ma, Zhaoxia Duan, Jin Yang, Yulu Wang, Xiaojun Zhang, Yaqi Huang, Yanwen Zhang, Cuiyu Deng and 3 more

Abstract read
In one paragraph

Article in American journal of infection control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Ying ChenDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Shixiang ChenDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Bingxin MaDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Zhaoxia DuanDepartment of Surgery, Tianjin Shuige Hospital, Tianjin, China.
Jin YangDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Yulu WangDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Xiaojun ZhangDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Yaqi HuangDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Yanwen ZhangDepartment of Nursing, Tianjin Medical University, Tianjin, China.
Cuiyu DengDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Qi LuDepartment of Nursing, Tianjin Medical University, Tianjin, China. Electronic address: luqi8674866@hotmail.com.
Yaogang WangDepartment of Public Health, Tianjin Medical University, Tianjin, China. Electronic address: wyg@tmu.edu.cn.
Yue ZhaoDepartment of Nursing, Tianjin Medical University, Tianjin, China. Electronic address: yuezhao35@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo consider a 1-year time window of the coronavirus disease 2019 (COVID-19) crisis to integrate qualitative and quantitative data and provide an in-depth analysis of all COVID-19 publications from geographical, epidemiological and chronological perspectives.

methodsPublications on COVID-19 from December 1, 2019, to December 31, 2020 without document type limitations were extracted from the Web of Science database. Microsoft Excel 2016, GraphPad Prism 9, VOSviewer 1.6.15 and IBM SPSS 21.0 were used to analyze the global epidemiological publication landscape and its correlations, research hotspots around the world and the top 5 countries in terms of publications.

resultsA total of 51,317 documents were analyzed in the present study. The publication trend could be divided into an increasing output stage and an explosive output stage. There were positive correlations between monthly publications, confirmed cases and deaths. Research hotspots from the whole year, from individual quarters, and from the top 5 countries with the most publications were further identified.

conclusionsThe correlation analysis of publications indicated that confirmed cases and deaths were forces driving the scientific output, reflecting the growing trend to some extent. Moreover, the hotspot analysis provided valuable information for scientists, funders, policy and decision-makers to determine what areas should be their focus when faced with public health emergencies in the future.

Indexed as

COVID-19BibliometricsDatabases, FactualForecastingHumansPublic HealthBibliometricKeyword co-occurrencePandemicPublication trend

Identifiers

PMID34986389
PMCPMC8720495

What OpenQuestion holds

Textmetadata
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.