Evidence map›Paper›PMID 34812380›Full record

ArticleIEEE access : practical innovations, open solutions2021

Spatiotemporal Differences of COVID-19 Infection Among Healthcare Workers and Patients in China From January to March 2020.

Peixiao Wang, Xinyan Zhu, Wei Guo, Hui Ren, Tao Hu

Open access · goldAbstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2021. 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
0.2field-weighted citation impact, top 56% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

5 authors at 2 institutions in 2 countries.

Peixiao WangState Key Laboratory of Information Engineering in SurveyingMapping and Remote Sensing, Wuhan University Wuhan 430079 China.
Xinyan ZhuState Key Laboratory of Information Engineering in SurveyingMapping and Remote Sensing, Wuhan University Wuhan 430079 China.
Wei GuoState Key Laboratory of Information Engineering in SurveyingMapping and Remote Sensing, Wuhan University Wuhan 430079 China.
Hui RenState Key Laboratory of Information Engineering in SurveyingMapping and Remote Sensing, Wuhan University Wuhan 430079 China.
Tao HuCenter for Geographic AnalysisHarvard University Cambridge MA 02138 USA.
Wuhan University · CNHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studying the spatiotemporal differences in coronavirus disease (COVID-19) between social groups such as healthcare workers (HCWs) and patients can aid in formulating epidemic containment policies. Most previous studies of the spatiotemporal characteristics of COVID-19 were conducted in a single group and did not explore the differences between groups. To fill this research gap, this study assessed the spatiotemporal characteristics and differences among patients and HCWs infection in Wuhan, Hubei (excluding Wuhan), and China (excluding Hubei). The temporal difference was greater in Wuhan than in the rest of Hubei, and was greater in Hubei (excluding Wuhan) than in the rest of China. The incidence was high in healthcare workers in the early stages of the epidemic. Therefore, it is important to strengthen the protective measures for healthcare workers in the early stage of the epidemic. The spatial difference was less in Wuhan than in the rest of Hubei, and less in Hubei (excluding Wuhan) than in the rest of China. The spatial distribution of healthcare worker infections can be used to infer the spatial distribution of the epidemic in the early stage and to formulate control measures accordingly.

Indexed as

COVID-19Healthcare worker infectionpatient infectionspatiotemporal differencesspatiotemporal distribution

Identifiers

PMID34812380
PMCPMC8545239
OpenAlexW3126150366

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.