Evidence map›Paper›PMID 35601794›Full record

ArticleTransactions in GIS : TG2022

Assessing work resumption in hospitals during the COVID-19 epidemic in China using multiscale geographically weighted regression.

Bisong Hu, Qianqian Zhang, Vincent Tao, Jinfeng Wang, Hui Lin, Lijun Zuo, Yu Meng

Abstract read
In one paragraph

Article in Transactions in GIS : TG, 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

7 authors.

Bisong HuSchool of Geography and Environment Jiangxi Normal University Nanchang China.ORCID https://orcid.org/0000-0003-3875-8792
Qianqian ZhangSchool of Geography and Environment Jiangxi Normal University Nanchang China.
Vincent TaoWayz AI Technology Company Limited Shanghai China.
Jinfeng WangState Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China.
Hui LinSchool of Geography and Environment Jiangxi Normal University Nanchang China.
Lijun ZuoAerospace Information Research Institute Chinese Academy of Sciences Beijing China.
Yu MengAerospace Information Research Institute Chinese Academy of Sciences Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The resumption of work and production is one of the key issues during the novel coronavirus (COVID-19) post-epidemic phase. We used location-based service data of mobile devices to assess the work resumption of 22,098 hospitals in mainland China. The multiscale influences of the determinants on work resumption in hospitals, including medical-service capacity, human movement, and epidemic severity, were examined using the multiscale geographically weighted regression technique. This study provides a novel insight into the assessment of work resumption in hospitals and its determinants, and is flexible to be extended to evaluate the work resumption of other industries. The findings can introduce helpful information for other countries to implement the strategies of work recovery during the post-epidemic phase.

Identifiers

PMID35601794
PMCPMC9115367

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.