Evidence map›Paper›PMID 37189135›Full record

ArticleInternational journal for equity in health2023

Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China.

Baoguo Shi, Yanjie Wang, Xiaodan Bai, Yongqiang Lai, Wenjing Xiang, Bing Wu, Qi Xia, Xinwei Liu, Ye Li

Open access · goldAbstract read
In one paragraph

Article in International journal for equity in health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. 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

9 authors at 2 institutions in 1 country.

Baoguo ShiDepartment of Economics, School of Economics, Minzu University of China, Beijing, China.
Yanjie WangDepartment of Economics, School of Economics, Minzu University of China, Beijing, China.
Xiaodan BaiDepartment of Economics, School of Economics, Minzu University of China, Beijing, China.
Yongqiang LaiResearch Center for Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, Heilongjiang, 150086, China.
Wenjing XiangDepartment of Economics, School of Economics, Minzu University of China, Beijing, China.
Bing WuResearch Center for Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, Heilongjiang, 150086, China.
Qi XiaResearch Center for Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, Heilongjiang, 150086, China.
Xinwei LiuResearch Center for Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, Heilongjiang, 150086, China.
Ye LiResearch Center for Health Policy and Management, School of Health Management, Harbin Medical University, Harbin, Heilongjiang, 150086, China. liye8459@163.com.
Harbin Medical University · CNMinzu University of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe transmission of 2019 novel coronavirus (COVID-19) has caused global panic in the past three years. Countries have learned an important lesson in the practice of responding to COVID-19 pandemic: timely and accurate diagnosis is critical. As an important technology of virus diagnosis, nucleic acid testing (NAT) is also widely used in the identification of other infectious diseases. However, geographic factors often constrain the provision of public health services such as NAT services, and the spatial nature of their resource allocation is a significant problem.

methodsWe used OLS, OLS-SAR, GWR, GWR-SAR, MGWR, and MGWR-SAR models to identify the determinants of spatial difference and spatial heterogeneity affecting NAT institutions in China.

resultsFirstly, we identify that the distribution of NAT institutions in China shows a clear spatial agglomeration, with an overall trend of increasing distribution from west to east. There is significant spatial heterogeneity in Chinese NAT institutions. Secondly, the MGWR-SAR model results show that city level, population density, number of tertiary hospitals and number of public health emergency outbreaks are important factors influencing the spatial heterogeneity of NAT institutions in China.

conclusionsTherefore, the government should allocate health resources rationally, optimise the spatial layout of testing facilities, and improve the ability to respond to public health emergencies. Meanwhile, third-party testing facilities need to focus on their role in the public health emergency response system as a market force to alleviate the inequitable allocation of health resources between regions. By taking these measures to prepare adequately for possible future public health emergencies.

Indexed as

COVID-19ChinaEmergenciesHumansPandemicsPublic HealthCOVID-19MGWR-SAR methodNucleic acid testing (NAT) institutionsSpatial heterogeneity

Identifiers

PMID37189135
PMCPMC10184634
OpenAlexW4376641362

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.