Evidence map›Paper›PMID 36002820›Full record

ArticleBMC health services research2022

An evaluation index system for regional mobile SARS-CoV-2 virus nucleic acid testing capacity in China: a modified Delphi consensus study.

Dong-Sheng Di, Jian-Li Zhang, Mu-Hong Wei, Hao-Long Zhou, Yuan Cui, Ru-Yi Zhang, Ye-Qing Tong, Jun-An Liu, Qi Wang

Abstract read
In one paragraph

Article in BMC health services research, 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

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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

9 authors.

Dong-Sheng DiMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Jian-Li ZhangMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Mu-Hong WeiMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Hao-Long ZhouMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Yuan CuiMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Ru-Yi ZhangMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Ye-Qing TongHubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, Hubei, China.
Jun-An LiuDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. lja10_11@163.com.
Qi WangMOE Key Lab of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. wangqi_tj@hust.edu.cn.

Funding

China Association for Science and Technology 20200608CG111315National Natural Science Foundation of China 81573235
6 · The paper itself

Abstract

backgroundLarge-scale detection has great potential to bring benefits for containing the COVID-19 epidemic and supporting the government in reopening economic activities. Evaluating the true regional mobile severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus nucleic acid testing capacity is essential to improve the overall fighting performance against this epidemic and maintain economic development. However, such a tool is not available in this issue. We aimed to establish an evaluation index system for assessing the regional mobile SARS-CoV-2 virus nucleic acid testing capacity and provide suggestions for improving the capacity level.

methodsThe initial version of the evaluation index system was identified based on massive literature and expert interviews. The Delphi method questionnaire was designed and 30 experts were consulted in two rounds of questionnaire to select and revise indexes at all three levels. The Analytic Hierarchy Process method was used to calculate the weight of indexes at all three levels.

resultsThe evaluation index system for assessing the regional mobile SARS-CoV-2 virus nucleic acid testing capacity, including 5 first-level indexes, 17 second-level indexes, and 90 third-level indexes. The response rates of questionnaires delivered in the two rounds of consultation were 100 and 96.7%. Furthermore, the authority coefficient of 30 experts was 0.71. Kendall's coordination coefficient differences were statistically significant (P < 0.001). The weighted values of capacity indexes were established at all levels according to the consistency test, demonstrating that 'Personnel team construction' (0.2046) came first amongst the five first-level indexes, followed by 'Laboratory performance building and maintenance' (0.2023), 'Emergency response guarantee' (0.1989), 'Information management system for nucleic acid testing resources' (0.1982) and 'Regional mobile nucleic acid testing emergency response system construction' (0.1959).

conclusionThe evaluation system for assessing the regional mobile SARS-CoV-2 virus nucleic acid testing capacity puts forward a specific, objective, and quantifiable evaluation criterion. The evaluation system can act as a tool for diversified subjects to find the weak links and loopholes. It also provides a measurable basis for authorities to improve nucleic acid testing capabilities.

Indexed as

COVID-19Nucleic AcidsChinaDelphi TechniqueHumansSARS-CoV-2Nucleic AcidsAnalytic hierarchy processDelphi methodNucleic acid testingTesting capacity evaluation

Identifiers

PMID36002820
PMCPMC9399982

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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.