| Literature DB >> 35570977 |
Yu Zhang1, Man Hu2, Junwu Wang1, Pingchuan Wang1, Pengzhi Shi2, Wenjie Zhao2, Xin Liu1, Qing Peng1, Bo Meng2, Xinmin Feng1, Liang Zhang1.
Abstract
COVID-19, which occurred at the end of December 2019, has evolved into a global public health threat and affects every aspect of human life. COVID-19's high infectivity and mortality prompted governments and the scientific community to respond quickly to the pandemic outbreak. The application of personal protective equipment (PPE) is of great significance in overcoming the epidemic situation. Since the discovery of severe acute respiratory coronavirus 2 (SARS-CoV-2), bibliometric analysis has been widely used in many aspects of the COVID-19 epidemic. Although there are many reported studies about PPE and COVID-19, there is no study on the bibliometric analysis of these studies. The citation can be used as an indicator of the scientific influence of an article in its field. The aim of this study was to track the research trends and latest hotspots of COVID-19 in PPE by means of bibliometrics and visualization maps.Entities:
Keywords: COVID-19; VOSviewer; bibliometric; personal protective equipment; transmission
Mesh:
Year: 2022 PMID: 35570977 PMCID: PMC9099374 DOI: 10.3389/fpubh.2022.855633
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Distribution of included publications by document type in COVID-19 and PPE.
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| 1 | Article | 778 | 53.2 | 741 | 6,240 |
| 2 | Letter | 301 | 20.6 | 420 | 2,874 |
| 3 | Editorial Material | 189 | 12.9 | 324 | 3,039 |
| 4 | Review | 106 | 7.3 | 271 | 1,991 |
| 5 | Article; Early Access | 67 | 4.6 | 0 | 50 |
| 6 | Editorial Material; Early Access | 8 | 0.5 | 0 | 2 |
| 7 | Letter; Early Access | 8 | 0.5 | 0 | 2 |
| 8 | Review; Early Access | 5 | 0.3 | 0 | 1 |
PPE, personal protective equipment; TLCS, total local citation score; TGCS, total global citation score.
Top-10 most prolific authors in COVID-19 and PPE.
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| 1 | Macintyre CR | 9 | 0.13 | 8 | 288 |
| 2 | Szarpak L | 8 | 0.11 | 12 | 45 |
| 3 | Bialynicki BR | 7 | 0.10 | 2 | 55 |
| 4 | Chou R | 7 | 0.10 | 25 | 60 |
| 5 | Li J | 7 | 0.10 | 5 | 32 |
| 6 | Smereka J | 7 | 0.10 | 12 | 55 |
| 7 | Dana T | 6 | 0.09 | 25 | 60 |
| 8 | Filipiak KJ | 6 | 0.09 | 12 | 45 |
| 9 | Hamzavi IH | 6 | 0.09 | 24 | 112 |
| 10 | Jungbauer R | 6 | 0.09 | 25 | 60 |
PPE, personal protective equipment; TLCS, total local citation score; TGCS, total global citation score.
Top-10 most productive countries in COVID-19 and PPE.
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| 1 | USA | 463 | 31.7 | 575 | 5,103 |
| 2 | China | 162 | 11.1 | 429 | 2,835 |
| 3 | England | 137 | 9.4 | 278 | 2,086 |
| 4 | India | 107 | 7.3 | 43 | 349 |
| 5 | Italy | 89 | 6.1 | 90 | 705 |
| 6 | Canada | 87 | 6.0 | 254 | 1,513 |
| 7 | Australia | 66 | 4.5 | 51 | 675 |
| 8 | Germany | 47 | 3.2 | 78 | 357 |
| 9 | Japan | 47 | 3.2 | 15 | 226 |
| 10 | Spain | 46 | 3.1 | 17 | 286 |
PPE, personal protective equipment; TLCS, total local citation score; TGCS, total global citation score.
Top-10 leading journals in COVID-19 and PPE.
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| 1 | Plos ONE | 34 | 2.3 | 0 | 258 | 3.24 | 1 |
| 2 | International Journal of Environmental Research and Public Health | 30 | 2.1 | 0 | 207 | 3.39 | 2 |
| 3 | Infection Control and Hospital Epidemiology | 26 | 1.8 | 10 | 185 | 3.25 | 2 |
| 4 | BMJ-British Medical Journal | 21 | 1.4 | 0 | 425 | 39.89 | 1 |
| 5 | Journal of Hospital Infection | 21 | 1.4 | 63 | 298 | 3.93 | 1 |
| 6 | Annals of Internal Medicine | 18 | 1.2 | 87 | 286 | 25.39 | 1 |
| 7 | American Journal of Infection Control | 17 | 1.2 | 18 | 90 | 2.92 | 1 |
| 8 | Science of The Total Environment | 16 | 1.1 | 0 | 420 | 7.96 | 1 |
| 9 | Journal of The European Academy of Dermatology and Venereology | 15 | 1.0 | 31 | 113 | 6.17 | 1 |
| 10 | Scientific Reports | 12 | 0.8 | 0 | 34 | 4.38 | 1 |
PPE, personal protective equipment; TLCS, total local citation score; TGCS, total global citation score; IF impact factor.
Top-10 frequently used words in COVID-19 and PPE.
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| 1 | COVID | 1,235 | 38.5 | 1,351 | 10,836 |
| 2 | Pandemic | 576 | 17.9 | 583 | 4,924 |
| 3 | Mask | 464 | 14.5 | 443 | 3,446 |
| 4 | Masks | 423 | 13.2 | 736 | 4,859 |
| 5 | Protective | 420 | 13.1 | 394 | 4,731 |
| 6 | Personal | 400 | 12.5 | 379 | 4,672 |
| 7 | Face | 397 | 12.4 | 687 | 5,078 |
| 8 | Equipment | 394 | 12.3 | 369 | 4,629 |
| 9 | Use | 226 | 7.0 | 378 | 2,500 |
| 10 | SARS | 160 | 5.0 | 582 | 3,782 |
PPE, personal protective equipment; TLCS, total local citation score; TGCS, total global citation score.
Top-10 most prolific institutions in COVID-19 and PPE.
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| 1 | Univ Toronto | 30 | 26 | 224 |
| 2 | Harvard Med Sch | 27 | 17 | 255 |
| 3 | Univ Hong Kong | 22 | 251 | 1,098 |
| 4 | Univ Milan | 17 | 23 | 154 |
| 5 | Oregon Hlth and Sci Univ | 16 | 32 | 766 |
| 6 | Univ Penn | 16 | 37 | 246 |
| 7 | Wroclaw Med Univ | 16 | 20 | 136 |
| 8 | All India Inst Med Sci | 15 | 1 | 31 |
| 9 | Stanford Univ | 15 | 1 | 146 |
| 10 | Johns Hopkins Univ | 14 | 0 | 143 |
PPE, personal protective equipment; TLCS, total local citation score; TGCS, total global citation score.
Figure 1Network visualization map of co-authorship country. A minimum of five documents per country was fixed. Of the 94 countries, only 55 meet the threshold. The size of the circle represents the number of articles published by the country, and the larger the circle, the higher the country's contribution to co-authorship. The more connections between the two countries, the stronger cooperation exists between the two countries.
Figure 2Network visualization map of keyword analysis. The co-occurrence network analysis tool was used to set the minimum number of occurrences to 18. Of the 3,061 keywords, 41 met the threshold. The larger the circle was, the words were used more frequently. Forty-one keywords classified in major four clusters.
Figure 3Visualization mapping of co-citation cited sources. (A) Network visualization map; (B) density visualization map. A minimum number of citations of a source: 200. Of the 11,711 sources, 20 sources met the threshold. For each of the 20 sources, the TLS with other sources was calculated. The sources with the greatest TLS were selected.
Figure 4Network visualization map of co-authorship institutions. A minimum of five documents per organization was fixed. Of the 2,403 institutions, 116 meet the threshold.