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LitCovid-sentences  

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Id Subject Object Predicate Lexical cue
T1 0-78 Sentence denotes The Productivity of Medical Publication on COVID-19 in the First Half of 2020:
T2 79-135 Sentence denotes A Retrospective Analysis of Articles Available in PubMed
T3 137-145 Sentence denotes Abstract
T4 146-156 Sentence denotes Background
T5 157-301 Sentence denotes The control of the coronavirus disease 2019 (COVID-19) pandemic depends on the profound investigation of the virus biology and its consequences.
T6 302-469 Sentence denotes We aimed to analyze the COVID-19 research productivity of authors representing different countries and associations between the number of articles and COVID-19 spread.
T7 470-477 Sentence denotes Methods
T8 478-576 Sentence denotes We retrieved all articles on COVID-19 indexed in PubMed between 31 December 2019 and 30 June 2020.
T9 577-641 Sentence denotes We identified the countries of individual authors’ affiliations.
T10 642-905 Sentence denotes We performed the R Spearman rank correlation test between the number of articles with at least one author from a country per one million citizens and Human Development Index (HDI), a number of COVID-19 cases and deaths per one million citizens before 1 July 2020.
T11 906-913 Sentence denotes Results
T12 914-1105 Sentence denotes Overall, we identified 27,815 articles, including 18,225 original contributions, 2,449 reviews, and 69 meta-analyses on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.
T13 1106-1298 Sentence denotes The highest productivity characterized the authors coming from China (n = 11,519 articles with at least one author), followed by the United States of America (n = 9,666) and Italy (n = 7,261).
T14 1299-1440 Sentence denotes The number of articles on COVID-19 associated with HDI (Rs = 0.79), the numbers of cases (Rs = 0.47), and deaths (Rs = 0.46) (all p < 0.001).
T15 1441-1452 Sentence denotes Conclusions
T16 1453-1612 Sentence denotes Early COVID-19 researches were most often authored by researchers from highly developed countries and those affected by the rapid initial spread of SARS-CoV-2.
T17 1614-1626 Sentence denotes Introduction
T18 1627-1748 Sentence denotes Coronavirus disease 2019 (COVID-19) pandemic is a novel public health emergency, activating the global healthcare system.
T19 1749-1878 Sentence denotes The control of the pandemic and treatment of people affected depends on deep understanding of the infection's biology and course.
T20 1879-2023 Sentence denotes Since the first reports of pneumonia of unknown origin in Wuhan [1], numerous researchers started investigations on the novel etiological agent.
T21 2024-2128 Sentence denotes Currently, over half a year has passed since the pandemic was declared by the World Health Organization.
T22 2129-2216 Sentence denotes There is little knowledge on the productivity of medical researches during this period.
T23 2217-2292 Sentence denotes Herein, we describe the sources of the outpour of publications on COVID-19.
T24 2293-2463 Sentence denotes The scientific productivity in the early stages of a public health emergency may reflect the health institutions’ adaptability and indicate areas of focus for the future.
T25 2464-2610 Sentence denotes We hypothesized that the analysis may reveal which countries lead in the investigations on the virus and indicate the main directions of research.
T26 2611-2871 Sentence denotes We aimed to analyze articles on COVID-19 available via PubMed in the first half of 2020 in order to (1) compare scientific productivity of authors representing different countries and (2) explore associations between the number of articles and COVID-19 spread.
T27 2873-2894 Sentence denotes Materials and methods
T28 2895-3054 Sentence denotes Data collection, manipulation, calculations, and visualization were performed using the R (version 3.6.3) programming language (R Foundation, Vienna, Austria).
T29 3055-3165 Sentence denotes We collected data on COVID-19 publications using the R PubMed API called "easyPubMed" on 9th of July 2020 [2].
T30 3166-3460 Sentence denotes We set the following query conditions: date between the 31st of December 2019 and 30th of June 2020, and search terms: "novel coronavirus," "coronavirus Wuhan," "SARS-CoV-2," "COVID-19." We identified articles with or without abstract, original articles, reviews, meta-analyses, and guidelines.
T31 3461-3563 Sentence denotes We ranked countries based on the number of articles with at least one author coming from each country.
T32 3564-3748 Sentence denotes We confronted the ranking of countries with the highest number of articles on COVID-19 with SCImago ranking of countries with the highest medical researchers' productivity in 2019 [3].
T33 3749-3858 Sentence denotes Moreover, we conducted the Spearman rank correlation test between the number of articles in each country and:
T34 3859-3955 Sentence denotes (a) the total number of COVID-19 cases per one million citizens before the 1st of July 2020 [4],
T35 3956-4068 Sentence denotes (b) the total number of deaths related to COVID-19 per one million citizens before the 1st of July 2020 [5], and
T36 4069-4116 Sentence denotes (c) Human Development Index (HDI) for 2018 [6].
T37 4117-4327 Sentence denotes We choose the R Spearman correlation rank test because the data we analyzed is presented in interval scale (e.g., HDI is an artificial index, and similarly like BMI, non-parametrical tests should be preferred).
T38 4328-4427 Sentence denotes Our data also had many outliers, which is other indication of Spearman correlation rank usefulness.
T39 4428-4541 Sentence denotes We matched journal names with the SCImago journal database that contains information on the journal category [7].
T40 4542-4832 Sentence denotes For instance, "The Lancet Infectious Diseases" is categorized as "Infectious Diseases" journal, while "Clinical Microbiology Reviews" as one of the following: "Epidemiology," "Infectious Diseases," "Microbiology (medical)," or "Public Health, Environmental and Occupational Health" journal.
T41 4833-4974 Sentence denotes We counted the number of reports on COVID-19 in journals from each category and presented categories with the highest number of publications.
T42 4976-4983 Sentence denotes Results
T43 4984-5076 Sentence denotes In the first half of 2020, the total number of articles published on PubMed equaled 858,641.
T44 5077-5185 Sentence denotes Overall, we identified 27,815 articles on COVID-19, which constitutes 3.24% of all publication in this time.
T45 5186-5341 Sentence denotes Among those we found 18,225 (65.52%) original articles, 2,449 (8.8%) reviews, 69 (0.25%) systematic reviews with meta-analysis, and 171 (0.61%) guidelines.
T46 5342-5448 Sentence denotes The remaining 6,901 (24.81%) positions were letters to the editors, commentaries, errata, or unclassified.
T47 5449-5668 Sentence denotes In a per-month analysis we found that in January, two articles (0.007%) on COVID-19 were indexed, 37 (0.13%) in February, 620 (2.23%) in March, 2,514 (9.04%) in April, 5,527 (19.87%) in May, and 18,596 (66.85%) in June.
T48 5669-5781 Sentence denotes From those articles, we retrieved n = 519 preprint publications (n = 319 from medRxiv and n = 200 from bioRxiv).
T49 5782-5848 Sentence denotes We were able to identify 62,051 authors coming from 148 countries.
T50 5849-5977 Sentence denotes Most authors came from China (n = 11,519), followed by the United States of America (n = 9,666) and Italy (n = 7,261) (Table 1).
T51 5978-6098 Sentence denotes Table 1 Top 20 countries with the highest number of publications on COVID-19 between 31 December 2019 and 30 June 2020.
T52 6099-6200 Sentence denotes Rank Country Number of publications with at least one author from the country SCImago country rank
T53 6201-6220 Sentence denotes 1 China 11,519 2
T54 6221-6258 Sentence denotes 2 United States of America 9,666 1
T55 6259-6277 Sentence denotes 3 Italy 7,261 6
T56 6278-6305 Sentence denotes 4 United Kingdom 4,362 3
T57 6306-6325 Sentence denotes 5 France 3,459 9
T58 6326-6345 Sentence denotes 6 India 2,568 10
T59 6346-6365 Sentence denotes 7 Spain 1,765 11
T60 6366-6385 Sentence denotes 8 Canada 1,679 7
T61 6386-6406 Sentence denotes 9 Germany 1,596 4
T62 6407-6426 Sentence denotes 10 Iran 1,349 17
T63 6427-6450 Sentence denotes 11 Australia 1,317 8
T64 6451-6475 Sentence denotes 12 Singapore 1,307 34
T65 6476-6497 Sentence denotes 13 Brazil 1,026 14
T66 6498-6517 Sentence denotes 14 Turkey 924 16
T67 6518-6542 Sentence denotes 15 Switzerland 796 15
T68 6543-6567 Sentence denotes 16 Netherlands 753 12
T69 6568-6585 Sentence denotes 17 Japan 717 5
T70 6586-6605 Sentence denotes 18 Taiwan 643 23
T71 6606-6626 Sentence denotes 19 Belgium 529 20
T72 6627-6778 Sentence denotes 20 Israel 459 26 In most cases, the country rank based on the number of publications on COVID-19 was similar to the SCImago country rank (Figure 1).
T73 6779-6923 Sentence denotes Figure 1 Comparison of SCImago country rank in category medicine and the rank of the countries with the highest number of articles on COVID-19.
T74 6924-7131 Sentence denotes The number of articles per one million citizens was positively associated with the Human Development Index, number of cases, and deaths due to COVID-19 per one million inhabitants (all p < 0.001) (Figure 2).
T75 7132-7406 Sentence denotes Figure 2 Correlation plots between number of articles one author from a country per at least one million citizens and (A) Human Development Index, (B) total number of COVID-19 cases per one million citizens, and (C) total number of COVID-19 deaths per one million citizens.
T76 7407-7557 Sentence denotes We identified 3,156 unique journal names to which we could match 2,571 titles (80.4%), including 27,296 unique articles that we were able to retrieve.
T77 7558-7759 Sentence denotes We found that most of the matched journals belonged to category “Medicine” (n = 5,038), followed by “Infectious Diseases” (n = 2,204) and “Cardiology and Cardiovascular Medicine” (n = 1,170) (Table 2).
T78 7760-7861 Sentence denotes Table 2 Top 20 journal categories with the highest number of articles on COVID-19 till 30 June 2020.
T79 7862-7900 Sentence denotes Rank Categories Number of articles
T80 7901-7930 Sentence denotes 1 Medicine 5,038 (21.18%)
T81 7931-7970 Sentence denotes 2 Infectious Diseases 2,204 (9.26%)
T82 7971-8029 Sentence denotes 3 Cardiology and Cardiovascular Medicine 1,170 (4.92%)
T83 8030-8059 Sentence denotes 4 Dermatology 708 (2.98%)
T84 8060-8130 Sentence denotes 5 Public Health, Environmental and Occupational Health 531 (2.23%)
T85 8131-8158 Sentence denotes 6 Neurology 525 (2.21%)
T86 8159-8193 Sentence denotes 7 Gastroenterology 514 (2.16%)
T87 8194-8244 Sentence denotes 8 Anesthesiology and Pain Medicine 511 (2.15%)
T88 8245-8308 Sentence denotes 9 Biochemistry, Genetics, and Molecular Biology 488 (2.05%)
T89 8309-8369 Sentence denotes 10 Critical Care and Intensive Care Medicine 472 (1.98%)
T90 8370-8406 Sentence denotes 11 Internal Medicine 436 (1.83%)
T91 8407-8436 Sentence denotes 12 Hematology 434 (1.82%)
T92 8437-8498 Sentence denotes 13 Pediatrics, Perinatology, and Child Health 433 (1.82%)
T93 8499-8525 Sentence denotes 14 Surgery 425 (1.79%)
T94 8526-8562 Sentence denotes 15 Multidisciplinary 415 (1.74%)
T95 8563-8592 Sentence denotes 16 Immunology 396 (1.66%)
T96 8593-8625 Sentence denotes 17 Health Policy 347 (1.46%)
T97 8626-8685 Sentence denotes 18 Radiology, Nuclear Medicine, and Imaging 337 (1.42%)
T98 8686-8717 Sentence denotes 19 Epidemiology 323 (1.36%)
T99 8718-8756 Sentence denotes 20 Otorhinolaryngology 299 (1.26%)
T100 8758-8768 Sentence denotes Discussion
T101 8769-8904 Sentence denotes In this report, we analyzed COVID-19-related publication productivity based on articles available via PubMed in the first half of 2020.
T102 8905-9003 Sentence denotes COVID-19-themed items considerably contributed to overall medical scholarly output in this period.
T103 9004-9103 Sentence denotes Importantly, most of the papers were original articles-the most essential medical knowledge source.
T104 9104-9203 Sentence denotes However, one in four positions on COVID-19 were minor papers such as editorials, commentaries, etc.
T105 9204-9271 Sentence denotes The growth in the number of articles was approximately geometrical.
T106 9272-9407 Sentence denotes These results have to be taken with caution because preprints were indexed in PubMed with delay resulting from the publication process.
T107 9408-9493 Sentence denotes COVID-19 pandemic is a new health phenomenon, which requires detailed investigations.
T108 9494-9556 Sentence denotes Several factors may enhance COVID-19 publication productivity.
T109 9557-9634 Sentence denotes First, many journals established free open-access for papers on COVID-19 [7].
T110 9635-9700 Sentence denotes Moreover, the most valuable reports may also be rapidly reviewed.
T111 9701-9807 Sentence denotes Many governmental and private institutions donated funds for research on SARS-CoV-2 and its spread [8-10].
T112 9808-9899 Sentence denotes Finally, media coverage of scientific progress related to COVID-19 remains intense [11,12].
T113 9900-9996 Sentence denotes In these circumstances, researchers have additional motivation to rapidly publish their results.
T114 9997-10103 Sentence denotes Every health crisis, like ongoing coronavirus pandemics, requires an acceleration in generating knowledge.
T115 10104-10220 Sentence denotes To further hasten the research, more funding is required to benefit researchers working on emerging health problems.
T116 10221-10449 Sentence denotes Other actions taken by authorities could be increasing the scientists' work time or engaging young researchers, who could increase not only their experience but also relieve more practiced scientists from their current projects.
T117 10450-10512 Sentence denotes Both of these actions require additional funding as well [13].
T118 10513-10659 Sentence denotes We should carefully analyze regular scientific expenditure and additional funding available during COVID-19 pandemics to validate this hypothesis.
T119 10660-10731 Sentence denotes This data should be compared with the research output about SARS-CoV-2.
T120 10732-10838 Sentence denotes To our best knowledge, there is no report concerning medical scientists’ productivity related to COVID-19.
T121 10839-10955 Sentence denotes We showed that authors from countries with higher HDI produced more articles than authors from less developed areas.
T122 10956-11020 Sentence denotes Previous publications also confirmed this disturbing trend [14].
T123 11021-11236 Sentence denotes There is a risk that developing countries generate less new knowledge on COVID-19, which could eventually lead to their further scientific marginalization and poor description of the pandemic in these areas [15,16].
T124 11237-11356 Sentence denotes We also showed that in most cases the country ranking based on COVID-19 publication is similar to SCImago country rank.
T125 11357-11578 Sentence denotes This suggests that authors coming from countries that normally produced the highest number of publications were also the most versatile in switching their scientific work related to the ongoing novel coronavirus pandemic.
T126 11579-11750 Sentence denotes It may also show that research funders from these countries can quickly and efficiently provide scientists with money needed for specific research in emergency situations.
T127 11751-11924 Sentence denotes There is also a possibility that the number of articles produced by authors from different countries varies not only because of lower HDI and severity of COVID-19 pandemics.
T128 11925-12040 Sentence denotes We have to consider the possible impact of factors such as armed conflicts, clinical engagement of physicians, etc.
T129 12041-12157 Sentence denotes Moreover, school closure may cause female researchers to leave scientific work and take care of their children [17].
T130 12158-12497 Sentence denotes Unsurprisingly, most of the articles were published in journals from the general category “Medicine,” and then “Infectious Diseases.” Further, the highest numbers of articles were published in categories “Cardiology and Cardiovascular Medicine” and “Dermatology.” In fact, COVID-19 may cause heart damage [18] and skin manifestations [19].
T131 12498-12839 Sentence denotes However, it may be suspected that more publications will be published in journals with categories such as “Public Health, Environmental and Occupational Health” and “Anesthesiology and Pain Medicine,” which will reflect the impact of the virus on public health and the emerging progress on intensive therapy on patients with severe COVID-19.
T132 12840-12849 Sentence denotes Strengths
T133 12850-12984 Sentence denotes First, entire MEDLINE was analyzed using an open API, and the economic and epidemiologic contexts were integrated in the calculations.
T134 12985-13186 Sentence denotes The data we provided suggest that the level of development and scientific productivity prior to the ongoing pandemic determined the efficacy and rate of producing knowledge about a new, unknown danger.
T135 13187-13360 Sentence denotes We may assume that future healthcare crises will also be better researched by countries with higher level of development, which are caring for their scientific productivity.
T136 13361-13400 Sentence denotes This work generates further hypotheses.
T137 13401-13553 Sentence denotes One of them is that greater spending on research proportionately associates with scientific productivity at the time of a public healthcare crisis [20].
T138 13554-13675 Sentence denotes We may also ask whether scientific productivity is associated with better results in fighting with the COVID-19 pandemic.
T139 13676-13687 Sentence denotes Limitations
T140 13688-13722 Sentence denotes The study has several limitations.
T141 13723-13954 Sentence denotes First, we analyzed only articles accessible via PubMed, which include the MEDLINE database and papers included in the National Library of Medicine catalogue [21]. PubMed only recently started to include preprints in search results.
T142 13955-14070 Sentence denotes Second, we did not weight the importance of the research by journals’ criteria, articles’ citations, or altmetrics.
T143 14071-14137 Sentence denotes These features may additionally distinguish most essential papers.
T144 14138-14242 Sentence denotes Finally, we analyzed a limited number of factors that may be associated with the article’s productivity.
T145 14244-14255 Sentence denotes Conclusions
T146 14256-14366 Sentence denotes Most of early COVID-19 research output came from highly developed countries strongly affected by the pandemic.
T147 14367-14487 Sentence denotes We believe that more researches on scientific productivity during the later months of the pandemics should be performed.
T148 14488-14618 Sentence denotes It is also important to further investigate the factors that determine the number of publications coming from different countries.
T149 14619-14656 Sentence denotes Our study, however, had a limitation.
T150 14657-14804 Sentence denotes We did not present the information about scientific expenditure on COVID-19, which could be another interesting topic to cover in further research.
T151 14806-14866 Sentence denotes The authors have declared that no competing interests exist.
T152 14867-14879 Sentence denotes Human Ethics
T153 14880-14934 Sentence denotes Consent was obtained by all participants in this study
T154 14935-14948 Sentence denotes Animal Ethics
T155 14949-14965 Sentence denotes Animal subjects:
T156 14966-15051 Sentence denotes All authors have confirmed that this study did not involve animal subjects or tissue.
T157 15053-15063 Sentence denotes Appendices
T158 15064-15065 Sentence denotes  
T159 15066-15204 Sentence denotes Table 3 Top 20 journal categories with the top 10 countries with highest number of articles on COVID-19 to 30 June 2020 on each category.
T160 15205-15598 Sentence denotes No Medicine n = 5,038 Infectious Diseases n = 2,204 Cardiology and Cardiovascular Medicine n = 1,170 Dermatology n = 926 Public Health, Environmental and Occupational Health n = 497 Neurology n = 919 Gastroenterology n = 889 Anesthesiology and Pain Medicine n = 869 Biochemistry, Genetics, and Molecular Biology n = 1,008 Critical Care and Intensive Care Medicine n = 1,036
T161 15599-15760 Sentence denotes 1 China n = 1,975 China n = 1,418 Italy n = 383 Italy n = 293 China n = 158 USA n = 244 Italy n = 243 USA n = 227 China n = 259 China n = 377
T162 15761-15915 Sentence denotes 2 USA n = 835 Italy n = 388 China n = 273 Spain n = 118 Italy n = 66 Italy n = 187 China n = 169 China n = 154 USA n = 222 USA n = 150
T163 15916-16067 Sentence denotes 3 Italy, UK n = 758 USA n = 362 USA n = 260 USA n = 110 USA n = 57 China n = 105 USA n = 159 UK n = 144 Italy n = 134 Italy n = 141
T164 16068-16214 Sentence denotes 4   France n = 191 Spain n = 161 India n = 97 Iran n = 45 France n = 97 UK n = 118 Italy n = 117 France n = 109 France n = 137
T165 16215-16368 Sentence denotes 5 India n = 522 Japan n = 155 UK n = 152 China n = 87 France n = 41 UK n = 72 France n = 69 Australia n = 45 UK n = 90 Germany n = 49
T166 16369-16536 Sentence denotes 6 France n = 409 Iran n = 131 Germany n = 113 France n = 75 India n = 35 Spain n = 63 Germany, Spain n = 30 Germany n = 44 Germany n = 56 UK n = 38
T167 16537-16688 Sentence denotes 7 Iran n = 314 UK n = 113 Australia n = 105 Turkey n = 59 UK n = 29 India n = 62   Singapore n = 38 Spain n = 45 Netherlands n = 30
T168 16689-16850 Sentence denotes 8 Germany n = 218 Canada n = 97 India n = 98 Germany n = 34 Brazil n = 25 Germany n = 36 Japan n = 25 India n = 36 India n = 36 Canada n = 28
T169 16851-17027 Sentence denotes 9 Spain n = 209 India n = 81 Canada n = 93 UK n = 27 Colombia n = 23 Canada n = 24 Australia, Belgium n = 23 Canada, Spain n = 32 Canada n = 33 Spain n = 23
T170 17028-17192 Sentence denotes 10 Switzerland n = 180 Germany n = 79 France n = 90 Iran n = 26 Australia n = 18 Brazil n = 24     Japan n = 24 Belgium, India, Singapore n = 21
T171 17193-17492 Sentence denotes No Internal Medicine n = 623 Hematology n = 932 Pediatrics, Perinatology, and Child Health n = 693 Surgery n = 497 Multidisciplinary n = 413 Immunology n = 806 Health Policy n = 428 Radiology, Nuclear Medicine, and Imaging n = 526 Epidemiology n = 375 Otorhinolaryngology n = 531
T172 17493-17654 Sentence denotes 1 Italy, USA n = 131 Italy n = 214 China n = 182 Italy n = 184 China n = 179 China n = 220 USA n = 102 China n = 201 China n = 77 USA n = 265
T173 17655-17806 Sentence denotes 2   USA n = 150 Italy n = 164 France n = 104 USA n = 71 Italy n = 170 China n = 93 Italy n = 101 France,Italy n = 53 France n = 110
T174 17807-17939 Sentence denotes 3 India n = 89 UK n = 135 India n = 121 USA n = 74 Italy,UK n = 34 USA n = 132 UK n = 81 UK n = 66   Italy n = 58
T175 17940-18082 Sentence denotes 4 China n = 71 France n = 114 USA n = 59 Brazil n = 35   Spain n = 84 Canada n = 37 Iran n = 51 UK n = 49 China, UK n = 22
T176 18083-18225 Sentence denotes 5 Australia n = 48 China n = 101 UK n = 37 UK n = 22 Germany n = 29 France n = 51 Italy n = 35 USA n = 36 Germany n = 39  
T177 18226-18396 Sentence denotes 6 UK n = 41 Spain n = 57 France, Spain n = 34 India n = 20 France n = 18 Germany n = 48 Australia n = 30 Japan n = 17 Netherlands n = 31 Brazil n = 18
T178 18397-18569 Sentence denotes 7 Canada n = 34 Brazil, Germany, Netherlands n = 41   China, Germany n = 15 Japan n = 13 UK n = 34 India n = 17 Canada n = 15 Canada n = 25 India n = 12
T179 18570-18717 Sentence denotes 8 Spain n = 24   Australia n = 30   Australia, Spain n = 12 Poland n = 28 France n = 12 Germany n = 14 USA n = 20 Germany n = 9
T180 18718-18861 Sentence denotes 9 France n = 20   Germany n = 17 Spain, Turkey n = 14   Turkey n = 20 Iran n = 11 Spain n = 13 Australia n = 16 Spain n = 8
T181 18862-19028 Sentence denotes 10 Brazil, Indonesia n = 17 Canada n = 38 Turkey n = 15   Switzerland n = 11 Australia n = 19 Belgium n = 10 France n = 12 Spain n = 12 Iran n = 7