Comparison of citation rates between Covid-19 and non-Covid-19 articles across 24 major scientific journals.

Covid-19 has been front and center in the global landscape since the beginning of 2020. In response, the scientific field has dedicated enormous amounts of resources to researching the virus and its effects. The number of times Covid-19 publications are being cited throughout the literature appears remarkably high but has not been directly compared to non-Covid-19 papers in the same journals over an extended period. In our study, we use Clarivate's Web of Science-Science Citation Index Expanded™ database to identify Covid-19 papers published in 24 major scientific journals over a period of 24 months from January 1, 2020 to December 31, 2021. We conduct our search using keywords "Covid-19", "coronavirus", and "sars-cov-2" to locate publications with these words in the title. We then quantify the number of citations these papers have received and compare rates to non-Covid-19 papers in the same journals over the same timeframe. We find that, across 24 open-access and subscription-based scientific journals, Covid-19 papers published in the past 2 years currently have a median citation rate of 120.79 compared to 21.63 for non-Covid-19 papers. When negative binomial regression is used to minimize the influence of other variables such as article number variation and field of research, Covid-19 papers have still experienced more than 80% increase in citations relative to non-Covid-19 papers. These novel findings demonstrate that Covid-19 papers are being cited at remarkably higher rates than non-Covid-19 articles contained within the same journals. This suggests that journal impact factor, which is a product of the number of citations that recently published articles receive, will likely be drastically influenced by the number of Covid-19 papers that a journal has included within its pages in the previous years.

Introduction

In the early days of January 2020, the World Health Organization (WHO) published a bulletin that brought attention to 44 new cases of pneumonia of unknown etiology that had appeared at the end of December 2019 in Wuhan City, Hubei Province of China [1]. Regional cases increased rapidly over the next weeks, and scientists worldwide began to take notice. By the end of January, more than 50 research papers had been published about the outbreak [2]. In the coming months, while researchers scrambled to learn more about the coronavirus that was now spreading internationally, the WHO again released a bulletin on March 11, 2020, officially classifying Covid-19 as a global pandemic [3]. For months after, cases and fatalities rose at staggering clips as governing bodies worldwide grappled with the best measures to contain the virus. Eventually, strict regulations and vaccine rollouts were implemented with enough success to begin to slow case growth [4]. Amidst all of this, there has been an explosion of peer-reviewed literature about Covid-19 as researchers work to uncover details such as structure, infectivity, spread, effects, prevention, and treatment of this novel virus. According to the Web of Science Science Citation Index Expanded™ (WOS), which includes more than 8,300 journals across 150 scientific disciplines, nearly 200,000 Covid-19 related papers were published or presented in 24 months between January 1, 2020 and December 31, 2021 [5].

Unsurprisingly, several seminal Covid-19 publications have been cited at incredibly high rates as researchers have turned to these papers to help guide their next steps [6-8]. However, this citation trend in Covid-19 literature has not been limited to only a select few articles. As Covid-19 remains in the spotlight, the existing Covid-19 body of literature continues to be heavily leaned upon by scientists hoping to expand the existing knowledge further.

The extent to which Covid-19 papers are being cited in selected top journals relative to non-Covid-19 papers in the same journals has yet to be explored in detail. To address this gap in the literature we use WOS to examine citation rates for Covid-19-related articles published between January 1, 2020 and December 31, 2021 across 24 major scientific journals. We compare these rates with citation rates for non-Covid-19 articles published in the same 24 journals over an identical time frame. We anticipate that these findings could be of value to journals editors and researchers when considering efforts for future publications. In addition, we expect these findings to shed light on the influence that the current influx of Covid-19 literature will have on Journal Impact Factor (JIF) in the years ahead.

Materials and methods

Journal selection

Using information provided in Clarivate’s 2020 Journal Citation Reports [9] published on June 30, 2021, the top three journals by impact factor were selected from eight scientific categories as defined by WOS. Disciplines were selected based on the likelihood of having high relevancy to Covid-19 and, therefore, a sufficient volume of Covid-19-related papers in that field’s premier journals. A baseline of 15 Covid-19 articles was set as a requirement for a journal to be included. If a top three journal did not meet this baseline, the next highest journal by impact factor from that field was included. The disciplines chosen were respiratory, cardiology, immunology, radiology, microbiology, gastroenterology and hepatology, general and internal medicine, and multidisciplinary sciences. With three journals each from eight fields, a total of 24 journals were selected (Table 1).

Table 1

Summary of 24 selected journals.

Journal	Specialty	COVID-19 article		Impact factor	Publisher	Publication mode (open-access, subscription-based, or hybrid)	Country	Number of issues/year
		Yes	No
		Articles number	Articles number
Nature	Multidisciplinary Sciences	145	1929	49.962	Nature Research	Hybrid	Germany	51
Nature Communications	Multidisciplinary Sciences	428	12449	14.919	Nature Research	Open-access	Germany	Continuous publishing
Science	Multidisciplinary Sciences	145	1479	47.728	Amer Assoc Advancement Science	Hybrid	USA	51
JAMA	Medicine, General, and Internal	54	350	56.274	Amer Medical Assoc	Subscription-based; free to public after 6 months	USA	48
Lancet	Medicine, General, and Internal	89	382	79.323	Elsevier Science Inc	Hybrid	USA	52
NEJM	Medicine, General, and Internal	98	579	91.253	Massachusetts Medical Soc	Hybrid	USA	52
Cell Host and Microbe	Microbiology	53	217	21.023	Cell Press	Subscription-based; free to public after 12 months	USA	12
Clinical Infectious Diseases	Microbiology	569	1837	9.079	Oxford Univ Press Inc	Hybrid	USA	24
Nature Microbiology	Microbiology	27	256	17.745	Nature Research	Hybrid	Germany	12
European Journal of Nuclear Medicine and Molecular Imaging	Radiology	43	685	9.236	Springer	Hybrid	USA	12
Radiology	Radiology	75	497	11.105	Radiological Soc North America	Hybrid	USA	12
Ultrasound in Obstetrics Gynecology	Radiology	27	355	7.299	Wiley	Hybrid	USA	12
Journal of Am Col Cardiology	Cardiology	39	673	24.093	Elsevier Science Inc	Hybrid	USA	50
Circulation	Cardiology	22	593	29.690	Lippincott Williams and Wilkins	Hybrid	USA	50
European Heart Journal	Cardiology	20	524	29.983	Oxford Univ Press	Hybrid	England	24
Gastroenterology	Gastroenterology and Hepatology	27	523	22.682	WB Saunders Co-Elsevier Inc	Hybrid	USA	12
Gut	Gastroenterology and Hepatology	35	498	23.059	BMJ Publishing Group	Hybrid	England	12
Journal of Hepatology	Gastroenterology and Hepatology	17	452	25.083	Elsevier	Hybrid	Netherlands	12
Am J of Respiratory and Crit Care Med	Respiratory	30	371	21.405	Amer Thoracic Soc	Hybrid	USA	24
European Respiratory Journal	Respiratory	40	457	16.671	European Respiratory Soc Journals Ltd	Hybrid	England	12
Lancet Respiratory Medicine	Respiratory	67	118	30.700	Elsevier Sci Ltd	Hybrid	England	12
Immunity	Immunology	48	279	31.745	Cell Press	Hybrid	USA	12
Nature Immunology	Immunology	26	249	25.606	Nature Research	Hybrid	Germany	12
Nature Reviews Immunology	Immunology	23	111	53.106	Nature Research	Subscription-based	Germany	12

Data collection and sample randomization

The WOS search criteria were customized to include documents categorized as “Article” published between January 1, 2020 and December 31, 2021. The database tags papers as articles if they meet the following criteria: “Reports of research on original works. Includes research papers, features, brief communications, case reports, technical notes, chronology, and full papers that were published in a journal and/or presented at a symposium or conference” [5]. In addition, we included papers categorized by Web of Science as “Review” to capture meta-analyses and systematic reviews as well. All articles published within the 24-month time frame were selected to produce an average citation rate for the journal itself over that period. Next, articles without the terms “Covid-19”, “coronavirus”, or “SARS-CoV-2” in the title were selected to provide an average citation rate for only non-Covid-19 articles in the journal. Finally, articles containing the keywords “Covid-19”, “coronavirus”, or “SARS-CoV-2” in the title were selected to provide an average citation rate for Covid-19-related articles. In this way, three separate citation averages were gathered for each journal: 1) all articles 2) non-Covid-19 articles 3) only Covid-19 articles.

In many journals, there was discrepancy between the number of Covid-19 and non-Covid-19 articles. To establish a comparison that was more evenly matched in terms of article volume, randomization software on Microsoft Excel was used to select a sample of non-Covid-19 papers from each journal to create a 1:1 comparison of citation rates between non-Covid and Covid papers. A single average citation rate was obtained from this smaller sample as well.

Data analysis

Data were analyzed with R software version 4.1.2 [10] using the packages (Rcmdr) [11] and (glm2) [12]. Significance was considered when the P-value was < 0.05. Median and range were used to represent continuous variables (not normally distributed) while we used frequencies and percentages to represent categorical variables. The skewness and Kurtosis tests were used for testing the normal distribution of continuous variables. We estimated the effect of Covid-19 subject on citation counts using a negative binomial regression model. The negative binomial regression model was selected over a linear regression model because it resulted in a better fit to the data and was more appropriate for count data. The negative binomial regression model is similar to the Poisson regression model (for count data) except that it performs better with data over-dispersion [13, 14]. The model was also used to assess any differences in citation rates attributed to the field category. Finally, the model was adjusted to account for the discrepancy in volume between non-Covid-19 papers and Covid-19 papers.

Results

Comparisons between non-Covid-19 and Covid-19 articles including all fields are shown in Table 2. The median citation rate at two years for Covid-19 articles in the top journals across all eight fields is 120.79 (p = <0.001). For non-Covid-19 articles, the median citation rate is 21.63 (p = < 0.001). This equates to a Covid-19: non-Covid-19 ratio of 5.58 citations per article. When comparing Covid-19 papers and the 1:1 randomized sample of non-Covid-19 papers, the median citation decreases from 21.63 to 20.1 for non-Covid-19 citations and the citation ratio between Covid-19 and non-Covid-19 papers climbs to 6.01 (p = <0.001).

Table 2

Quantity of citations for Covid-19 and non-Covid-19 articles with median and range values across all fields.

Variables		COVID-19 article				Total		P-value
		No		Yes		(N = 28,010)
		(n = 25,863)		(n = 2,147)
		Count	%	Count	%	Count	%
Field	Cardiology	1,790	6.9	81	3.8	1,871	6.7	0.006*
	Gastroenterology Hepatology	1,473	5.7	79	3.7	1,552	5.5
	Immunology	639	2.5	97	4.5	736	2.6
	Medicine, General, and Internal	1,311	5.1	241	11.2	1,552	5.5
	Microbiology	2,310	8.9	649	30.2	2,959	10.6
	Multidisciplinary Sciences	15,857	61.3	718	33.4	16,575	59.2
	Radiology	1,537	5.9	145	6.8	1,682	6.0
	Respiratory	946	3.7	137	6.4	1,083	3.9
Variables		Median	Range	Median	Range	Median	Range	P-value
Average citations		21.63	6.02–83.63	120.79	28.72–824.44	52.815	6.02–824.44	< 0.001*
Average citations–random sample		20.1	6.99–79.31	120.79	28.72–824.44	53.935	6.99–824.44	< 0.001*

*Statistically significant

A negative binomial regression model was used to assess for potential confounding variables (Table 3). Only Covid-19 articles within the Medicine, General, and Internal category were significantly affected by the field itself with a 28% boost in citation rate relative to non-Covid-19 articles (p = 0.029, 95%CI [0.13–2.43]). No other fields accounted for significant difference in citation rates amongst Covid-19 and non-Covid-19 papers published within the same field. When controlling for influence of field categorization and article numbers, Covid-19 papers received 84% more citations than non-Covid-19 papers in the non-randomized sample (p<0.001, 95% CI [1.22–2.45]). When the randomized 1:1 sample was analyzed, Covid-19 papers still received 82% more citations than non-Covid-19 papers (p<0.001, 95% CI [1.20–2.43]).

Table 3

Negative binomial regression output reporting independent variable effects on citation count¶.

Predictors	Non-randomized sample				Randomized sample
	IRR	95% Confidence Interval		P-value	IRR	95% Confidence Interval		P-value
		Lower	Upper			Lower	Upper
Cardiology	Reference
Respiratory	-0.17	-1.32	0.98	0.771	-0.31	-1.46	0.84	0.592
Radiology	-0.76	-1.92	0.40	0.197	-0.82	-1.97	0.34	0.167
Multidisciplinary Sciences	0.53	-0.72	1.77	0.407	0.48	-0.76	1.72	0.449
Microbiology	-0.22	-1.38	0.93	0.702	-0.29	-1.45	0.86	0.619
Medicine, General, and Internal	1.28	0.13	2.43	0.029*	1.20	0.05	2.34	0.041
Immunology	0.11	-1.03	1.26	0.846	0.15	-1.00	1.30	0.800
Gastroenterology Hepatology	-0.26	-1.41	0.89	0.659	-0.33	-1.48	0.82	0.572
Non-COVID-19 article	Reference
COVID-19 article	1.84	1.22	2.45	<0.001*	1.82	1.20	2.43	<0.001*

¶Adjusted for articles’ number

*Statistically significant

Discussion

We used WOS to determine the difference in rates at which Covid-19 and non-Covid-19 articles from 24 top medical journals are being cited. Looking at all categories and journals that were included, Covid-19 articles published between January 1, 2020 and December 31, 2021 are being cited at considerably higher rates than the non-Covid-19 papers. Across eight selected fields, the median citation for a Covid-19 paper approaches six times that of a non-Covid-19 paper within the same journals. This holds even when article volume is equated using a 1:1 sample of non-Covid to Covid articles as median citation is six times greater for the Covid-19 articles. Using a negative regression model to analyze the entire data, Covid-19 papers have 84% more citations than non-Covid-19 papers when controlling for field and article number discrepancies. This number dips only slightly to 82% when the smaller, randomized sample is compared. `Amongst all fields, only articles categorized as Medicine, General, or Internal according to WOS see a bump (28%) in citation rates that can be attributed to the field itself. Thus, an article’s focus on Covid-19 seems to be a primary driver of increased citations for these articles compared to those that do not deal with a Covid-19 related topic.

Reasons behind the major increase in citations for Covid-19 articles seem straightforward. Covid-19 has dominated global focus since the onset of 2020, affecting over 200 countries across the world [15]. As such, researchers are eager to add their contributions to what is known and what can be done to combat Covid-19 and, to do this, are citing earlier works to support their approaches. This earnest for more knowledge is further bolstered by increased government funding for Covid-19 research. In the United States, the Coronavirus Aid, Relief, and Economic Security (CARES) Act was signed into law on March 27, 2020 and allocates 940 million dollars to the National Institute of Health (NIH) to be used for funding Covid-19 research [16]. Thus, more funding opportunities are available at the researcher level for research that focuses on Covid-19. Another potential reason for the spike in Covid-19 citations is the exhibited capacity of the virus to mutate rapidly. As new variants appear, researchers are offered the chance to publish on new epidemiological or variant characterization studies.

Previous studies have looked at citation rates for preprints of Covid-19 papers [17] and quality of evidence contained within published Covid-19 articles [18, 19]. Additionally, citation rate for Covid-19 papers has been assessed previously without direct comparison to non-Covid-19 papers in the same journals [20]. To our knowledge, this study is the first to quantify the rate at which a large volume of peer-reviewed Covid-19 articles are being cited, on average, in major medical journals and compare these results to non-Covid-19 articles in the same journals. In doing this, we demonstrate the sharp contrast between citation rates for Covid-19 and non-Covid-19 articles published in 24 months during the rise and height of the global pandemic. While our research reveals the substantial degree to which Covid-19 articles are being cited in top journals relative to non-Covid-19 articles, the effect on journals themselves remains to be seen.

One way that these effects may be observed is through the influence that Covid-19 papers will have on JIF. JIF is a commonly used surrogate to determine journal excellence and is calculated by dividing number of citations in the current year for articles published in the previous two years by total number of articles published in that journal during the previous two years [21]. Therefore, it is a direct measure of how many citations recently published articles in a given journal receive. As we have shown, Covid-19 papers across all selected fields are being cited at a vastly increased rate compared to non-Covid-19 papers within the same journals. We would estimate that as Covid-19 papers continue to flood the literature across all scientific fields, so long as Covid-19 continues to hold the global spotlight, Covid-19 papers will continue to be cited, on average, at much higher levels than non-Covid-19 papers. We anticipate that JIFs will be affected in coming years which could change the landscape for how journal excellence is determined in the future.

Limitations

For the scope of this paper, we used papers categorized as “Article” or “Review” in our WOS search to ensure that we were focusing on original works and evidence-based literature. This means that other publications such as letters, editorials, perspectives, and opinions were not included in our search criteria which leaves a large number of publications out of the study. Inclusion of these would undoubtedly have increased the volume of papers and affected the results, though the direction or magnitude of change is unclear. Another limitation of this study is that open-access versus subscription-based journals were not filtered separately during the WOS search. Thus, data include a combination of open-access and subscription-based publications in the non-Covid-19 articles. This would seemingly be an impactful factor in how often these articles are being cited. However, a recent meta-analysis showed that the advantage of open-access is debatable with many studies showing no difference in citation rates andquality and heterogeneity concerns posing challenges for generalization [22].

Finally, though WOS is a comprehensive and highly regarded database, it is not without shortcomings. Most notably, its categorization of a publication as “Article” seems imperfect. To examine this more closely, we randomly selected three journals included for this paper and manually searched each journal’s website for Covid-19-related articles that the journal itself had categorized as an original piece of research over three months. We compared this to the papers under “Article” that WOS captured over the same 3-month period for that journal. We found that the WOS database included 76% of the Covid-19 papers contained within the journals themselves. Further, 91% of the papers under the “Article” category in the database were classified as original works by the journals themselves. In our sample, the database captured about three-quarters of the papers that should be included but is more precise in labeling only reports of research on original work as “Article”. Though our method of locating Covid-19 and non-Covid-19 papers in the selected journals was more expedient, manual scouring of the journals themselves over the 24 months would have optimized both the sensitivity and specificity of locating and comparing the most comprehensive list of publications possible.

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Comparison of citation rates between Covid-19 and non-Covid-19 articles across 18 major medical journals

PONE-D-22-05834

Thank you for asking me to review the above-titled manuscript. The topic is interesting. However, there are significant problems in the manuscript.

Abstract: 1) Line 29- What are these major journals? 2) Line 30 - start starting and end dates; why only 18 months and not up to 31 December 2021? 3) How did you search the WOS? 4) Were these non-covid and covid papers published in the same journal? 5) Were these open-access journals or subscription-based journals? Did you balance between them? 6) What were the JIFs of these journals or the median IQR? 7) Lines 34-35-- look strange because all papers on COVID-19 in subscription-based journals were available free of charge. I cannot see any explanation in your discussion 8) JIF is measured every 2 years, not 18 months. 9) Lines 37-39- on what basis did you come. 10) What was the percentage of Covid versus non-covid in each journal selected.

Introduction - 1) China declared a novel virus causing this disease by December 2019. 2) Lines 56, page 3: Why not up to 31 December 2021? to include vaccination research as well? 3) Give references/citations (lines 57-63). 4) Not clear what is the problem that triggered the study? 5) What is the purpose of the study? We all know that citations are most likely higher for COVID-19 papers, you need to dig deeper into this. 6) What is your research question?

Methods- 1) Line 75- was the number of articles on Covid-19 and non-Covid balanced? How? 2) Line 72-Why only top JIF journals? 3) Why did you not target the top JIF (Q1), the middle JIF journals (Q2-Q3) and those with low JIF (Q4)? 4). Why were Journals on Neurology and those on Gastroenterology and Hepatology not included? 5) What do you mean by Multidisciplinary Science journals? Line 78? 6) How many journals were included for each field? STATE THE JOURNALS INCLUDED IN EACH FIELD. 7) WHAT ARE THESE THREE TOP JOURNALS? Were these on Microbiology and or Virology?

Methods- It is unusual and strange that the authors do not provide any details about their work. Research must be transparent.

Methods- Lines 80-85 We know that this is a limitation in the classification of articles in WoS. Did you identify them in the analysis and show numbers of research, numbers of case report, numbers of brief communication etc, and you should define each category.

Methods- Lines 87 (page 4) and linnes 88-90 (page 5) NOT CLEAR.

Methods 94-96 - The aim should be EQUAL NUMBERS of Covid-19 and Non-Covid papers not 2:1. The number of Non-Covid is usually small, so accept it as the basic number and randomise for an equivalent number of COVID-19 papers. This should be the way.

METHODS- WHY THE AUTHORS DID NOT INCLUDE FUNDING AND COMPARE BETWEEN THE COVID-19 PAPERS and NON-COVID PAPERS?

Methods- What were the countries and institutes that produced these papers in both groups?

Methods: WHY WERE THE ALTMETRIC SCORES NOT COMPARED? As well?

English needs editing. Several statements are not clearly stated. Also, statements like "This was done..."

Table 1- 1) What is the number of journals in each category "Multidisciplinary, Cardiology etc" 2) What is the NAME of the Journal in each category? 3) What is the JIF of each journal? 4) State the number of papers from each journal in Covid-19 and Non-Covid 19.

Table- You need a new table summarising key topics raised in each category and numbers in both groups.

Discussion- 1) Poorly written. 2) Why do lines 141-155 have no citations? 2) Funding should be compared between the two groups in the study; SEE COMMENTS UNDER METHODS? 3) We need to know with journals were open access and which one was subscription-based paper.

Discussion- No explanation was given to the 10 times issue of open access journals. We know that all papers on COVID-19 were available free of charge and this is an important cause for the high citations of the COVID-19 papers (not discussed). BUT it does not explain the authors' claim for 10 times issue (also missing).

Limitations: 1) Articles are not only research and what is stated is not accurate. 2) Are case reports evidence-based? 3) Talking about evidence-based work- The top in this are Systematic Reviews and meta-analyses. MMy question, Why these two groups were excluded? Lines 191.

What are these three journals- state their Names. For all journals, you must state title, company/publisher, JIF, open-access or subscription-based, country, and the number of issues per year, the year it was issued. Show the number of papers for each group This could be in a table.

Conclusion- should be rewritten.

References- Should be improved.

**********

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Reviewer #1: Yes: Dr Mustafa Mohammed Mustafa

Reviewer #2: No

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13 Jun 2022

Comments also included in separate attached file title "Response to Reviewers"

Response to Reviewer Comments

Reviewer #1: The scientific value of the research is low, but the authors followed a good research methodology, data analysis, as well as the unique research idea that enriched the article.

We appreciate the positive review of our study

1. Judging in this research depends on the availability of data about scientific journals that have been cited, which supports the results, and therefore the authors must attach the list of scientific journals that were included in the study, (it will be useful if added to the methodology), even if that would benefit the journals but it is not considered advertisement for them, it is their right, and in the same time it is essential document for the publishing of this article. Thank you for bringing this to our attention. We created an additional table to list all journals included in the study. We will also include all data gathered from each journal in our data set which will be uploaded as a Supporting Information File.

Reviewer #2: Thank you for asking me to review the above-titled manuscript. The topic is interesting. However, there are significant problems in your manuscript.

We thank you for your interest in the study and willingness to provide helpful feedback.

1. Line 29- What are these major medical journals? Because there are 24 journals, we believe that it would detract from the focus of the abstract to list them individually. They are listed separately in Table 1 in the methodology section.

2. Line 30- Start and end dates; Why only 18 months and not up to 31 December 2021? Start and end dates have now been included. Data has been expanded to include 24 months up to 31 December 2021.

3. How did you search the WOS? The search was conducted by searching for all titles that had “Covid, “sars-cov-2”, or “coronavirus” in a given journal and obtaining a single average citation for these papers. We then repeated the process for all titles that did not have any of the aforementioned keywords and obtained a single citation for these papers as well. The process was repeated individually for each journal. We have included an additional sentence explaining briefly how the search was conducted.

4. Were these non-Covid and Covid papers published in the same journal? We have adjusted the wording to make it clearer that these papers were published within the same journal.

5. Were these open-access journals or subscription-based journals? Did you balance between them? We have added a line stating that both open-access and subscription-based journals were included. The great majority of the included journals employ a hybrid model with options for both open-access and subscription-based publishing. WOS does allow for filtering of open-access articles but fails to filter for articles that were originally published as subscription-based but become free to the public after a specified period of time has elapse, as is the protocol for several of the journals that we searched. Further, a recent meta-analysis showed the advantage of open-access is debatable with many studies showing no difference, with quality and heterogeneity concerns posing challenges for generalization.

Reference:

Langham-Putrow A, Bakker C, Riegelman A (2021). Is the open access citation advantage real? A systematic review of the citation of open access and subscription-based articles. PLOS ONE 1e0253129. https://doi.org/10.1371/journal.pone.0253129

6. What are the JIFs of these journals or the median IQR? JIFs for all journals now included as part of additional table (Table 1).

7. Lines 34-35—look strange because all COVID-19 in subscription-based journals were available free of charge. I cannot see any explanation in your discussion. Wording has been adjusted to clarify this point.

8. JIF is measured every 2 years, not 18 months. Data now reflects 2-year period from 1/1/2020 to 31/12/2021 rather than 18 months as previously.

9. Lines 37-39- on what basis did you come? We are arriving at this suggestion based on our findings that Covid-19 papers are being cited at much higher rates than non-Covid papers within the same journals. Therefore, we expect that journals will see their JIF inflate in the coming years due given that they have been publishing (Covid) articles that are, on average, more highly cited than articles that are unrelated to Covid. We have adjusted the wording to make this point more salient.

10. What was the percentage of Covid versus non-Covid in each journal selected? Total number of papers of each type now included in Table 1.

11. China declared a novel virus causing this disease by December 2019. Wording adjusted to make this point clearer.

12. Lines 56, page 3: Why not up to 31 December 2021 to include vaccination research as well? Data now includes all publications up to this date.

13. Give references/citations (lines 57-63). Citation for these lines has now been added.

14. Not clear what is the problem that triggered the study? What is the purpose of the study? We all know that citations are most likely higher for COVID-19 papers, you need to dig deeper into this. What is your research question? We agree that it is widely known that Covid-19 papers are cited at a higher rate across the literature. However, we note that there is a gap in the literature comparing the rate at which Covid-19 papers in top journals are being cited to the rate at which non-Covid articles in the same journals are being cited. By doing this direct comparison we intend to answer the question “How much different is the rate of citation for Covid articles versus non-Covid articles published within the same journals across 24 of the top journals spanning the scientific field?” Though not the main focus of our paper, we believe that these data will be helpful in the future when determining the utility of JIF to quantify journal excellence and prestige in a post-Covid landscape.

15. Methods-1) Line 75- was the number of articles on Covid-19 and non-Covid balanced? How? Yes, in Tables 2 and 3 we include both absolute numbers and a balanced 1:1 random sample of Covid and non-Covid papers.

16. Line 72- why only top JIF journals? Why did you not target the top JIF (Q1), the middle JIF journals (Q2-Q3) and those with low JIF (Q4)? We targeted only top JIF journals from 8 fields with the belief that these 24 journals and the >20000 articles within would provide adequate sample size to highlight the different rates at which Covid-19 and non-Covid-19 articles from the same journals are being cited.

17. Why were journals on Neurology and those on Gastroenterology and Hepatology not included?

Top journals by JIF in Neurology did not meet inclusion criteria of minimum number of Covid articles per WOS search. Thank you for the suggestion of adding Gastroenterology and Hepatology. Data from the top 3 journals in this category have been added.

18. What do you mean by Multidisciplinary Science journals? This is the categorization that is assigned by WOS to journals that publish broadly across the field of science.

19. How many journals were included for each field? State the journals included in each field. What are these three top journals? Were these on Microbiology and or Virology? It is unusual and strange that the authors do not provide any details about their work. Research must be transparent. Table 1 has been added which lists all journals (3 from each field) and will be included in the methodology section. These journals were not specific to Microbiology or Virology. We have added Microbiology as a separate category and included 3 journals from this category as well.

20. Methods- lines 80-85- We know that this is a limitation in the classification of articles in WOS. Did you identify them in the analysis and show numbers of research, numbers of case report, numbers of brief communication etc, and you should define each category. Unfortunately, WOS classifies each of these article types under a single “Article” categorization. Distinguishing between paper types would require manual individual extraction of each paper which is not feasible given volume of included papers. Further, as our main objective is to compare citation rates between Covid and non-Covid articles within the same journals, we believe that focus on sub-categorization does not advance the paper toward the main objective.

21. Lines 87 (page 4) and lines 88-90 (page 5) not clear. Wording has been adjusted for clarity

22. Methods 94-96- The aim should be equal numbers of Covid-19 and Non-Covid papers not 2:1. The number of Non-Covid is usually small, so accept it as the basic number and randomize for an equivalent number of Covid-19 papers. Thank you for this recommendation. We have updated the date to compare a 1:1 sample rather than 2:1.

23. Why did the authors not include funding and compare between the Covid-19 papers and non-Covid papers? Determining funding would require manual extraction as WOS does not allow for filtering by funding. This is not feasible given number of papers.

24. What were the countries and institutes that produced these papers in both groups? Similarly, this would require manual extraction from each paper which was not feasible given volume.

25. Methods: Why were the altimetric scores not compared as well? Given our specific objective of comparing citation rates in Covid and non-Covid articles within top selected journals based on JIF, we believe that this would not influence the objective.

26. English needs editing. Several statements are not clearly stated. Also, statements like “This was done…” We reworded any statements that appeared unclear and removed “This was done..” where present

27. Table 1 1) What is the number of journals in each category “Multidisciplinary, Cardiology etc”. What is the name of the journal in each category? What is the JIF of each journal? State the number of papers from each journal in Covid-19 and Non-Covid-19. We have created a new table (now Table 1) which provides each of these details.

28. Table- you need a new table summarizing key topics raised in each category and numbers in both groups. Given the volume of papers, it would not be feasible to go through each paper to determine key topics as there is not a set way to do this with the WOS search function.

29. Discussion- Poorly written. Discussion reworked to improve fluidity and clarity

30. Why do lines 141-155 have no citations? These lines are in reference to the data accrued from this study. We have added references to the tables for clarity.

31. We need to know which journals were open access and which one was subscription-based paper. No explanation was given to the 10 times issue of open access journals. We know that all papers on Covid-19 were available free of charge and this is an important cause for the high citations of the Covid-19 papers (not discussed). But it does not explain the authors’ claim for 10 times issue (also missing). Table 1 now includes the mode of publication for each journal. In the updated data (Table 3), we have added “Field” as a categorical variable which should help address the 10 times issue and we also added an additional 6 months’ worth of publications which should both help to make the data more logical. We have added the open-access versus subscription-based issue to our limitations as this could impact citations but feel that the recently published large meta-analysis (reference included in response to comment number 5) provides support that there is not clear-cut evidence to suggest that open-access publications will inherently be cited at a greater rate than subscription-based publications.

32. Limitations- Articles are not only research and what is stated is not accurate. Are case reports evidence-based? Talking about evidence-based work- The top in this are Systematic Reviews and meta-analyses. Why were these two groups excluded? Line 191. WOS defines “Article” as “Reports of research on original works. Includes research papers, features, brief communications, case reports, technical notes, chronology, and full papers that were published in a journal and/or presented at a symposium or conference.” Your point that Systematic Reviews and Meta-Analyses are evidence-based work is well-made and these publications fall under the “Review” category for WOS. For the updated data, we included all papers under the “Review” category as well as the “Article” category. We have included a link to the WOS category distinction for reference.

- https://images.webofknowledge.com/images/help/WOS/hs_document_type.html

33. What are these three journals- state their names. For all journals, you must state title, company/publisher, JIF, open-access or subscription-based, country, and the number of issues per year. Show the number of papers for each group. This could be a table. Thank you for this helpful suggestion. Table 1 has been created to consolidate these pieces of information.

34. Conclusion- Should be rewritten. Conclusion was reworked for clarity and fluency

35. References should be improved. References updated for improved clarity and formatting

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

23 Jun 2022

Comparison of citation rates between Covid-19 and non-Covid-19 articles across 24 major scientific journals

PONE-D-22-05834R1

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Reviewers' comments:

18 Jul 2022

PONE-D-22-05834R1

Comparison of citation rates between Covid-19 and non-Covid-19 articles across 24 major scientific journals

Dear Dr. Brandt:

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