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Preprinting a pandemic

Jonny A Coates

Institute for Globally Distributed Open Research and Education (IDGORE)

Jonny.coates@igdore.org

@JACoates

jacoates.co.uk

trends, dissemination, and regulation of COVID-19 preprints

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Traditional publishing is slow, requires more data than ever and hinders ECRs

Sekara et al. PNAS 2018 https://doi.org/10.1073/pnas.1800471115

We need to improve speed of knowledge distribution and our means of quality assessment

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Preprints

Preprints are manuscripts shared online before the completion of journal-organized peer review.

Permanent

Versioned

Citable

Fraser et al, 2019 10.1101/673665v1

Not peer reviewed ≠ poor quality

peer reviewed ≠ good quality

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Months - years

~1-2 days

Months - years

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Preprints were almost poised for a pandemic…

In contrast to the slow, laborious traditional publishing methods

Are preprints being used more than normal to communicate COVID-19 science?

What usage are preprint servers experiencing?

What do COVID-19 preprints look like?

How are preprints being shared?

Can we comment on the quality of preprints?

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Are preprints being used more than normal to communicate COVID-19 science?

Scientific community has rapidly responded to the pandemic

  • 30,260 COVID-19 preprints

  • = 25% of all COVID-19 research

  • 10,232 posted to medRxiv + bioRxiv

  • = 23% of all preprints on medRxiv + bioRxiv

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COVID-19 preprints were published at accelerated rates

  • More likely to be published�(21.1% vs 15.4%)�(Chi-square test, p < 0.001)

  • Published more quickly�(median publishing time, �68 days vs 116 days)�(Mann-Whitney test, p < 0.001)

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  • How much more quickly depends on publisher!

  • Greatest estimated difference for AAAS (Science), = 102 days

(two-way ANOVA, preprint type*publisher interaction, F9,5273 = 6.6, p < 0.001)

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The scientific response to the pandemic was rapid – within 1 month of first case

Preprints represent a significant proportion of the COVID-19 literature

Especially early on….

Summary I

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COVID-19 preprints are being accessed and downloaded at unprecedented levels

  • Early COVID-19 preprints viewed 18.2 times and downloaded 27.1 times more than non-COVID-19�(rate ratios from time-adjusted negative binomial GLMs, p < 0.001)

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How are COVID-19 preprints being shared?

COVID-19 preprints are cited, tweeted and covered by news organisations

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Preprints represent a significant proportion of the COVID-19 literature

Labs are posting preprints for the first time directly as a response to the pandemic

COVID-19 preprints are being accessed, downloaded and shared at unprecedented levels – & not just by scientists

Summary II

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  • Top hashtags associated with top 100 most tweeted preprints shows audiences beyond scientific ones ��– including conspiracy theory and nationalist ideologies

But there is a danger to all this sharing as science is hijacked by right-wing media and conspiracy groups

But! Not just preprints, also seen in published, peer reviewed, articles.

Which is more dangerous?

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Can we trust preprints?

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~100 articles

Jan – April 2020 (initial phase of the pandemic)

~100 COVID & 100 Non-COVID articles (total of 400 manuscripts)

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COVID-19 preprints show little change in figure content upon publication

Over 70% (COVID or non-COVID) preprints have figure rearrangements or no changes upon publication

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Over 85% of COVID-19 (>94% of non-COVID-19) abstracts have no significant changes upon publication

6% of non-COVID-19

15% of COVID-19 abstracts undergo a discrete change in key conclusions

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  • Variation is difficult to capture!

  • Following study of reporting standards1, examine change in preprint -> publication

  • Large scale (>30,000) NLP analysis of bioRxiv corpus1

  • Separately investigated our subset

  • Couldn’t readily separate our data from the rest of the corpus – suggesting our dataset is applicable to the wider preprint literature

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1. What are the rates of preprint posting?

2. Who is posting COVID-19 preprints?

3. How are COVID-19 preprints accessed and shared?

4. Are COVID-19 preprints sufficient “quality”?

100 times past epidemics, ¼ of articles

authors from UK, US, China new to preprinting

18 times more views; 27 times more downloads than non-COVID

quality not detectably different to non-COVID, >85% have no significant changes to key conclusions upon publication

sharing work/code on Twitter & posting preprints can lead to collabs!

Preprints have experienced a cultural shift during COVID-19

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From bottom left clockwise:Dr Nicholas Fraser, Leibniz Information Centre for Economics

Dr Liam Brierley, University of Liverpool

Dr Máté Pálfy, Company of Biologists

Dr Gautam Dey, EMBL

Dr Federico Nanni, Alan Turing Institute

Dr Jessica Polka, ASAPbio

Thanks, Grazie, Gracias, danke, Kiitos, Kea leboga, Merci, ob-ree-gah-doh, Asante

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Why preprint?

Gives you more visibility & more citations

Fraser et al, 2019 10.1101/673665v1

Steve Royle, https://quantixed.org/2020/03/30/screenager-screening-times-at-biorxiv/

Can use altmetrics in cover letter to journals to show impact

Screening takes ~1 day

Makes academia more equitable and supports ECRs

https://ecrlife.org/why-you-should-publish-your-work-as-a-preprint-a-conversation-with-dr-prachee-avasthi/

Prachee Avasthi

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  • COVID-19 rate: 39.5 preprints/day
  • Ebola, Zika rates: < 0.3 preprints/day

This significant use of preprints is unique to the COVID-19 pandemic

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So who is publishing all these preprints?

  • Most COVID-19 corresponding authors from US, UK or Chinese institutions
  • First preprints posted close to first cases�(Spearman’s rank, rho = 0.54, p < 0.001)

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Labs shifted expertise to best help with pandemic research

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usage metric

rate ratio

Blogs

3.7

Wikipedia articles

4.5

Tweets

7.6

Comments

11.0

Citations

13.7

News articles

92.8

(all correlations Spearman’s rank rho estimates)

COVID-19 preprints are being widely shared across multiple platforms

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Scientific messages are getting through but significant “hijacking” by right-wing conspiracy groups – and this can be linked to specific preprints

Aerosol and surface stability of HCoV-19 (SARS-CoV-2) compared to SARS-CoV-1

COVID-19 Antibody Seroprevalence in Santa Clara County, California

Nb. This data was sampled earlier than the prev slide

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What do COVID-19 preprints look like?

COVID-19 preprints are shorter than non-COVID-19 preprints

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  • More authors posting preprint for first time among COVID-19 authors�(Bonferroni-adjusted Chi-square tests, *** p < 0.001, ** p < 0.01, * p < 0.05)

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Dark bar = previously posted preprints

Light bar = First time posting preprints

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COVID-19 articles have less data availability and less transparency in peer-review

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COVID-19 preprints published more and in wide-array of journals

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The degree of change is not associated with any specific location or type of change

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Major conclusion changes do not associate with a longer time to publication

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The degree of change does not appear to be impacted by final published journal