Many cultures share common constellations and common narratives about the stars in the night sky. Previous research has shown that this overlap in asterisms, minimal star groupings inside constellations, is clearly present across 22 distinct culture groups and can be explained in part by properties of individual stars (brightness) and properties of pairs of stars (proximity) (Kemp, Hamacher, Little and Cropper, 2022). The same work, however, found no evidence that properties of triples (angle) and quadruples (good continuation) predicted constellation formation. We developed a behavioural experiment to explore how individuals form constellations under conditions that reduce cultural learning. We found that participants independently selected and connected similar stars, and that their responses were predicted by two properties of triples (angle and even spacing) in addition to the properties of brightness and proximity supported by previous work. Our findings lend further evidence to the theory that commonality of constellations across cultures is not a result of shared human history but rather stems from shared human nature.


Visual perception principles in constellation creation in individuals

Vaccine delivery in under-resourced locations with security
risks is not just challenging but also life threatening. The
COVID pandemic and the need to vaccinate added even more
urgency to this issue. Motivated by this problem, we propose
a general framework to set-up limited temporary (vaccination)
centers that balance physical security and desired (vaccine)
service coverage with limited resources. We set-up the
problem as a Stackelberg game between the centers operator
(defender) and an adversary, where the set of centers is not
fixed a priori but is part of the decision output. This results in
a mixed combinatorial and continuous optimization problem.
As part of our scalable approximation solution, we provide a
fundamental contribution by identifying general duality conditions
of switching max and min when both discrete and continuous
variables are involved. Via detailed experiments, we
show that the solution proposed is scalable in practice.

Securing Lifelines: Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach

OBJECTIVE: PCOS is the most common metabolic-endocrine disorder that can impact health and quality of life over a lifespan. It is important we understand the scope of health outcomes that impact the health and quality of life of those with PCOS in order to improve health care in this population. The aim of this study was to determine the incidence of co-morbidities in PCOS compared to an age-matched population. 
METHODS: We conducted a retrospective observational case-control study in those diagnosed with PCOS and age-matched controls using the Alberta Health Services Health Analytics database from 2002-2019 in Alberta, Canada. 
RESULTS: The incidence of high blood pressure, high blood lipids, diseases of the heart, kidney, gastrointestinal tract, pre-diabetes, eating disorders, mental illness, depression-anxiety, rheumatoid arthritis, respiratory infections and all cancers was 20-40% (p<0.0001) higher in PCOS (n=16531) compared to controls (n=49335). Overweight-obesity, non-alcoholic liver disease, Type 1 diabetes (T1D) and T2D had a 3-fold greater incidence in PCOS (p<0.0001). Cardiovascular disease and cerebrovascular disease were 60% higher in PCOS compared to controls (p<0.0001). 
CONCLUSION: These findings indicate PCOS is associated with a significantly greater incidence of co-morbidities and adverse health outcomes. This data provides evidence of the potential economic health care burden and lower quality of life in those with PCOS. The data may also indicate a need to improve education of patients and clinicians in raising awareness of health risks and implementation of preventative health care in this high-risk population. 
This work was funded by the Women and Children’s Health Research Institute and University of Alberta Medical Research Foundation.

PCOS is Associated with Increased Incidence of Co-morbidities in a Canadian Population Cohort

**Objective** The inclusion of duplicate publications in
systematic reviews (SRs) has led to repeated patient
information (RPI).1,2 Repeated patient information in SRs is
the inclusion of a patient’s information multiple times, with
the assumption that they are different participants. This could
result in the overestimation or underestimation of results,
which can lead to substantial clinical implications through
misleading estimates.1
A proportion of studies with shared
timing and location was identified in SRs by evaluating an early-stage sample of COVID-19 SRs. According to the
International Committee of Medical Journal Editors, a
duplicate publication overlaps substantially with a published
article without clear reference to the initial publication.3
The proportion of studies with shared characteristics that could
suggest RPI was assessed in this study.

**Design** This study was an umbrella review of SRs with
clinical data for patients with COVID-19. An experienced
librarian performed a comprehensive search strategy for
peer-reviewed articles in the English language published
between December 1, 2019, and April 6, 2020, in databases
that included Ovid MEDLINE In-Process & Other Non-
Indexed Citations, Ovid MEDLINE, Ovid Embase, Ovid
Cochrane Central Register of Controlled Trials, Ovid
Cochrane Database of Systematic Reviews, and Scopus.
Studies included in SRs were grouped into clusters depending
on characteristics including time frame and location. The
frequency of studies that met the definition of at risk of
including RPI was measured according to shared timing and
location in the same SR.

**Results** Fifteen SRs were included, with a total population of
172,558 participants. A median (IQR) of 9 (6-20) studies were
included in each SR, and 6 (2-10) studies included by each SR
were considered at risk. Of these, 14 (93.3%) had risk of RPI.
Subsequently, 103 clusters were generated. A median (IQR)
of 3 (1-6) at-risk clusters were included in each SR. Eleven
SRs (73.3%) included articles with RPI from a single hospital.

**Conclusions** Risk of RPI was prevalent in COVID-19 SRs
published early in the pandemic, and RPI may also be
common in SRs of topics outside COVID-19. The impact of
RPI on SRs could dilute their validity. Statements about effect
sizes should be made carefully, ensuring studies have
carefully selected their population to include unique
participants. The following are suggestions to improve the
often-complex process of identifying RPI: (1) journals should
ask authors to state if any data have been published and, if so,
to provide a reference; (2) reporting guidelines (CONSORT,
STARD, CARE, STROBE, and PRISMA) should include a
domain asking the authors if any of the data has been
published elsewhere; and (3) the quality assessment tool for
SRs (AMSTAR) should include a domain that evaluates
whether the authors evaluate the inclusion of RPI.

**References**

1. Choi WS, Song SW, Ock SM, et al. Duplicate publication of
articles used in meta-analysis in Korea. SpringerPlus.
2014;3(1):182.
2. von Elm E, Poglia G, Walder B, Tramèr MR. Different
patterns of duplicate publication: an analysis of articles used
in systematic reviews. JAMA. 2004;291(8):974-980.
3. Recommendations for the Conduct, Reporting, Editing,
and Publication of Scholarly work in Medical Journals.
International Committee of Medical Journal Editors. Updated
May 2022. Accessed January 29, 2022. http://icmje.org/
recommendations/

**Conflict of Interest Disclosures** None reported.

**Funding/Support** This study was funded in part by the
intramural research program of the National Institutes of Health.

**Role of the Funder/Sponsor** The sponsor was not involved in
the design or conduct of the study, the preparation of the abstract, or
the decision to submit the abstract.

**Additional Information** Pablo J. Moreno-Peña and Miguel
Zambrano-Lucio share equal credit as co–first authors. Fady
Hannah-Shmouni is a co–corresponding author.

![](https://assets.underline.io/uploads/markdown_image/1/image/120905f0e370a4d658db58c247084fbf.png)

Assessing Repeated Patient Information in Systematic Reviews Published Early in the COVID-19 Pandemic

**Objective** To determine whether COVID-19 restrictions
reduced manuscript submissions during the standard
working day.

**Design** This was a retrospective cohort study of all
submissions from January 2015 to March 2022 to the
Journal of Paediatrics and Child Health, a bimonthly
peer-reviewed medical journal and the official journal of the
Royal Australasian College of Physicians’ Paediatrics and
Child Health Division. The submission time stamps for all
manuscripts submitted by Australia-based authors for which a final editorial decision had been recorded were analyzed.
The first confirmed case of COVID-19 in Australia was
identified in January 2020, and the first COVID-19–related
restrictions were introduced to some Australian states in
March 2020, so the data set was divided into 2 time periods:
before COVID-19 (January 2015 to February 2020 inclusive)
and the COVID-19 era (March 2020 to March 2022
inclusive). Two-tailed t tests were performed to determine the
differences in proportions between the time periods for the
standard working week vs weekends and between standard
working hours (9 am to 5 pm) vs early hours (12 to 8 am) vs late
hours (6 to 11 pm).

**Results** There were a total of 8244 manuscripts submitted to
the journal during this period. Of these, 2167 manuscripts
were submitted by Australia-based researchers, and there
were 2114 manuscripts for which an editorial decision was
recorded (53 under review). A median of 286 manuscripts
were submitted by Australia-based researchers each year.
**Table 83** shows the day and time of manuscript submission.
Before the onset of COVID-19, 89.4% of submissions were
made during the standard working week (Monday through
Friday); during the COVID-19 era, this proportion reduced to
80.5%, although the difference was not statistically significant
(P = .48). Before the onset of COVID-19, 67.3% of
submissions were made during standard working hours (9 am
to 5 pm); during the COVID-19 era, this reduced to 61.5%, but
the difference was not statistically significant (P = .43).
Likewise, the differences in proportion of submissions for the
time periods 12 to 8 am (14.2% vs 16.7%; P = 0.7) and 6 to 11
pm (18.5% vs 21.8%; P = .40) were not statistically significant.

![](https://assets.underline.io/uploads/markdown_image/1/image/b1a7f52efb6115008d72e1199fe01bba.png)

**Conclusions** Most manuscript submissions occurred during
the standard working week and working hours, with no
significant change before and after COVID-19 restrictions.
The day and time of manuscript submission represents only
one aspect of the processes involved in conducting research
and may not correlate to when other parts of research are
performed. However, COVID-19 restrictions are ongoing in
Australia, and their effect on research practices may still be
evolving.

**Acknowledgments** We thank Ms Kate Edmonds and Prof David
Isaacs for their assistance in obtaining the editorial data.

![](https://assets.underline.io/uploads/markdown_image/1/image/51b75ed7256129205772c1fecc88cc4a.png)

Day and Time of Submissions of Manuscripts to the Journal of Paediatrics and Child Health Before and During the COVID-19 Pandemic

**Objective** Due to the pandemic, preprint servers contained
up to 25% more trials, whereas some medical journals
accelerated their editorial processes to ensure the rapid
dissemination of findings.1
Concerns regarding quality and
transparency rose.2
This meta-study assessed the
transparency, completeness, and consistency of COVID-19
reports and whether there was an improvement after journal
peer review.

**Design** The Cochrane COVID-19 Study Register and L·OVE
COVID-19 platform were searched to identify all reports
(preprints or peer-reviewed publications) of randomized
clinical trials (RCTs) assessing pharmacologic interventions
for the treatment of COVID-19, up to May 31, 2021. A
standardized, online data-extraction form was developed.
Data extraction covered general trial characteristics,
transparency indicators (eg, trial registration and data
sharing statement), completeness of reporting (eg, 10 of the
most important Consolidated Standards of Reporting Trials
[CONSORT] 2010 items3
), and changed outcomes between
report and registry (ie, switched outcomes). Two reviewers
were trained and assessed 20 trials separately, with an
agreement of 96.6% and a κ coefficient of 0.87. A third person
resolved disagreements, when needed. A single reviewer
assessed all remaining trials. For all trials published first as a
preprint, a systematic search was performed for a subsequent
publication in peer-reviewed journals, up to October 7, 2021.
In a second step, the peer-reviewed journal publication was
assessed and compared with the matched preprint.

**Results** A total of 251 trial reports were identified: 121
peer-reviewed journal publications (48%) and 130 preprints
(52%). Approximately half of the trials were prospectively
registered (140 [56%]); 38% (n = 95) made their full protocols
or statistical analysis plan available, and 29% (n = 72)
provided access to their statistical analysis plan report. A data
sharing statement was available in 68% of the reports (n =
170); 91% stated their willingness to share. Only 32% of the
trials (n = 81) completely defined the prespecified primary
outcome measures; 57% (n = 143) reported the process of
allocation concealment. Overall, 51% (n = 127) adequately
reported results for the primary outcomes, whereas only 14%
of the trials (n = 36) adequately described harms. Primary
outcome(s) reported in trial registries and published reports
were inconsistent in 49% of the trials (n = 104); only 15% (n =
16) disclosed outcome switching in the report. There were no
major differences between preprints and peer-reviewed
publications. Of the 130 RCTs published as a preprint, 78
were then published in a peer-reviewed journal (median delay to journal publication, 94 days; IQR, 55-168 days). There was
no major improvement after the peer review process.

**Conclusions** Lack of transparency, completeness, and
consistency of reporting are important barriers to trust,
interpretation, and synthesis in COVID-19 clinical trials.
Peer-reviewed publications did not report the items assessed
better than preprints. The comparison of paired reports
published as a preprint and as a peer-reviewed publication
did not indicate major improvements.

**References**

1. Else H. How a torrent of COVID science changed research
publishing—in 7 charts. Nature. 2020;588(7839):553.
doi:10.1038/d41586-020-03564-y
2. Besançon L, Peiffer-Smadja N, Segalas C, et al. Open
science saves lives: lessons from the COVID-19 pandemic.
BMC Med Res Methodol. 2021;221(1):117. doi:10.1186/
s12874-021-01304-y
3. Chauvin A, Ravaud P, Moher D, et al. Accuracy in detecting
inadequate research reporting by early career peer reviewers
using an online CONSORT-based peer-review tool (COBPeer)
versus the usual peer-review process: a cross-sectional
diagnostic study. BMC Med. 2019;17(1):205. doi:10.1186/
s12916-019-1436-0

**Conflict of Interest Disclosures** Isabelle Boutron is a member
of the Peer Review Congress Advisory Board but was not involved
in the editorial review or decision for this abstract. No other
disclosures were reported.

**Funding/Support** This study was part of the COVID-NMA
initiative, which received funding from Université de Paris,
Assistance Publique Hôpitaux de Paris, INSERM, Cochrane France
(Ministry of Health), the French Ministry of Higher Education and
Research, Agence Nationale de la Recherche, and the World Health
Organization.

![](https://assets.underline.io/uploads/markdown_image/1/image/5f2462693a970f13400e34d4d146a2a0.png)

Assessment and Comparison of Preprints and Peer-Reviewed Publications of Reporting Characteristics of Randomized Clinical Trials of Pharmacologic Treatment for COVID-19

**Objective** Transparent, timely results dissemination
prevents bias and reduces waste in clinical research. Global
emergencies, like COVID-19, increase the necessity of timely
and complete reporting.1
The World Health Organization
(WHO) has emphasized the importance of rapid sharing of
clinical data and results during public health emergencies.2
The Dissemination of Registered COVID-19 Clinical Trials
(DIRECCT) project examines how and when COVID-19
clinical trial results are disseminated.

**Design** Trials completed during the first 18 months of the
pandemic on interventions for the treatment and prevention
of acute COVID-19 were examined using the WHO
International Clinical Trials Registry Platform COVID-19
study database. Following a minimum delay of 6 weeks
between trial completion and searches, automated and
manual searches for results publications in PubMed were
conducted using Peer Review of Electronic Search Strategies
(PRESS) for COVID-19 trial publications from the COVID-
evidence project and were supplemented by automated
searches for trial identification numbers in the CORD-19
database, manual checks of trial registries and the Cochrane
COVID-19 Study Register, and manual keyword searches in
trial identification numbers and targeted keywords across
CORD-19, the Cochrane COVID-19 Study Register, PubMed,
Europe PMC, Google Scholar, and Google. Reporting rates
overall and by dissemination route (ie, journal article,
preprint, or registry) were described, and time to report
across routes was evaluated using survival analysis methods.
In addition, data from the registered intervention arms from
all trials were extracted to characterize reporting of the most
commonly studied COVID-19 interventions.

**Results** Overall, 2621 trials completed between January 1,
2020, and June 30, 2021, were included in the analysis
population and searched for results; 1638 (62%) were
searched by 1 author. In the preliminary analysis of the first 6
months of the pandemic (285 trials, all dual searched), 41 trials (14%) had results available by August 15, 2020.3
The
most common dissemination route was preprints (25 trials)
followed by journal articles (18) and registry results (2); of
these, only 4 trials were available as both a preprint and a
journal article. The cumulative incidence of any reporting
surpassed 20% at 119 days from completion.

**Conclusions** COVID-19 trials completed during the first 6
months of the pandemic did not consistently yield rapid
results in the literature or on registries; however, preprints
played an important role in results dissemination. These
preliminary findings suggest results may be appearing more
rapidly compared with clinical trial publication practices
prior to the pandemic. Considering trials completed during
the first 18 months of the pandemic will offer a more
comprehensive picture of trial reporting during COVID-19.
The variable quality of registry data potentially limits the
precision and completeness of these analyses.

**References**
1. Jones CW, Adams AC, Murphy E, et al. Delays in reporting
and publishing trial results during pandemics: cross sectional
analysis of 2009 H1N1, 2014 Ebola, and 2016 Zika clinical
trials. BMC Med Res Methodol. 2021;21:120. doi:10.1186/
s12874-021-01324-8 
 2. World Health Organization. Developing global norms for
sharing data and results during public health emergencies:
statement arising from a WHO consultation held on 1-2
September 2015. Accessed June 20, 2022. http://www.who.int/medicines/ebola-treatment/blueprint_phe_datashare-results/en/ 
 3. Salholz-Hillel M, Grabitz P, Pugh-Jones M, Strech D,
DeVito NJ. Results availability and timeliness of registered
COVID-19 clinical trials: interim cross-sectional results from
the DIRECCT study. BMJ Open. 2021;11(11):e053096.
https://doi.org/10.1136/bmjopen-2021-053096

**Conflict of Interest Disclosures** Maia Salholz-Hillel
is employed as a researcher under grants from the German
Bundesministerium für Bildung und Forschung (BMBF). Outside
the submitted work, Nicholas J. DeVito has received a doctoral
studentship from the Naji Foundation, has received grant support
from the FetzerFranklin Memorial Fund, and has been employed
under grants from the Laura and John Arnold Foundation and Good
Thinking Society. No other disclosures were reported.

**Funding/Support** This project received funding support through
grant FKZ:01KX2021 from the BMBF.

**Role of Funder/Sponsor** The funders had no involvement in the
study design, analysis, or writing of the abstract nor the decision to
submit.

**Additional Contributions** We acknowledge our colleagues on the
Dissemination of Registered COVID-19 Clinical Trials (DIRECCT)
research team who contributed to this project, primarily with
extensive manual searches: Peter Grabitz, Nicole Hildebrand, Molly Pugh-Jones, Susanne Schorr, Tjada Schult, Johannes Schweitering,
and Daniel Strech.

![](https://assets.underline.io/uploads/markdown_image/1/image/8f34fb1fe4526aee680e1b572bc22b68.png)

Results Availability and Timeliness of Registered COVID-19 Clinical Trials During the First 18 Months of the Pandemic

**Objective** To describe study features and publication
characteristics of COVID-19–related clinical trial preprints.

**Design** This was a cross-sectional analysis of COVID-19–
related clinical trials published as preprints. Preprints were
included if they were uploaded between January 1 and
December 31, 2020, to any open-access preprint server
indexed by the National Institutes of Health iSearch
COVID-19 portfolio and described results from a clinical trial
assessing an intervention related to the treatment or
prevention of COVID-19. A single investigator assessed
manuscripts for eligibility by reviewing the titles and
abstracts for all preprints within the iSearch registry, followed
by a full-text review of potentially eligible preprints.
MEDLINE, Google Scholar, and Embase were then searched
to identify peer-reviewed publications matching the included
preprints. Two investigators, including a medical librarian,
independently searched for published articles at least 14
months after the initial preprint posting date. Two
investigators abstracted information from each eligible preprint, including basic study characteristics (location,
funding, size, intervention type), features affecting risk of bias
(prospective registration, allocation method, blinding), and
trial outcome. Descriptive statistics are reported for these
study features, and Cox proportional hazards regression was
used to determine associations between key study
characteristics and peer-reviewed publication status.

**Results** A total of 22,615 preprints were screened for
eligibility and 145 met inclusion criteria. These included
preprints uploaded to 5 different preprint servers (medRxiv,
Research Square, SSRN, preprints.org, and bioRxiv). Funding
sources included government for 65 (45%), industry for 32
(22%), a university or health system for 28 (19%), and a
foundation for 16 (11%). The most commonly assessed
interventions were drugs (86 [59%]), convalescent plasma (19
[13%]), and vaccines (16 [11%]). Median enrollment was 78
participants (IQR, 30-174 participants). Most trials were
registered (136 [94%]), although less than half were
registered prospectively (71 [49%]). Blinding was reported for
participants in 35 trials (24%), investigators and research
staff in 27 (19%), and outcome assessors in 34 (23%). Among
106 trials with more than 1 treatment group, 89 (84%)
randomly allocated participants between treatments.
Matching peer-reviewed publications were identified for 118
of 145 preprints (81%) in 77 different journals. The median
time elapsed between preprint posting and peer-reviewed
publication was 115 days (IQR, 55-201 days). Cox
proportional hazards analysis revealed significant
associations with peer-reviewed publication for government
funding and study size (**Table 67**).

![](https://assets.underline.io/uploads/markdown_image/1/image/d39170fb0e084bd779cf9429d00ed733.png)

**Conclusions** Most COVID-19 clinical trial preprints had
undergone peer-reviewed publication, although delays of
several months were common. A high proportion were not
prospectively registered. Significant associations were not
observed between peer-reviewed publication and study
characteristics related to risk of bias.

**Conflict of Interest Disclosures** Timothy F. Platts-Mills is
an employee of Ophirex. Christopher W. Jones reported receiving
grants from AstraZeneca, Abbott, Vapotherm, and Ophirex.

**Funding/Support** This work was supported by US Department
of Health and Human Services Office of Research Integrity grant
ORIIR200066-01-00.

**Role of the Funder/Sponsor** The sponsor had no role in
the design and conduct of the study; collection, management,
analysis, and interpretation of the data; preparation, review, or
approval of the manuscript; and decision to submit the abstract for
presentation.

**Disclaimer** The contents of this abstract are those of the authors
and do not represent the official views of or an endorsement by
the Office of the Assistant Secretary for Health, US Department of
Health and Human Services, or the US government.

![](https://assets.underline.io/uploads/markdown_image/1/image/539ee98e43e9734c54721e0134206441.png)

Characteristics of COVID-19 Clinical Trial Preprints and Associated Publications

**Objective** High-quality scientific evidence is critical to
support public health decision-making. During public health
emergencies, including the COVID-19 pandemic, the US
Centers for Disease Control and Prevention (CDC) has been
an important source of scientific information. The CDC can
provide timely data on and evidence from fundamental public
health activities, including domestic and international
epidemiologic investigations, laboratory detection, disease
surveillance and research, and other scientific work.1
Routinely, all manuscripts authored by CDC scientists are
reviewed internally for scientific quality before publication
through a rigorous multilevel process involving subject
matter experts and other CDC staff.2
The objective of this
analysis was to understand the CDC’s contributions to new
COVID-19 science.

**Design** A bibliometric analysis was conducted of the CDC’s
COVID-19 public health scientific publications and their effect
from January 20, 2020, to January 20, 2022, using a quality
improvement approach (SQUIRE, version 2.0). COVID-19
scientific articles were cataloged if they had at least 1 CDC-
affiliated author, had been reviewed and cleared internally, and were subsequently published in a peer-reviewed scientific
journal and indexed in the World Health Organization’s
COVID-19 database. The priority topics addressed were
identified according to the CDC’s COVID-19 Public Health
Science Agenda and were assigned tags using keyword scripts
in EndNote, and their scientific effects were assessed using
Scopus citations, news media, social media impressions, and
Altmetric attention scores. This work received a nonresearch
determination from the CDC.

**Results** During the first 2 years of the pandemic, CDC
authors contributed to 1044 unique COVID-19 scientific
publications in 208 journals. The topic areas of focus
commonly included testing (853 publications [82%]);
prevention strategies (658 publications [63%]); natural
history, transmission, breakthrough infections, and
reinfections (587 publications [56%]); vaccines (567
publications [54%]); health equity (308 publications [30%]);
variants (232 publications [22%]); and post–COVID-19
conditions (44 publications [4%]) (**Figure 26**). In addition,
the CDC adapted to changing key scientific questions as the
pandemic evolved, addressing issues including COVID-19
testing expansions; COVID-19 vaccine effectiveness, safety,
duration of protection, and access; emergence of new viral
variants of concern; and improving health equity.3 These
publications were cited 40,427 times in the scientific
literature, have been the topic of 81,921 news media reports
and 1,058,893 social media impressions, and received a
combined total Altmetric attention score of 920,763.
Preprints were not included in this analysis.

![](https://assets.underline.io/uploads/markdown_image/1/image/8328a7ac3f158c522d9971750f0cc3fc.png)

**Conclusions** Throughout the COVID-19 pandemic, the CDC
has supported the development of high-quality science
oriented to improving public health outcomes. The lessons
learned from this evaluation included: (1) the agency’s
COVID-19 Public Health Science Agenda helped guide
scientific activities; (2) scientific manuscripts developed,
reviewed, and published to address priority topics became
highly effective; and (3) the CDC is committed to monitoring
emerging issues and addressing gaps in evidence needed to
improve health outcomes. Data-driven strategies are essential
to address disparities and improve the health outcomes of
people disproportionately affected by COVID-19.

**References**
1. Bunnell R, Ryan J, Kent C; CDC Office of Science, CDC
Excellence in Science Committee. Toward a new strategic
public health science for policy, practice, impact, and health
equity. Am J Public Health. 2021;111(8):1489-1496.
doi:10.2105/AJPH.2021.306355 
 2. Cono J, Jaffe H. The CDC clearance process: supporting
quality science. Am J Public Health. 2015;105(6):e1-e2.
doi:10.2105/AJPH.2015.302691 
 3. Cohn AC, Mahon BE, Walensky RP. One year of COVID-19
vaccines: a shot of hope, a dose of reality. JAMA.
2022;327(2):119-120. doi:10.1001/jama.2021.23962

**Conflict of Interest Disclosures** None reported.

**Funder/Sponsor** The Centers for Disease Control and Prevention
(CDC).

**Role of the Funder/Sponsor** The CDC participated in the design
and conduct of the study; collection, management, analysis, and
interpretation of the data; preparation, review, or approval of the
abstract; and decision to submit the abstract for presentation.

**Disclaimer** The findings and conclusions in this report are those
of the authors and do not necessarily represent the official position
of the CDC.

**Additional Information** Martha Knuth is a co-corresponding
author.

![](https://assets.underline.io/uploads/markdown_image/1/image/32b9f77a362d7354836889d84279860f.png)

COVID-19 Public Health Scientific Publications From the Centers for Disease Control and Prevention, January 2020 to January 2022

**Objective** To assess whether strategies adopted by Brazilian
journals for COVID-19 articles are associated with the
increase of article submission and publication in 2020. Early
assessments of medical journals worldwide since the outbreak
of the pandemic showed that COVID-19–related articles were
published faster than all articles before the pandemic.1

**Design** An online survey was conducted with Brazilian
researchers from October to December 2020. After ethical
approval, a questionnaire with closed questions about the associations of the pandemic with editorial tasks was sent by
email. This analysis included the questionnaires answered by
editors in chief who identified their journal name to assess
whether policies adopted by Brazilian journals were
associated with outcomes for submissions and publications in
the first semester of 2020. Information on journal subject
area, index source, open access status, whether the publisher
was public or private, and charges for submission or
publication was collected from journal websites. The 2021
journal impact factor (JIF) was also collected for all journals.
Adjusted odds ratio (ORs) and 95% CIs were calculated by
logistic regression adjusted by private or public publisher,
charging status, and JIF.

**Results** In total, 1299 Brazilian researchers responded to the
survey. Of 163 editors in chief who participated, 87 (53%)
provided their journal name and were included in the
analysis. Journal subject areas included the humanities (n =
43), life sciences (n = 41), and exact sciences (n = 3). Most
journals were open access (n = 85), one-third were indexed in
Web of Science (n = 29), and a 2021 JIF was available for 18.
Thirty-two publishers were private, and 21 charged for
submission or publication. The scope of 58 journals covered
topics related to COVID-19. Journals that adopted fast-track
publishing had a greater increase in manuscript submissions
(OR, 3.85; 95% CI, 1.42-10.41) and publications (OR, 3.03;
95% CI, 1.20-7.63). Journals that invited manuscripts about
COVID-19 also had a greater increase in submissions (OR,
2.89; 95% CI, 1.13-7.40) and publications (OR, 2.57; 95% CI,
1.03-6.38). The increase in publications was greater in
journals that started to accept articles published as preprints
(OR, 4.26; 95% CI, 1.26-14.38) and that opened a call for
COVID-19 manuscripts (OR, 3.49; 95% CI, 1.22-10.00),
whereas those that published an editorial about COVID-19
had a greater increase in submissions (OR, 2.65; 95% CI,
1.02-6.88). Publishing a dedicated COVID-19 issue did not
affect the outcomes (**Table 68**).

![](https://assets.underline.io/uploads/markdown_image/1/image/e1c0d4e44013775309c43232562e74d9.png)

**Conclusions** Editorial changes in response to the COVID-19
pandemic’s challenges were associated with an increase in thenumber of submissions and publications by Brazilian
journals. These results are limited by the small size and
nonrepresentativeness of the sample.

**Reference**
1. Horbach SPJM. Pandemic publishing: medical journals
strongly speed up their publication process for COVID-19.
Quant Sci Stud. 2020;1(3):1056-1067. doi:10.1162/
qss_a_00076

**Conflict of Interest Disclosures** Luísa von Zuben Veçoso is an
employee of Boehringer Ingelheim in Brazil. The company has no
connection to this work.

**Additional Information** Taís Freire Galvão is a co–
corresponding author.

![](https://assets.underline.io/uploads/markdown_image/1/image/2891dee3e7178148ba5942f2c0be3f92.png)

Brazilian Researchers and Journal Editors Experiences With Scientific Publication During the COVID-19 Pandemic

**Objective** To compare media attention, Twitter engagement,
and citations among COVID-19–related clinical trial preprints
and corresponding peer-reviewed publications. 
 **Design** Preprints of clinical trials were included in this
cross-sectional study if they reported results related to the
treatment or prevention of COVID-19 and were uploaded to
an open access preprint server indexed by the National
Institutes of Health iSearch COVID-19 portfolio in 2020. Two
investigators, including a medical librarian, independently
searched Medline, Google Scholar, and Embase to identify
peer-reviewed publications corresponding to the included
preprints. Altmetric data were used to quantify media
mentions and Twitter interactions within 3 months after
publication for both preprints and peer-reviewed
manuscripts. Citation counts were also recorded using Web of
Science. Descriptive statistics were reported for the included
trials, and linear regression was used to assess associations
between study characteristics and media mentions, Twitter
interactions, and citation counts. 
 **Results** Of 22,615 preprints screened for eligibility, 145 were
included. MedRxiv was the source for most eligible preprints
(n =100; 69%). Peer reviewed publications matching 118 of
145 preprints (81%) were found. Sixty-eight preprints (47%)
received media citations within 3 months of publication
(median [IQR] number of mentions per preprint, 0 [0-9];
maximum mentions, 568), and 118 (81%) had Twitter
interactions (median [IQR] tweets per preprint, 28 [4-202];
maximum mentions, 18,177). One hundred preprints (69%)
were cited in published literature (median [IQR] citations, 2
[0-12]). Among 118 preprints with matching peer-reviewed
publications, Altmetric and citation data were unavailable for
5 (4%). Preprints received more media mentions than the
corresponding peer-reviewed publications in 33 cases (28%),
equal mentions in 38 cases (32%), and fewer media mentions
in 42 cases (36%). Twitter mentions were greater for
preprints than peer-reviewed publications in 54 cases (46%),
equal in 2 (2%), and fewer for 62 (53%). In 26 cases (22%),
preprints received more citations than peer-reviewed
publications; citation counts were equal in 6 cases (5%) and
in 85 cases (72%), the peer-reviewed version received more
citations. Study size, government funding, failure to
prospectively register, and positive study results were most
often associated with increased media mentions, tweets, and
citations (**Table 20**). 
 ![](https://assets.underline.io/uploads/markdown_image/1/image/59664a9a5f5c8dc866bb6ab1f830560e.png) 
 **Conclusions** Although peer-reviewed publications had more
media, Twitter, and citation activity than corresponding
preprints in most cases, it was not uncommon for preprints to
receive more attention than peer-reviewed publications.
Measures of trial reliability or quality were generally not
associated with increases in these metrics. 
 **Conflict of Interest Disclosures** Christopher W. Jones reported
receiving grants from AstraZeneca, Abbott, Vapotherm, and
Ophirex outside the submitted work. Timothy F. Platts-Mills is an
employee of Ophirex. No other disclosures were reported. 
 **Funding/Support** This work was supported by the US
Department of Health and Human Services (HHS) Office of
Research Integrity (grant ORIIR200066-01-00). 
 **Role of the Funder/Sponsor** The sponsor had no role in
the design and conduct of the study; collection, management,
analysis, and interpretation of the data; preparation, review, or
approval of the manuscript; and decision to submit the abstract for
presentation. 
 **Additional Information** The contents of this manuscript are
those of the authors and do not represent the official views of, nor
an endorsement by, the Office of the Assistant Secretary for Health,
the HHS, or the US government. 
 ![](https://assets.underline.io/uploads/markdown_image/1/image/3af6ee0204355a3795cd4012c2ef7123.png)

Media Attention, Twitter Engagement, and Citations of COVID-19 Clinical Trial Preprints and Their Corresponding Peer-Reviewed Publications

**Objective** The COVID-19 pandemic may have signaled a
positive shift in attitudes toward sharing individual-level
patient data (IPD).1 This project aimed to obtain IPD from
trialists of randomized clinical trials (RCTs) of
pharmacological treatments for COVID-19 for the purposes of
conducting an IPD meta-analysis under the COVID-NMA
initiative.2

**Design** This single cohort study evaluated the effectiveness
of accessing IPD from trialists of COVID-19 RCTs through
email requests and online data repositories. Participants were
the corresponding authors of RCTs of pharmacological trials
for the treatment of COVID-19 who published their findings
in a preprint or peer-reviewed journal between March 2020
and May 2021. Corresponding authors were emailed once,
with at least 2 reminders over 9 months (November 2020 to
September 2021) regardless of their data sharing statement.
Online data repositories (including Vivli, Yale University
Open Data Access Project, and ClinicalStudyDataRequest.
com) were also searched. The primary outcome was the
proportion of studies for which IPD were accessed; IPD was
defined as a data set obtained directly from trialists or those
that were made accessible online. The project team
collaborated with Vivli, a global data sharing platform.

**Results** Fifty-six of 229 COVID-19 RCT trialists (24%)
shared their IPD by the end of December 2021. Of these, 18
(32%) declared their positive willingness to share in the
registry and 42 (75%) in their preprint or publication. Of
those trials that did not share their data, 53 (31%) declared
their positive willingness to share in the registry and 100
(58%) in their preprint or publication. Stratified by funding,
trials that shared vs did not share IPD received funding from
sources that were public or nonprofit (shared: 13 [23%]; not
shared: 79 [46%]), private (shared: 10 [18%]; not shared: 36
[21%]), mixed public/nonprofit and private (shared: 20
[36%]; not shared: 37 [21%]), no funding (shared: 11 [20%];
not shared: 10 [6%]), and not reported or unclear (shared: 2
[4%]; not shared: 11 [6%]). Trials that shared vs did not share
IPD were based in high-income countries (shared: 19 [34%];
not shared: 45 [26%]), low- to middle-income countries
(shared: 31 [55%]; not shared: 117 [68%]), and both high-
income and low- to middle-income countries (shared: 6
[11%]; not shared: 11 [6%]).

**Conclusions** Despite the positive shift in attitudes toward
sharing IPD, less than one-quarter of trialists shared their
IPD. Furthermore, data sharing statements often did not line
up with the ability to obtain the data. This study emphasizes
the need to mandate and/or reward timely data sharing while
addressing remaining administrative, resource infrastructure,
and cultural obstacles.

**References**
1. Larson K, Sim I, von Isenburg M, et al. COVID-19
interventional trials: analysis of data sharing intentions
during a time of pandemic. Contemp Clin Trials.
2022;115:106709. doi:10.1016/j.cct.2022.106709 
 2. Boutron I, Chaimani A, Meerpohl JJ, et al; COVID-NMA
Consortium. The COVID-NMA project: building an evidence
ecosystem for the COVID-19 pandemic. Ann Intern Med.
2022;173(12):1015-1017. doi:10.7326/M20-5261

**Conflict of Interest Disclosures** Isabelle Boutron is a member
of the Peer Review Congress Advisory Board but was not involved
in the review or decision for this abstract. No other disclosures were
reported.

**Funding/Support** This study, as part of the COVID-NMA
initiative, received funding from Université de Paris, Assistance
Publique Hôpitaux de Paris, INSERM, Cochrane France (Ministry
of Health), the French Ministry of Higher Education and Research,
Agence Nationale de la Recherche, and the World Health
Organization.

**Additional Information** Isabelle Boutron is a co–corresponding
author.

![](https://assets.underline.io/uploads/markdown_image/1/image/e347bbf33644d08756b4e91337063f86.png)

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