Evidence map›Paper›PMID 36308993›Full record

ArticleEpidemics2022

Timeliness of reporting of SARS-CoV-2 seroprevalence results and their utility for infectious disease surveillance.

Claire Donnici, Natasha Ilincic, Christian Cao, Caseng Zhang, Gabriel Deveaux, David Clifton, David Buckeridge, Niklas Bobrovitz, Rahul K Arora

Abstract read
In one paragraph

Article in Epidemics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Designing Surveillance at a Population Level.American journal of public health · 2023
    Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Claire DonniciCumming School of Medicine, University of Calgary, Calgary, AB, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada. Electronic address: claire.donnici@ucalgary.ca.
Natasha IlincicTemerty Faculty of Medicine, University of Toronto, 27 King's College Cir, Toronto, ON, M5S 1A1, Canada.
Christian CaoCumming School of Medicine, University of Calgary, Calgary, AB, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada.
Caseng ZhangFaculty of Health Sciences, McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada.
Gabriel DeveauxCumming School of Medicine, University of Calgary, Calgary, AB, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada.
David CliftonInstitute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Headington, Oxford, OX3 7DQ, UK.
David BuckeridgeFaculty of Medicine and Health Sciences, McGill University, 3605 Rue de la Montagne, Montreal, QC H3G 2M1, Canada.
Niklas BobrovitzCumming School of Medicine, University of Calgary, Calgary, AB, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada; Temerty Faculty of Medicine, University of Toronto, 27 King's College Cir, Toronto, ON, M5S 1A1, Canada.
Rahul K AroraCumming School of Medicine, University of Calgary, Calgary, AB, 3330 Hospital Dr, Calgary, AB, T2N 4N1, Canada; Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Headington, Oxford, OX3 7DQ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Seroprevalence studies have been used throughout the COVID-19 pandemic to monitor infection and immunity. These studies are often reported in peer-reviewed journals, but the academic writing and publishing process can delay reporting and thereby public health action. Seroprevalence estimates have been reported faster in preprints and media, but with concerns about data quality. We aimed to (i) describe the timeliness of SARS-CoV-2 serosurveillance reporting by publication venue and study characteristics and (ii) identify relationships between timeliness, data validity, and representativeness to guide recommendations for serosurveillance efforts. We included seroprevalence studies published between January 1, 2020 and December 31, 2021 from the ongoing SeroTracker living systematic review. For each study, we calculated timeliness as the time elapsed between the end of sampling and the first public report. We evaluated data validity based on serological test performance and correction for sampling error, and representativeness based on the use of a representative sample frame and adequate sample coverage. We examined how timeliness varied with study characteristics, representativeness, and data validity using univariate and multivariate Cox regression. We analyzed 1844 studies. Median time to publication was 154 days (IQR 64-255), varying by publication venue (journal articles: 212 days, preprints: 101 days, institutional reports: 18 days, and media: 12 days). Multivariate analysis confirmed the relationship between timeliness and publication venue and showed that general population studies were published faster than special population or health care worker studies; there was no relationship between timeliness and study geographic scope, geographic region, representativeness, or serological test performance. Seroprevalence studies in peer-reviewed articles and preprints are published slowly, highlighting the limitations of using the academic literature to report seroprevalence during a health crisis. More timely reporting of seroprevalence estimates can improve their usefulness for surveillance, enabling more effective responses during health emergencies.

Indexed as

Communicable DiseasesCOVID-19HumansPandemicsSARS-CoV-2Seroepidemiologic StudiesBibliometricsCOVID-19Infectious diseasePublic health surveillanceReportingSeroprevalence

Identifiers

PMID36308993
PMCPMC9583624

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.