Evidence map›Paper›PMID 40978508›Full record

ArticleFrontiers in drug safety and regulation2025

A national pharmacovigilance centre perspective on pandemic preparedness -

Florence van Hunsel, Agnes Kant

Abstract read
In one paragraph

Article in Frontiers in drug safety and regulation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Editorial: Pandemic preparedness in vaccine safety and regulation.Frontiers in drug safety and regulation · 2026
    Article
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

2 authors.

Florence van HunselNetherlands Pharmacovigilance Centre Lareb, 'sHertogenbosch, Netherlands.
Agnes KantNetherlands Pharmacovigilance Centre Lareb, 'sHertogenbosch, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 (COVID-19) pandemic highlighted the critical role of pharmacovigilance in ensuring vaccine and drug safety. This perspective from the Netherlands Pharmacovigilance Centre Lareb outlines key experiences and lessons learned during the pandemic. Lareb managed over 233,000 individual case safety reports (ICSRs) related to COVID-19 vaccines, with a considerable proportion submitted by consumers/vaccinated persons directly. Lareb employed both spontaneous reporting and cohort event monitoring (CEM) to gain a better understanding of the safety of these vaccines in a real-world setting. Challenges included the overwhelming volume of data, limited initial access to national vaccination and healthcare registries, underreporting of adverse reactions to SARS-CoV-2 treatments, and a strain on the trained staff to perform tasks while scaling up in personnel. Lareb addressed some challenges through further automation, although more work in this area is still needed. Communication efforts were expanded with a focus on transparency and timeliness. Key recommendations for future pandemic preparedness include investing in Artificial Intelligence for further automation in the reporting process and in signal detection, looking at ways to tackle underreporting for specific associations or medicines in innovative ways and enhancing timely linkage between vaccination and healthcare data. The article underscores the importance of transparent, independent communication and the need for a resilient pharmacovigilance system capable of rapid scale-up during health crises.

Indexed as

adverse drug reaction (ADR)adverse event following immunization (AEFI)COVID-19 vaccinespandemic preparednesspharmacovigilance

Identifiers

PMID40978508
PMCPMC12443082

What OpenQuestion holds

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Registered trials

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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.