Methodological frontiers in vaccine safety: Qualifying available evidence for rare events, use of distributed data networks to monitor vaccine safety issues, and monitoring the safety of pregnancy interventions

Caitlin Dodd*, Nick Andrews, Helen Petousis-Harris, Miriam Sturkenboom, Saad B. Omer, Steven Black

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
12 Downloads (Pure)

Abstract

While vaccines are rigorously tested for safety and efficacy in clinical trials, these trials do not include enough subjects to detect rare adverse events, and they generally exclude special populations such as pregnant women. It is therefore necessary to conduct postmarketing vaccine safety assessments using observational data sources. The study of rare events has been enabled in through large linked databases and distributed data networks, in combination with development of case-centred methods. Distributed data networks necessitate common protocols, definitions, data models and analytics and the processes of developing and employing these tools are rapidly evolving. Assessment of vaccine safety in pregnancy is complicated by physiological changes, the challenges of mother-child linkage and the need for long-term infant follow-up. Potential sources of bias including differential access to and utilisation of antenatal care, immortal time bias, seasonal timing of pregnancy and unmeasured determinants of pregnancy outcomes have yet to be fully explored. Available tools for assessment of evidence generated in postmarketing studies may downgrade evidence from observational data and prioritise evidence from randomised controlled trials. However, real-world evidence based on real-world data is increasingly being used for safety assessments, and new tools for evaluating real-world evidence have been developed. The future of vaccine safety surveillance, particularly for rare events and in special populations, comprises the use of big data in single countries as well as in collaborative networks. This move towards the use of real-world data requires continued development of methodologies to generate and assess real world evidence.

Original languageEnglish
Article numbere003540
Number of pages9
JournalBMJ Global Health
Volume6
Issue numberSUPPL_2
Early online date19 May 2021
DOIs
Publication statusE-pub ahead of print - 19 May 2021

Bibliographical note

Funding Information: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Open Access: This is an open access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial.

Publisher Copyright: © Author(s) (or their employer(s)) 2021.

Citation: Dodd C, Andrews N, Petousis-Harris H, et al. Methodological frontiers in vaccine safety: qualifying available evidence for rare events, use of distributed data networks to monitor vaccine safety issues, and monitoring the safety of pregnancy interventions. BMJ Global Health 2021;6:e003540.

DOI: 10.1136/bmjgh-2020-003540

Keywords

  • Epidemiology
  • Review
  • Vaccines

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