What would have happened anyway? Population data source considerations when estimating background incident rates of adverse events following immunisation to inform vaccine safety.

Understanding background incident rates of adverse events following immunisation (AEFI) is essential to rapidly detect, evaluate, respond to, and communicate about vaccine safety concerns, especially for new vaccines. Creating estimates based on geographic specific population level data is increasingly important, as new AEFI presentations will be subject to the same local influences of population demography, exposures, health system variations and level of health care sought. We conducted a retrospective cohort analysis of hospital admissions, emergency department presentations and general practice consultations from 2015 to 2019-before introduction of COVID-19, Mpox or Shingrix vaccination-to estimate background incident rates for 37 conditions considered potential AEFI of special interest (AESI). Background incident rates per 100,000 population were calculated and presented as cases expected to occur coincidentally 1 day, 1 week and 6 weeks post-vaccination, by life-stage age-groups and presenting healthcare setting. We then assessed the proportional contribution of each data source to inform each AESI background rate estimate. 16,437,156 episodes of the 37 AESI were identified. Hospital admissions predominantly informed 19 (51%) of AESI, including exclusively ADEM and CVST; 8 AESI (22%) by primary care, and 10 (27%) a mix. Four AESI (allergic urticaria, Bell's palsy, erythema multiform and sudden death) were better informed by emergency presentations than admissions, but conversely 11 AESI (30%) were not captured in ICD-10 coded emergency presentations at all. Emergent safety concerns are inevitable in population-wide implementation of new vaccines, therefore understanding local background rates aids both safety signal detection as well as maintaining public confidence in vaccination. Hospital and primary care data sources can be interrogated to inform expected background incident rates of adverse events that may occur following vaccination. However, it is necessary to understand which data-source provides best intelligence according to nature of condition and presenting healthcare setting.

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest Hazel J Clothier, Aishwarya N Shetty, Jim P Buttery reports financial support was provided by Department of Health, Victoria. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.