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

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Audiovestibular adverse events following COVID-19 vaccinations.

INTRODUCTION: Evidence regarding audiovestibular adverse events post COVID-19 vaccination to date has been inconclusive regarding a potential association. This study aimed to determine if there was an increase in audiovestibular events following COVID-19 vaccination in South-eastern Australia during January 2021-March 2023. METHODS: A multi-data source approach was applied. First, a retrospective observational analysis of spontaneous reports of audiovestibular events to a statewide vaccine safety surveillance service, SAEFVIC. Second, a self-controlled case series analysis using general practice data collected via the POpulation Level Analysis and Reporting (POLAR) tool. RESULTS AND CONCLUSIONS: This study is the first to demonstrate an increase in general practice presentations of vertigo following mRNA vaccines (RI = 1.40, P <.001), and tinnitus following both the Vaxzevria® adenovirus vector and mRNA vaccines (RI = 2.25, P <.001 and 1.53, P <.001 respectively). There was no increase in hearing loss following any COVID-19 vaccinations. Our study, however, was unable to account for the potential of concurrent COVID-19 infections, which literature has indicated to be associated with audiovestibular events. Healthcare providers and vaccinees should be alert to potential audiovestibular complaints after COVID-19 vaccination. Our analysis highlights the importance of using large real-world datasets to gather reliable evidence for public health decision making.