Simulation study to explore the suitability of epidemiological designs for COVID-19 vaccine safety studies.

Abstract

During the vaccination stages of the COVID-19 pandemic, researchers used varied study designs to conduct vaccine safety studies. This highlighted the diversity in study designs used by researchersand variance in the results they found, even when their aims were similar. These experiences suggest that establishing a uniform approach in vaccine safety study designs is imperative. This uniformity is vital in providing policymakers with informed guidance regarding vaccine safety quicker and is essential for pandemic preparedness. Our objective is to assess and contrast the applicability of a cohort study versus a self-controlled study design. This comparative analysis aims to pave the way for establishing cohesive and consistent methodologies in future vaccine safety investigations. To accomplish this aim, we propose a Monte Carlo simulation study. We will generate data for two scenarios. The first scenario reflects parameters strongly linked to the outcome of interest, while the second dataset features a randomly distributed prevalence of the outcome within the sample. We will include the parameters age, sex, follow-up time, type of vaccine, number of doses, and unmeasured confounding, to emulate real world data challenges both the study designs face. This data will be analysed in a substantive analysis for bias of the association paramters age, sex, follow-up time, type of vaccine, number of doses, and the unmeasured confounder. The proposed research will span two years, involving tasks such as code writing, code checks, data analysis, internal peer review, and report writing. We have identified potential alternatives to address any challenges that may arise during our planning and research.