This colloquium has been cancelled.
Colloquium Speaker:
Dr. Muhammad Abu Shadeque Mullah, Ph.D.
School of Epidemiology and Public Health, University of Ottawa
Title: A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID-19 hospital and ICU admissions
Abstract: Traditional vaccine effectiveness (VE) studies rely on observational cohorts and require extensive data linkages from administrative datasets. Linking individual-level data can be time-consuming, labor-intensive, and may also raise privacy concerns. We propose statistical methods that leverage aggregated count data from public sources without the need for data linkage. Specifically, we develop a proportional incidence model that estimates VE at the population level using conditional likelihood for aggregated data. Our model assumes that the population counts of clinical outcomes for an infectious disease arise from a superposition of Poisson processes corresponding to different vaccination statuses. We then formulate a log-linear model in terms of relative risk, defined as the ratio between the per capita incidence rates of vaccinated and unvaccinated individuals. In this regression framework, we treat the baseline incidence rate as a nuisance parameter, analogous to the Cox proportional hazards model in survival analysis. We apply the proposed models and methods to age-stratified weekly counts of COVID-19–related hospital and ICU admissions among adults in Ontario, Canada. The study period spans 2021 through February 2022, covering both the Omicron era and the rollout of booster vaccine doses. We also discuss the limitations and confounding effects, while advocating for the necessity of more comprehensive and up-to-date individual-level data that document clinical outcomes and measure potential confounders.
Day & Time: Friday, September 26, 2025, at 3:00pm
Location: Lambton Tower, Room 9-118
Counts toward seminar attendance for MSc and PhD students in Math & Stats.