Abstract
Though widely applied in other epidemiological fields, the case-cohort study design has seen little application in the field of vaccinology. Case-cohort studies use probabilistic sampling and reweighting to draw inferences about effects (in this case vaccine efficacy) at the population level in an efficient manner. The SARS-CoV-2 pandemic was met with high vaccine uptake, and high rates of population testing prior to the emergence of Omicron variants of concern, in Ontario, Canada, providing an ideal environment for application of case-cohort methodology. We combined a population-based case line list and vaccination database for the province of Ontario between December 2020 and October 2021. Risk of infection after vaccination was evaluated in all laboratory-confirmed vaccinated SARS-CoV-2 cases, and a 2 % sample of vaccinated controls, evaluated using survival analytic methods, including construction of Cox proportional hazards models. Vaccination status was treated as a time-varying covariate. First and second doses of SARS-CoV-2 vaccine markedly reduced risk of infection (first dose efficacy 68 %, 95 % CI 67 %–69 %; second dose efficacy 88 %, 95 % CI 87–88 %). In multivariable models, extended dosing intervals were associated with lowest risk of breakthrough infection (HR for redosing 0.64 (95 % CI 0.61–0.67) at 6–8 weeks). Heterologous vaccine schedules that mixed viral vector vaccine first doses with mRNA second doses were significantly more effective than mRNA only vaccines. Risk of infection largely vanished during the time period 4–6 months after the second vaccine dose, but rose markedly thereafter. We conclude that a case-cohort design provided an efficient means to identify strong protective effects associated with SARS-CoV-2 vaccination in real time, and also served to quantify the timing and magnitude of infection breakthrough risk in the same cohort. Heterologous vaccination and extended dosing intervals improved the durability of immune response.
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