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Vaccinations are considered the major tool to curb the current SARS-CoV-2 pandemic. A randomized placebo-controlled trial of the Pfizer BNT162b2 vaccine has demonstrated a 95% efficacy in preventing COVID-19 disease. These results are now corroborated with statistical analyses of real-world vaccination rollouts, but resolving vaccine effectiveness across demographic groups and its interaction with comorbidities is challenging. Here, applying a multivariable logistic regression analysis approach to a large patient-level dataset, including SARS-CoV-2 tests, vaccine inoculations and personalized demographics, we model vaccine effectiveness at daily resolution and its interaction with sex, age and comorbidities. Vaccine effectiveness gradually increased post day 12 of inoculation, then plateaued, around 35 days, reaching 95.0% [CI 93.4%-96.3%] for all infections and 99.5% [CI 97.0%-99.9%] for symptomatic infections. While effectiveness was on average uniform for men and women, it declined mildly but significantly with age especially for males. Effectiveness further declined for people with type 2 diabetes, COPD, and immunosuppression, as well as cardiac disease in females. Quantifying real-world vaccine effectiveness, including both biological and behavioral effects, our analysis provides initial measurement of vaccine effectiveness across demographic groups.