BACKGROUND: The development of a successful coronavirus disease 2019 (COVID-19) control strategy requires a thorough understanding of the trends in the geographic and demographic distributions of the disease burden. In terms of the estimation of the population prevalence, this includes the crucial process of unravelling the number of patients who remain undiagnosed. OBJECTIVE: This study estimates the period prevalence of COVID-19 between March 1, 2020 and November 30, 2020 and the proportion of the infected population that remained undiagnosed for the provinces of Quebec, Ontario, Alberta, and British Columbia in Canada. METHODS: A model-based mathematical framework based on a disease progression and transmission model was developed to estimate the historical prevalence of COVID-19 using provincial-level statistics reporting seroprevalence, diagnoses, and deaths resulting from COVID-19. The framework was applied to three different age cohorts (under 30; 30-69; and 70+) in each of the provinces studied. RESULTS: The estimates of COVID-19 period prevalence between March 1, 2020 to November 30, 2020 were 4.73% (4.42%-4.99%), 2.88% (2.75%-3.02%), 3.27% (2.72%-3.70%), 2.95% (2.77%-3.15%) for Quebec, Ontario, Alberta, and British Columbia, respectively. Among the cohorts considered in this study, the estimated total number of infections ranged from 2-fold the number of diagnoses (among Quebecers aged 70+: 26,476 diagnosed out of a total of 53,549) to 6-fold the number of diagnoses (among British Columbians aged 70+: 3,108 diagnosed out of a total of 18,147). CONCLUSIONS: Our estimates indicated that a high proportion of the population infected between March 1 and November 30, 2020, remained undiagnosed. Knowledge of the COVID-19 period prevalence and undiagnosed population can provide vital evidence for policy makers to consider when planning COVID-19 control interventions and vaccination programs. CLINICALTRIAL: