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Estimation of the COVID-19 prevalence and undiagnosed proportion in Canadian provinces (Preprint)


 BACKGROUND
 The development of a successful 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 prevalence and undiagnosed proportion of COVID-19 in Quebec, Ontario, Alberta, and British Columbia, Canada using a model-based approach, informed by provincial data.
 
 
 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 reported provincial data. 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. Those values are 3–6 fold the reported number of diagnosed cases in the provinces.
 
 
 CONCLUSIONS
 Our study extrapolates the estimates of previous COVID-19 seroprevalence studies by integrating a natural history and transmission model with population-level reported data on COVID-19-related health events. This approach provides continuous updates of the COVID-19 period prevalence when no recent seroprevalence data is available. Knowledge of COVID-19 period prevalence can provide vital evidence for policy makers to consider when planning COVID-19 control interventions and vaccination programs.
