Abstract
BACKGROUND: The effective reproduction number, R(t) , is a tool to track and understand pandemic dynamics. This investigation of R(t) estimations was conducted to guide the national COVID-19 response in Qatar, from the onset of the pandemic until August 18, 2021. METHODS: Real-time "empirical" R(t) (Empirical) was estimated using five methods, including the Robert Koch Institute, Cislaghi, Systrom-Bettencourt and Ribeiro, Wallinga and Teunis, and Cori et al. methods. R(t) was also estimated using a transmission dynamics model (R(t) (Model-based) ). Uncertainty and sensitivity analyses were conducted. Correlations between different R(t) estimates were assessed by calculating correlation coefficients, and agreements between these estimates were assessed through Bland-Altman plots. RESULTS: R(t) (Empirical) captured the evolution of the pandemic through three waves, public health response landmarks, effects of major social events, transient fluctuations coinciding with significant clusters of infection, and introduction and expansion of the Alpha (B.1.1.7) variant. The various estimation methods produced consistent and overall comparable R(t) (Empirical) estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in pandemic dynamics. R(t) (Empirical) estimates were consistent whether using time series of symptomatic PCR-confirmed cases, all PCR-confirmed cases, acute-care hospital admissions, or ICU-care hospital admissions, to proxy trends in true infection incidence. R(t) (Model-based) correlated strongly with R(t) (Empirical) and provided an average R(t) (Empirical) . CONCLUSIONS: R(t) estimations were robust and generated consistent results regardless of the data source or the method of estimation. Findings affirmed an influential role for R(t) estimations in guiding national responses to the COVID-19 pandemic, even in resource-limited settings.