Characterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar’s experience
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Date
2022-02-05Author
Bsat, RaghidChemaitelly, Hiam
Coyle, Peter
Tang, Patrick
Hasan, Mohammad R
Al Kanaani, Zaina
Al Kuwari, Einas
Butt, Adeel A
Jeremijenko, Andrew
Kaleeckal, Anvar Hassan
Latif, Ali Nizar
Shaik, Riyazuddin Mohammad
Nasrallah, Gheyath K
Benslimane, Fatiha M
Al Khatib, Hebah A
Yassine, Hadi M
Al Kuwari, Mohamed G
Al Romaihi, Hamad Eid
Al-Thani, Mohamed H
Al Kha, Abdullatif
Bertollini, Roberto
Abu-Raddad, Laith J
Ayoub, Houssein H
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Show full item recordAbstract
Background: The effective reproduction number, Rt, is a tool to track and understand epidemic dynamics. This investigation of Rt estimations was conducted to guide the national COVID-19 response in Qatar, from the onset of the epidemic until August 18, 2021.
Methods: Real-time “empirical” RtEmpirical was estimated using five methods, including the Robert Koch Institute, Cislaghi, Systrom-Bettencourt and Ribeiro, Wallinga and Teunis, and Cori et al. methods. Rt was also estimated using a transmission dynamics model (RtModel-based). Uncertainty and sensitivity analyses were conducted. Agreements between different Rt estimates were assessed by calculating correlation coefficients.
Results: RtEmpirical captured the evolution of the epidemic 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 B.1.1.7 variant. The various estimation methods produced consistent and overall comparable RtEmpirical estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in epidemic dynamics. RtEmpirical 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. RtModel-based correlated strongly with RtEmpirical and provided an average RtEmpirical.
Conclusions: Rt estimations were robust and generated consistent results regardless of the data source or the method of estimation. Findings affirmed an influential role for Rt estimations in guiding national responses to the COVID-19 pandemic, even in resource-limited settings.
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