Characterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar's experience
Author | Bsat, Raghid |
Author | Chemaitelly, Hiam |
Author | Coyle, Peter |
Author | Tang, Patrick |
Author | Hasan, Mohammad R. |
Author | Kanaani, Zaina Al |
Author | Kuwari, Einas Al |
Author | Butt, Adeel A. |
Author | Jeremijenko, Andrew |
Author | Kaleeckal, Anvar Hassan |
Author | Latif, Ali Nizar |
Author | Shaik, Riyazuddin Mohammad |
Author | Nasrallah, Gheyath K. |
Author | Benslimane, Fatiha M. |
Author | Khatib, Hebah A.Al |
Author | Yassine, Hadi M. |
Author | Kuwari, Mohamed G.Al |
Author | Romaihi, Hamad Eid Al |
Author | Al-Thani, Mohamed H. |
Author | Khal, Abdullatif Al |
Author | Bertollini, Roberto |
Author | Abu-Raddad, Laith J. |
Author | Ayoub, Houssein H. |
Available date | 2024-07-09T10:13:49Z |
Publication Date | 2022 |
Publication Name | Journal of Global Health |
Identifier | http://dx.doi.org/10.7189/jogh.12.05004 |
Citation | Bsat, R., Chemaitelly, H., Coyle, P., Tang, P., Hasan, M. R., Al Kanaani, Z., ... & Ayoub, H. H. (2022). Characterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar’s experience. Journal of global health, 12. |
ISSN | 2047-2978 |
Abstract | Background The effective reproduction number, Rt, is a tool to track and understand pandemic dynamics. This investigation of Rt 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” 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. Correlations between different Rt estimates were assessed by calculating correlation coefficients, and agreements between these estimates were assessed through Bland-Altman plots. Results RtEmpirical 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 RtEmpirical estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in pandemic dynamics. RtEmpirical estimates were consistent whether using time series of symptomatic PCR-confirmed cases, all PCR-con-firmed cases, acute-care hospital admissions, or ICUcare 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. |
Sponsor | This work was funded by: - Biostatistics, Epidemiology, and Biomathematics Research Core - Ministry of Public Health and Hamad Medical Corporation [12S-0216-190094, 9-040-3-008] - Qatar University and Marubeni [M-QJRC-2020-5] - Qatar Genome Programme - Weill Cornell Medicine-Qatar - Gilead Sciences - Qatar National Research Fund |
Language | en |
Publisher | Edinburgh University Global Health Society |
Subject | Basic Reproduction Number SARS-CoV-2 |
Type | Article |
Volume Number | 12 |
ESSN | 2047-2986 |
Files in this item
This item appears in the following Collection(s)
-
Biomedical Research Center Research [738 items ]
-
Biomedical Sciences [738 items ]
-
Mathematics, Statistics & Physics [740 items ]
-
Public Health [431 items ]