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AuthorBsat, Raghid
AuthorChemaitelly, Hiam
AuthorCoyle, Peter
AuthorTang, Patrick
AuthorHasan, Mohammad R
AuthorAl Kanaani, Zaina
AuthorAl Kuwari, Einas
AuthorButt, Adeel A
AuthorJeremijenko, Andrew
AuthorKaleeckal, Anvar Hassan
AuthorLatif, Ali Nizar
AuthorShaik, Riyazuddin Mohammad
AuthorNasrallah, Gheyath K
AuthorBenslimane, Fatiha M
AuthorAl Khatib, Hebah A
AuthorYassine, Hadi M
AuthorAl Kuwari, Mohamed G
AuthorAl Romaihi, Hamad Eid
AuthorAl-Thani, Mohamed H
AuthorAl Kha, Abdullatif
AuthorBertollini, Roberto
AuthorAbu-Raddad, Laith J
AuthorAyoub, Houssein H
Available date2022-02-09T07:34:35Z
Publication Date2022-02-05
Publication NameJournal of Global Health
Identifierhttp://dx.doi.org/10.1101/2021.10.07.21264599
CitationBsat R, Chemaitelly H, Coyle P, Tang P, Hasan MR, Al Kanaani A, Al Kuwari E, Butt AA, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Nasrallah GK, Benslimane FM, Al Khatib HA, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Al Khal A, Bertollini R, Abu-Raddad LJ, Ayoub HH. Characterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar’s experience. J Glob Health 2022;12:05004.
ISSN2047-2978
URIhttp://hdl.handle.net/10576/26589
AbstractBackground: 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.
SponsorHHA and RB acknowledge the joint support of Qatar University and Marubeni M-QJRC-2020-5. The authors are grateful for support provided by the Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core, both at Weill Cornell Medicine-Qatar, as well as for support provided by the Ministry of Public Health and Hamad Medical Corporation. The developed mathematical models were made possible by NPRP grant number 9-040-3-008 (Principal investigator: LJA) and NPRP grant number 12S-0216-190094 (Principal investigator: LJA) from the Qatar National Research Fund (a member of Qatar Foundation; https://www.qnrf.org). The authors are also grateful for the Qatar Genome Programme for institutional support for the reagents needed for the viral genome sequencing. The statements made herein are solely the responsibility of the authors. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Languageen
PublisherInternational Society of Global Health
SubjectCOVID-19
SARS-CoV-2
TitleCharacterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar’s experience
TypeArticle
ESSN2047-2986


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