Your browser doesn't support javascript.
Characterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar's experience.
Bsat, Raghid; Chemaitelly, 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 Khal, Abdullatif; Bertollini, Roberto; Abu-Raddad, Laith J; Ayoub, Houssein H.
  • Bsat R; Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar.
  • Chemaitelly H; Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.
  • Coyle P; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar.
  • Tang P; Hamad Medical Corporation, Doha, Qatar.
  • Hasan MR; Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar.
  • Al Kanaani Z; Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom.
  • Al Kuwari E; Department of Pathology, Sidra Medicine, Doha, Qatar.
  • Butt AA; Department of Pathology, Sidra Medicine, Doha, Qatar.
  • Jeremijenko A; Hamad Medical Corporation, Doha, Qatar.
  • Kaleeckal AH; Hamad Medical Corporation, Doha, Qatar.
  • Latif AN; Hamad Medical Corporation, Doha, Qatar.
  • Shaik RM; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA.
  • Nasrallah GK; Hamad Medical Corporation, Doha, Qatar.
  • Benslimane FM; Hamad Medical Corporation, Doha, Qatar.
  • Al Khatib HA; Hamad Medical Corporation, Doha, Qatar.
  • Yassine HM; Hamad Medical Corporation, Doha, Qatar.
  • Al Kuwari MG; Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar.
  • Al Romaihi HE; Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar.
  • Al-Thani MH; Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar.
  • Al Khal A; Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar.
  • Bertollini R; Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar.
  • Abu-Raddad LJ; Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar.
  • Ayoub HH; Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar.
J Glob Health ; 12: 05004, 2022.
Article in English | MEDLINE | ID: covidwho-1687376
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" Rt Empirical 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 (Rt Model-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:

Rt 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 Rt Empirical estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in pandemic dynamics. Rt 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. Rt Model-based correlated strongly with Rt Empirical and provided an average Rt Empirical .

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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study Topics: Variants Limits: Humans Country/Region as subject: Asia Language: English Journal: J Glob Health Year: 2022 Document Type: Article Affiliation country: Jogh.12.05004

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study Topics: Variants Limits: Humans Country/Region as subject: Asia Language: English Journal: J Glob Health Year: 2022 Document Type: Article Affiliation country: Jogh.12.05004