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A new estimation method for COVID-19 time-varying reproduction number using active cases.
Hasan, Agus; Susanto, Hadi; Tjahjono, Venansius; Kusdiantara, Rudy; Putri, Endah; Nuraini, Nuning; Hadisoemarto, Panji.
  • Hasan A; Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Alesund, Norway. agus.hasan@ntnu.no.
  • Susanto H; Department of Mathematics, Khalifa University, Abu Dhabi, United Arab Emirates.
  • Tjahjono V; Department of Mathematical Sciences, University of Essex, Colchester, UK.
  • Kusdiantara R; Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
  • Putri E; Department of Mathematics, Institut Teknologi Bandung, Bandung, Indonesia.
  • Nuraini N; Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
  • Hadisoemarto P; Department of Mathematics, Institut Teknologi Bandung, Bandung, Indonesia.
Sci Rep ; 12(1): 6675, 2022 04 23.
Article in English | MEDLINE | ID: covidwho-1805656
ABSTRACT
We propose a new method to estimate the time-varying effective (or instantaneous) reproduction number of the novel coronavirus disease (COVID-19). The method is based on a discrete-time stochastic augmented compartmental model that describes the virus transmission. A two-stage estimation method, which combines the Extended Kalman Filter (EKF) to estimate the reported state variables (active and removed cases) and a low pass filter based on a rational transfer function to remove short term fluctuations of the reported cases, is used with case uncertainties that are assumed to follow a Gaussian distribution. Our method does not require information regarding serial intervals, which makes the estimation procedure simpler without reducing the quality of the estimate. We show that the proposed method is comparable to common approaches, e.g., age-structured and new cases based sequential Bayesian models. We also apply it to COVID-19 cases in the Scandinavian countries Denmark, Sweden, and Norway, where the positive rates were below 5% recommended by WHO.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-10723-w

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-10723-w