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Using Proper Mean Generation Intervals in Modeling of COVID-19.
Tang, Xiujuan; Musa, Salihu S; Zhao, Shi; Mei, Shujiang; He, Daihai.
  • Tang X; Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
  • Musa SS; Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China.
  • Zhao S; Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria.
  • Mei S; The Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
  • He D; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China.
Front Public Health ; 9: 691262, 2021.
Article in English | MEDLINE | ID: covidwho-1320592
ABSTRACT
In susceptible-exposed-infectious-recovered (SEIR) epidemic models, with the exponentially distributed duration of exposed/infectious statuses, the mean generation interval (GI, time lag between infections of a primary case and its secondary case) equals the mean latent period (LP) plus the mean infectious period (IP). It was widely reported that the GI for COVID-19 is as short as 5 days. However, many works in top journals used longer LP or IP with the sum (i.e., GI), e.g., >7 days. This discrepancy will lead to overestimated basic reproductive number and exaggerated expectation of infection attack rate (AR) and control efficacy. We argue that it is important to use suitable epidemiological parameter values for proper estimation/prediction. Furthermore, we propose an epidemic model to assess the transmission dynamics of COVID-19 for Belgium, Israel, and the United Arab Emirates (UAE). We estimated a time-varying reproductive number [R0(t)] based on the COVID-19 deaths data and we found that Belgium has the highest AR followed by Israel and the UAE.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia / Europa Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.691262

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia / Europa Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.691262