Using Proper Mean Generation Intervals in Modeling of COVID-19

Xiujuan Tang, Salihu S. Musa, Shi Zhao, Shujiang Mei, Daihai He

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Article number691262
Pages (from-to)1-7
Number of pages7
JournalFrontiers in Public Health
Volume9
DOIs
Publication statusPublished - 5 Jul 2021

Keywords

  • COVID-19
  • generation interval
  • infectious period
  • latent period
  • reproduction number

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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