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Heterogeneity in the onwards transmission risk between local and imported cases affects practical estimates of the time-dependent reproduction number.
Creswell, R; Augustin, D; Bouros, I; Farm, H J; Miao, S; Ahern, A; Robinson, M; Lemenuel-Diot, A; Gavaghan, D J; Lambert, B C; Thompson, R N.
  • Creswell R; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Augustin D; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Bouros I; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Farm HJ; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Miao S; Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK.
  • Ahern A; Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK.
  • Robinson M; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Lemenuel-Diot A; Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel CH-4070, Switzerland.
  • Gavaghan DJ; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Lambert BC; Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
  • Thompson RN; Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.
Philos Trans A Math Phys Eng Sci ; 380(2233): 20210308, 2022 Oct 03.
Article in English | MEDLINE | ID: covidwho-1992465
ABSTRACT
During infectious disease outbreaks, inference of summary statistics characterizing transmission is essential for planning interventions. An important metric is the time-dependent reproduction number (Rt), which represents the expected number of secondary cases generated by each infected individual over the course of their infectious period. The value of Rt varies during an outbreak due to factors such as varying population immunity and changes to interventions, including those that affect individuals' contact networks. While it is possible to estimate a single population-wide Rt, this may belie differences in transmission between subgroups within the population. Here, we explore the effects of this heterogeneity on Rt estimates. Specifically, we consider two groups of infected hosts those infected outside the local population (imported cases), and those infected locally (local cases). We use a Bayesian approach to estimate Rt, made available for others to use via an online tool, that accounts for differences in the onwards transmission risk from individuals in these groups. Using COVID-19 data from different regions worldwide, we show that different assumptions about the relative transmission risk between imported and local cases affect Rt estimates significantly, with implications for interventions. This highlights the need to collect data during outbreaks describing heterogeneities in transmission between different infected hosts, and to account for these heterogeneities in methods used to estimate Rt. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.
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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: Philos Trans A Math Phys Eng Sci Journal subject: Biophysics / Biomedical Engineering Year: 2022 Document Type: Article Affiliation country: Rsta.2021.0308

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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: Philos Trans A Math Phys Eng Sci Journal subject: Biophysics / Biomedical Engineering Year: 2022 Document Type: Article Affiliation country: Rsta.2021.0308