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Träfflista för sökning "WFRF:(Panovska Griffiths Jasmina) "

Sökning: WFRF:(Panovska Griffiths Jasmina)

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1.
  • Marion, Glenn, et al. (författare)
  • Modelling : Understanding pandemics and how to control them
  • 2022
  • Ingår i: Epidemics. - : Elsevier BV. - 1755-4365 .- 1878-0067. ; 39
  • Tidskriftsartikel (refereegranskat)abstract
    • New disease challenges, societal demands and better or novel types of data, drive innovations in the structure, formulation and analysis of epidemic models. Innovations in modelling can lead to new insights into epidemic processes and better use of available data, yielding improved disease control and stimulating collection of better data and new data types. Here we identify key challenges for the structure, formulation, analysis and use of mathematical models of pathogen transmission relevant to current and future pandemics.
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2.
  • Vegvari, Carolin, et al. (författare)
  • Commentary on the use of the reproduction number R during the COVID-19 pandemic
  • 2022
  • Ingår i: Statistical Methods in Medical Research. - : SAGE Publications. - 0962-2802 .- 1477-0334. ; 31:9, s. 1675-1685
  • Tidskriftsartikel (refereegranskat)abstract
    • Since the beginning of the COVID-19 pandemic, the reproduction number R has become a popular epidemiological metric used to communicate the state of the epidemic. At its most basic, R is defined as the average number of secondary infections caused by one primary infected individual. R seems convenient, because the epidemic is expanding if R>1 and contracting if R<1. The magnitude of R indicates by how much transmission needs to be reduced to control the epidemic. Using R in a naïve way can cause new problems. The reasons for this are threefold: (1) There is not just one definition of R but many, and the precise definition of R affects both its estimated value and how it should be interpreted. (2) Even with a particular clearly defined R, there may be different statistical methods used to estimate its value, and the choice of method will affect the estimate. (3) The availability and type of data used to estimate R vary, and it is not always clear what data should be included in the estimation. In this review, we discuss when R is useful, when it may be of use but needs to be interpreted with care, and when it may be an inappropriate indicator of the progress of the epidemic. We also argue that careful definition of R, and the data and methods used to estimate it, can make R a more useful metric for future management of the epidemic. 
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