Literature DB >> 33721104

A non-parametric method for determining epidemiological reproduction numbers.

Frank P Pijpers1.   

Abstract

In the spreading of infectious diseases, an important number to determine is how many other people will be infected on average by anyone who has become infected themselves. This is known as the reproduction number. This paper describes a non-parametric inverse method for extracting the full transfer function of infection, of which the reproduction number is the integral. The method is demonstrated by applying it to the timeline of hospitalisation admissions for covid-19 in the Netherlands up to May 20 2020, which is publicly available from the site of the Dutch National Institute of Public Health and the Environment (rivm.nl).

Entities:  

Keywords:  Covid-19; Estimation techniques; Infectious diseases; Reproduction number; Transmission

Mesh:

Year:  2021        PMID: 33721104      PMCID: PMC7958596          DOI: 10.1007/s00285-021-01590-6

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  2 in total

1.  Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation.

Authors:  Chang Sun; Serge Richard; Takemasa Miyoshi; Naohiro Tsuzu
Journal:  J Clin Med       Date:  2022-04-25       Impact factor: 4.964

2.  The discrete-time Kermack-McKendrick model: A versatile and computationally attractive framework for modeling epidemics.

Authors:  Odo Diekmann; Hans G Othmer; Robert Planqué; Martin C J Bootsma
Journal:  Proc Natl Acad Sci U S A       Date:  2021-09-28       Impact factor: 11.205

  2 in total

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