Literature DB >> 3266036

Analytical threshold and stability results on age-structured epidemic models with vaccination.

D Greenhalgh1.   

Abstract

This paper examines mathematical models for common childhood diseases such as measles and rubella and in particular the use of such models to predict whether or not an epidemic pattern of regular recurrent disease incidence will occur. We use age-structured compartmental models which divide the population amongst whom the disease is spreading into classes and use partial differential equations to model the spread of the disease. This paper is particularly concerned with an analytical investigation of the effects of different types of vaccination schemes. We examine possible equilibria and determine the stability of small oscillations about these equilibria. The results are important in predicting the long-term overall level of incidence of disease, in designing immunisation programs and in describing the variations of the incidence of disease about this equilibrium level.

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Year:  1988        PMID: 3266036     DOI: 10.1016/0040-5809(88)90016-0

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  4 in total

1.  Vaccination in density-dependent epidemic models.

Authors:  D Greenhalgh
Journal:  Bull Math Biol       Date:  1992-09       Impact factor: 1.758

2.  Threshold and stability results for an age-structured epidemic model.

Authors:  H Inaba
Journal:  J Math Biol       Date:  1990       Impact factor: 2.259

3.  An SEIV Epidemic Model for Childhood Diseases with Partial Permanent Immunity.

Authors:  Mei Bai; Lishun Ren
Journal:  Comput Math Methods Med       Date:  2015-05-18       Impact factor: 2.238

4.  Endogenous murine microbiota member Faecalibaculum rodentium and its human homologue protect from intestinal tumour growth.

Authors:  Elena Zagato; Chiara Pozzi; Alice Bertocchi; Tiziana Schioppa; Fabiana Saccheri; Silvia Guglietta; Bruno Fosso; Laura Melocchi; Giulia Nizzoli; Jacopo Troisi; Marinella Marzano; Bianca Oresta; Ilaria Spadoni; Koji Atarashi; Sara Carloni; Stefania Arioli; Giulia Fornasa; Francesco Asnicar; Nicola Segata; Simone Guglielmetti; Kenya Honda; Graziano Pesole; William Vermi; Giuseppe Penna; Maria Rescigno
Journal:  Nat Microbiol       Date:  2020-01-27       Impact factor: 17.745

  4 in total

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