Literature DB >> 19475453

On the final size of epidemics with seasonality.

Nicolas Bacaër1, M Gabriela M Gomes.   

Abstract

We first study an SIR system of differential equations with periodic coefficients describing an epidemic in a seasonal environment. Unlike in a constant environment, the final epidemic size may not be an increasing function of the basic reproduction number R(0) or of the initial fraction of infected people. Moreover, large epidemics can happen even if R(0) < 1. But like in a constant environment, the final epidemic size tends to 0 when R(0) < 1 and the initial fraction of infected people tends to 0. When R(0) > 1, the final epidemic size is bigger than the fraction 1 - 1/R(0) of the initially nonimmune population. In summary, the basic reproduction number R(0) keeps its classical threshold property but many other properties are no longer true in a seasonal environment. These theoretical results should be kept in mind when analyzing data for emerging vector-borne diseases (West-Nile, dengue, chikungunya) or air-borne diseases (SARS, pandemic influenza); all these diseases being influenced by seasonality.

Entities:  

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Year:  2009        PMID: 19475453     DOI: 10.1007/s11538-009-9433-7

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  17 in total

1.  On the biological interpretation of a definition for the parameter R₀ in periodic population models.

Authors:  Nicolas Bacaër; El Hadi Ait Dads
Journal:  J Math Biol       Date:  2011-10-11       Impact factor: 2.259

2.  Genealogy with seasonality, the basic reproduction number, and the influenza pandemic.

Authors:  Nicolas Bacaër; El Hadi Ait Dads
Journal:  J Math Biol       Date:  2010-07-06       Impact factor: 2.259

3.  Stochastic epidemic models with random environment: quasi-stationarity, extinction and final size.

Authors:  J R Artalejo; A Economou; M J Lopez-Herrero
Journal:  J Math Biol       Date:  2012-08-15       Impact factor: 2.259

4.  A century of transitions in New York City's measles dynamics.

Authors:  Karsten Hempel; David J D Earn
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

5.  On the probability of extinction in a periodic environment.

Authors:  Nicolas Bacaër; El Hadi Ait Dads
Journal:  J Math Biol       Date:  2012-11-10       Impact factor: 2.259

6.  Determination of optimal vaccination strategies using an orbital stability threshold from periodically driven systems.

Authors:  Nelson Owuor Onyango; Johannes Müller
Journal:  J Math Biol       Date:  2013-02-14       Impact factor: 2.259

7.  Deux modèles de population dans un environnement périodique lent ou rapide.

Authors:  Nicolas Bacaër
Journal:  J Math Biol       Date:  2019-11-19       Impact factor: 2.259

8.  Cholera modeling: challenges to quantitative analysis and predicting the impact of interventions.

Authors:  Yonatan H Grad; Joel C Miller; Marc Lipsitch
Journal:  Epidemiology       Date:  2012-07       Impact factor: 4.822

9.  Breaking the waves: modelling the potential impact of public health measures to defer the epidemic peak of novel influenza A/H1N1.

Authors:  Matthias An der Heiden; Udo Buchholz; Gérard Krause; Göran Kirchner; Hermann Claus; Walter H Haas
Journal:  PLoS One       Date:  2009-12-21       Impact factor: 3.240

Review 10.  The role of environmental variables on Aedes albopictus biology and chikungunya epidemiology.

Authors:  Joanna Waldock; Nastassya L Chandra; Jos Lelieveld; Yiannis Proestos; Edwin Michael; George Christophides; Paul E Parham
Journal:  Pathog Glob Health       Date:  2013-07       Impact factor: 2.894

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