Literature DB >> 11257415

Herd immunity after vaccination: how to quantify it and how to use it to halt disease.

M C De Jong1, A Bouma.   

Abstract

In comparison to unvaccinated individuals, vaccinated individuals have fewer clinical symptoms, reduced susceptibility and reduced infectivity. The first two effects of vaccination can mean that each vaccinated individual is protected against clinical symptoms. From experiments and field trials, the extent of individual protection can be determined by a statistical analysis of the resulting data. In addition, there is an effect of the vaccination on the populations in which one or more individuals are vaccinated. This effect on the population is due to the effects of vaccination on susceptibility and infectivity of the vaccinated individuals. The population effect is called herd immunity and is observed as a reduction in chance of becoming infected when being part of a population with some of the individuals vaccinated. Note that the protection by herd immunity applies to vaccinated individuals as well as to unvaccinated individuals. Thus, protection against disease can be achieved not only by vaccinating the individuals that have to be protected but also by vaccinating other individuals in the same population. Such an application of herd immunity is especially important in protecting farm animals. To plan and evaluate vaccination at the population level, the herd immunity needs to be quantified. It will be illustrated that it is possible, not only theoretically but also practically, to quantify herd immunity among farm animals with data from small-scale experiments as well as with data from field trials.

Mesh:

Year:  2001        PMID: 11257415     DOI: 10.1016/s0264-410x(00)00509-0

Source DB:  PubMed          Journal:  Vaccine        ISSN: 0264-410X            Impact factor:   3.641


  8 in total

1.  The effect of foot-and-mouth disease (FMD) vaccination on virus transmission and the significance for the field.

Authors:  Karin Orsel; Annemarie Bouma
Journal:  Can Vet J       Date:  2009-10       Impact factor: 1.008

2.  Development of a cumulative metric of vaccination adherence behavior and its application among a cohort of 12-month-olds in western Kenya.

Authors:  Casey L Benzaken; Joshua D Miller; Maricianah Onono; Sera L Young
Journal:  Vaccine       Date:  2020-03-14       Impact factor: 3.641

3.  Model-guided fieldwork: practical guidelines for multidisciplinary research on wildlife ecological and epidemiological dynamics.

Authors:  Olivier Restif; David T S Hayman; Juliet R C Pulliam; Raina K Plowright; Dylan B George; Angela D Luis; Andrew A Cunningham; Richard A Bowen; Anthony R Fooks; Thomas J O'Shea; James L N Wood; Colleen T Webb
Journal:  Ecol Lett       Date:  2012-07-19       Impact factor: 9.492

4.  A single vaccination of commercial broilers does not reduce transmission of H5N1 highly pathogenic avian influenza.

Authors:  Okti Poetri; Annemarie Bouma; Ivo Claassen; Guus Koch; Retno Soejoedono; Arjan Stegeman; Michiel van Boven
Journal:  Vet Res       Date:  2011-06-02       Impact factor: 3.683

5.  Impact of viral drift on vaccination dynamics and patterns of seasonal influenza.

Authors:  Yanyu Xiao; Seyed M Moghadas
Journal:  BMC Infect Dis       Date:  2013-12-13       Impact factor: 3.090

6.  Optimal vaccination in a stochastic epidemic model of two non-interacting populations.

Authors:  Edwin C Yuan; David L Alderson; Sean Stromberg; Jean M Carlson
Journal:  PLoS One       Date:  2015-02-17       Impact factor: 3.240

7.  Hitting the Optimal Vaccination Percentage and the Risks of Error: Why to Miss Right.

Authors:  Michael J Harvey; Lisa A Prosser; Mark L Messonnier; David W Hutton
Journal:  PLoS One       Date:  2016-06-22       Impact factor: 3.240

Review 8.  Critical interpretative synthesis of herd immunity for COVID-19 pandemic.

Authors:  Suneela Garg; Meghachandra M Singh; Chetana Prakash Deshmukh; Nidhi Bhatnagar; Amod L Borle; Raman Kumar
Journal:  J Family Med Prim Care       Date:  2021-04-08
  8 in total

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