Literature DB >> 19364721

Control of equine influenza: scenario testing using a realistic metapopulation model of spread.

M Baguelin1, J R Newton, N Demiris, J Daly, J A Mumford, J L N Wood.   

Abstract

We present a metapopulation model of the spread of equine influenza among thoroughbred horses parametrized with data from a 2003 outbreak in Newmarket, UK. The number of horses initially susceptible is derived from a threshold theorem and a published statistical model. Two simulated likelihood-based methods are used to find the within- and between-yard transmissions using both exponential and empirical latent and infectious periods. We demonstrate that the 2003 outbreak was largely locally driven and use the parametrized model to address important questions of control. The chance of a large epidemic is shown to be largely dependent on the size of the index yard. The impact of poor responders to vaccination is estimated under different scenarios. A small proportion of poor responders strongly influences the efficiency of vaccine policies, which increases risk further when the vaccine and infecting strains differ following antigenic drift. Finally, the use of vaccinating in the face of an outbreak is evaluated at a global and individual management group level. The benefits for an individual horse trainer are found to be substantial, although this is influenced by the behaviour of other trainers.

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Year:  2009        PMID: 19364721      PMCID: PMC2839373          DOI: 10.1098/rsif.2009.0030

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  19 in total

1.  Markov chain Monte Carlo without likelihoods.

Authors:  Paul Marjoram; John Molitor; Vincent Plagnol; Simon Tavare
Journal:  Proc Natl Acad Sci U S A       Date:  2003-12-08       Impact factor: 11.205

2.  Approximate Bayesian computation in population genetics.

Authors:  Mark A Beaumont; Wenyang Zhang; David J Balding
Journal:  Genetics       Date:  2002-12       Impact factor: 4.562

3.  Evidence supporting the inclusion of strains from each of the two co-circulating lineages of H3N8 equine influenza virus in vaccines.

Authors:  Janet M Daly; Philip J Yates; J Richard Newton; Andrew Park; William Henley; James L N Wood; Nick Davis-Poynter; Jennifer A Mumford
Journal:  Vaccine       Date:  2004-09-28       Impact factor: 3.641

4.  Silent spread of H5N1 in vaccinated poultry.

Authors:  Nicholas J Savill; Suzanne G St Rose; Matthew J Keeling; Mark E J Woolhouse
Journal:  Nature       Date:  2006-08-17       Impact factor: 49.962

Review 5.  The equine influenza surveillance program.

Authors:  J A Mumford
Journal:  Adv Vet Med       Date:  1999

6.  Antigenic and genetic evolution of equine H3N8 influenza A viruses.

Authors:  J M Daly; A C Lai; M M Binns; T M Chambers; M Barrandeguy; J A Mumford
Journal:  J Gen Virol       Date:  1996-04       Impact factor: 3.891

7.  Optimising vaccination strategies in equine influenza.

Authors:  A W Park; J L N Wood; J R Newton; J Daly; J A Mumford; B T Grenfell
Journal:  Vaccine       Date:  2003-06-20       Impact factor: 3.641

8.  Description of the outbreak of equine influenza (H3N8) in the United Kingdom in 2003, during which recently vaccinated horses in Newmarket developed respiratory disease.

Authors:  J R Newton; J M Daly; L Spencer; J A Mumford
Journal:  Vet Rec       Date:  2006-02-11       Impact factor: 2.695

9.  Studies with inactivated equine influenza vaccine. 2. Protection against experimental infection with influenza virus A/equine/Newmarket/79 (H3N8).

Authors:  J Mumford; J M Wood; A M Scott; C Folkers; G C Schild
Journal:  J Hyg (Lond)       Date:  1983-06

10.  The effects of strain heterology on the epidemiology of equine influenza in a vaccinated population.

Authors:  A W Park; J L N Wood; J M Daly; J R Newton; K Glass; W Henley; J A Mumford; B T Grenfell
Journal:  Proc Biol Sci       Date:  2004-08-07       Impact factor: 5.349

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  6 in total

1.  Using a computer simulation model to examine the impact of biosecurity measures during a facility-level outbreak of equine influenza.

Authors:  Kelsey L Spence; Terri L O'Sullivan; Zvonimir Poljak; Amy L Greer
Journal:  Can J Vet Res       Date:  2018-04       Impact factor: 1.310

2.  Real-time analysis of the diphtheria outbreak in forcibly displaced Myanmar nationals in Bangladesh.

Authors:  Flavio Finger; Sebastian Funk; Kate White; M Ruby Siddiqui; W John Edmunds; Adam J Kucharski
Journal:  BMC Med       Date:  2019-03-12       Impact factor: 8.775

3.  The effect of the definition of 'pandemic' on quantitative assessments of infectious disease outbreak risk.

Authors:  Benjamin J Singer; Robin N Thompson; Michael B Bonsall
Journal:  Sci Rep       Date:  2021-01-28       Impact factor: 4.379

4.  Transmission of equine influenza virus during an outbreak is characterized by frequent mixed infections and loose transmission bottlenecks.

Authors:  Joseph Hughes; Richard C Allen; Marc Baguelin; Katie Hampson; Gregory J Baillie; Debra Elton; J Richard Newton; Paul Kellam; James L N Wood; Edward C Holmes; Pablo R Murcia
Journal:  PLoS Pathog       Date:  2012-12-20       Impact factor: 6.823

Review 5.  A Systematic Review of Recent Advances in Equine Influenza Vaccination.

Authors:  Romain Paillot
Journal:  Vaccines (Basel)       Date:  2014-11-14

Review 6.  What can mathematical models bring to the control of equine influenza?

Authors:  J M Daly; J R Newton; J L N Wood; A W Park
Journal:  Equine Vet J       Date:  2013-08-02       Impact factor: 2.888

  6 in total

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