Literature DB >> 12798628

Optimising vaccination strategies in equine influenza.

A W Park1, J L N Wood, J R Newton, J Daly, J A Mumford, B T Grenfell.   

Abstract

A stochastic model of equine influenza (EI) is constructed to assess the risk of an outbreak in a Thoroughbred population at a typical flat race training yard. The model is parameterised using data from equine challenge experiments conducted by the Animal Health Trust (relating to the latent and infectious period of animals) and also published data on previous epidemics (to estimate the transmission rate for equine influenza). Using 89 ponies, an empirical relationship between pre-challenge antibody and the probability of becoming infectious is established using logistic regression. Changes in antibody level over time are quantified using published and unpublished studies comprising 618 ponies and horses. A plausible Thoroughbred population is examined over the course of a year and the model is used to assess the risk of an outbreak of EI in the yard under the current minimum vaccination policy in the UK. The model is adapted to consider an alternative vaccination programme where the frequency of vaccination in older horses (2-year-olds and upwards) is increased. Model results show that this practical alternative would offer a significant increase in protection. Spread of infection between yards is also considered to ascertain the risk of secondary outbreaks.

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Year:  2003        PMID: 12798628     DOI: 10.1016/s0264-410x(03)00156-7

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


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

Authors:  M Baguelin; J R Newton; N Demiris; J Daly; J A Mumford; J L N Wood
Journal:  J R Soc Interface       Date:  2009-04-01       Impact factor: 4.118

3.  Influenza A viruses with truncated NS1 as modified live virus vaccines: pilot studies of safety and efficacy in horses.

Authors:  T M Chambers; M Quinlivan; T Sturgill; A Cullinane; D W Horohov; D Zamarin; S Arkins; A García-Sastre; P Palese
Journal:  Equine Vet J       Date:  2009-01       Impact factor: 2.888

Review 4.  A Comprehensive Review on Equine Influenza Virus: Etiology, Epidemiology, Pathobiology, Advances in Developing Diagnostics, Vaccines, and Control Strategies.

Authors:  Raj K Singh; Kuldeep Dhama; Kumaragurubaran Karthik; Rekha Khandia; Ashok Munjal; Sandip K Khurana; Sandip Chakraborty; Yashpal S Malik; Nitin Virmani; Rajendra Singh; Bhupendra N Tripathi; Muhammad Munir; Johannes H van der Kolk
Journal:  Front Microbiol       Date:  2018-09-06       Impact factor: 5.640

5.  Multifocal Equine Influenza Outbreak with Vaccination Breakdown in Thoroughbred Racehorses.

Authors:  Sarah Gildea; Marie Garvey; Pamela Lyons; Rachel Lyons; Jacinta Gahan; Cathal Walsh; Ann Cullinane
Journal:  Pathogens       Date:  2018-04-17

6.  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

Review 7.  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

8.  Estimation models for the morbidity of the horses infected with equine influenza virus.

Authors:  Shigeo Sugita; Hironori Oki; Telhisa Hasegawa; Nobushige Ishida
Journal:  J Equine Sci       Date:  2008-10-24
  8 in total

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