Literature DB >> 16395942

Modelling the spread of foot-and-mouth disease in Australia.

M G Garner1, S D Beckett.   

Abstract

Preparedness for an incursion of an exotic animal disease is of key importance to government, industry, producers and the Australian community. An important aspect of Australia's preparedness for a possible incursion of foot-and-mouth disease is investigation into the likely effectiveness and cost-efficiency of eradication strategies when applied to different regional outbreak scenarios. Disease modelling is a tool that can be used to study diseases such as foot-and-mouth disease to better understand potential disease spread and control under different conditions. The Australian Government Department of Agriculture, Fisheries and Forestry has been involved with epidemiologic simulation modelling for more than 10 years, and has developed a sophisticated spatial model for foot-and-mouth disease (AusSpread) that operates within a geographic information system framework. The model accommodates real farm boundary or point-location data, as well as synthesised data based on agricultural census and land use information. The model also allows for interactions between herds or flocks of different animal species and production type, and considers the role that such interactions are likely to play in the epidemiology of a regional outbreak of foot-and-mouth disease. The user can choose mitigations and eradication strategies from those that are currently described in Australia's veterinary emergency plan. The model also allows the user to evaluate the impact of constraints on the availability of resources for mitigations or eradication measures. Outputs include a range of maps and tabulated outbreak statistics describing the geographic extent of the outbreak and its duration, the numbers of affected, slaughtered, and, as relevant, vaccinated herds or flocks, and the cost of control and eradication. Cost-related outputs are based on budgets of the value of stock and the cost of mitigations, each of which can be varied by the user. These outputs are a valuable resource to assist with policy development and disease management.

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Mesh:

Year:  2005        PMID: 16395942     DOI: 10.1111/j.1751-0813.2005.tb11589.x

Source DB:  PubMed          Journal:  Aust Vet J        ISSN: 0005-0423            Impact factor:   1.281


  25 in total

1.  Coping without farm location data during a foot-and-mouth outbreak.

Authors:  Steven Riley
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-08       Impact factor: 11.205

2.  Impact of spatial clustering on disease transmission and optimal control.

Authors:  Michael J Tildesley; Thomas A House; Mark C Bruhn; Ross J Curry; Maggie O'Neil; Justine L E Allpress; Gary Smith; Matt J Keeling
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-01       Impact factor: 11.205

3.  Decision-making for foot-and-mouth disease control: Objectives matter.

Authors:  William J M Probert; Katriona Shea; Christopher J Fonnesbeck; Michael C Runge; Tim E Carpenter; Salome Dürr; M Graeme Garner; Neil Harvey; Mark A Stevenson; Colleen T Webb; Marleen Werkman; Michael J Tildesley; Matthew J Ferrari
Journal:  Epidemics       Date:  2015-12-10       Impact factor: 4.396

4.  Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia.

Authors:  Brendan D Cowled; M Graeme Garner; Katherine Negus; Michael P Ward
Journal:  Vet Res       Date:  2012-01-16       Impact factor: 3.683

5.  Evaluating vaccination strategies to control foot-and-mouth disease: a model comparison study.

Authors:  S E Roche; M G Garner; R L Sanson; C Cook; C Birch; J A Backer; C Dube; K A Patyk; M A Stevenson; Z D Yu; T G Rawdon; F Gauntlett
Journal:  Epidemiol Infect       Date:  2014-07-31       Impact factor: 4.434

6.  Evaluating vaccination strategies to control foot-and-mouth disease: a country comparison study.

Authors:  T G Rawdon; M G Garner; R L Sanson; M A Stevenson; C Cook; C Birch; S E Roche; K A Patyk; K N Forde-Folle; C Dubé; T Smylie; Z D Yu
Journal:  Epidemiol Infect       Date:  2018-05-22       Impact factor: 4.434

7.  Using GIS to create synthetic disease outbreaks.

Authors:  Rochelle E Watkins; Serryn Eagleson; Sam Beckett; Graeme Garner; Bert Veenendaal; Graeme Wright; Aileen J Plant
Journal:  BMC Med Inform Decis Mak       Date:  2007-02-14       Impact factor: 2.796

8.  A Bayesian ensemble approach for epidemiological projections.

Authors:  Tom Lindström; Michael Tildesley; Colleen Webb
Journal:  PLoS Comput Biol       Date:  2015-04-30       Impact factor: 4.475

9.  Serotype-Specific Transmission and Waning Immunity of Endemic Foot-and-Mouth Disease Virus in Cameroon.

Authors:  Laura W Pomeroy; Ottar N Bjørnstad; Hyeyoung Kim; Simon Dickmu Jumbo; Souley Abdoulkadiri; Rebecca Garabed
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

Review 10.  Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America.

Authors:  K M Pepin; E Spackman; J D Brown; K L Pabilonia; L P Garber; J T Weaver; D A Kennedy; K A Patyk; K P Huyvaert; R S Miller; A B Franklin; K Pedersen; T L Bogich; P Rohani; S A Shriner; C T Webb; S Riley
Journal:  Prev Vet Med       Date:  2013-12-01       Impact factor: 2.670

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