Literature DB >> 12628769

Modeling alternative mitigation strategies for a hypothetical outbreak of foot-and-mouth disease in the United States.

Mark A Schoenbaum1, W Terry Disney.   

Abstract

Alternative mitigation strategies were compared during hypothetical outbreaks of foot-and-mouth disease (FMD) in the USA using a computer-simulation model. The epidemiologic and economic consequences were compared during these simulated outbreaks. Three vaccination and four slaughter strategies were studied along with two speeds of FMD virus spread among three susceptible populations of animals. The populations represented typical animal demographics in the United States. The best strategy depended on the speed of spread of FMD virus and the demographics of the susceptible population. Slaughter of herds in contact with known contagious herds was less costly than slaughtering only contagious herds. Slaughtering in 3 km rings around contagious herds was consistently more costly than other slaughter strategies. Ring vaccination in 10 km rings was judged more costly than slaughter alone in most situations. Although early ring vaccination resulted in lower government costs and duration in fast-spread scenarios, it was more costly when vaccinated animals were slaughtered with indemnity and other related slaughter costs.

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Year:  2003        PMID: 12628769     DOI: 10.1016/s0167-5877(03)00004-7

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  12 in total

1.  Modeling the spread and control of foot-and-mouth disease in Pennsylvania following its discovery and options for control.

Authors:  Michael J Tildesley; Gary Smith; Matt J Keeling
Journal:  Prev Vet Med       Date:  2011-12-12       Impact factor: 2.670

Review 2.  Models of foot-and-mouth disease.

Authors:  Matt J Keeling
Journal:  Proc Biol Sci       Date:  2005-06-22       Impact factor: 5.349

3.  Impacts of Pathogen Introduction Risk on Importer Behavior and Gains from Trade in the Livestock Industry.

Authors:  Katherine D Lee; David Finnoff; Peter Daszak
Journal:  Ecohealth       Date:  2017-12-11       Impact factor: 3.184

4.  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

5.  Economic Assessment of FMDv Releases from the National Bio and Agro Defense Facility.

Authors:  Dustin L Pendell; Thomas L Marsh; Keith H Coble; Jayson L Lusk; Sara C Szmania
Journal:  PLoS One       Date:  2015-06-26       Impact factor: 3.240

6.  Resource Estimations in Contingency Planning for Foot-and-Mouth Disease.

Authors:  Anette Boklund; Sten Mortensen; Maren H Johansen; Tariq Halasa
Journal:  Front Vet Sci       Date:  2017-05-11

7.  Assessment of China's H5N1 routine vaccination strategy.

Authors:  Zhen Sun; Jimin Wang; Zeying Huang
Journal:  Sci Rep       Date:  2017-04-19       Impact factor: 4.379

Review 8.  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

9.  Impact of stakeholders influence, geographic level and risk perception on strategic decisions in simulated foot and mouth disease epizootics in France.

Authors:  Maud Marsot; Séverine Rautureau; Barbara Dufour; Benoit Durand
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

10.  The Effect of the Post 2001 Reforms on FMD Risks of the International Live Animal Trade.

Authors:  David W Shanafelt; C Perrings
Journal:  Ecohealth       Date:  2018-02-27       Impact factor: 3.184

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