Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

EARLY DECISION INDICATORS FOR FOOT AND MOUTH DISEASE OUTBREAKS IN NON ENDEMIC COUNTRIES

dc.contributor.authorGarner, Michael
dc.contributor.authorEast, Iain
dc.contributor.authorStevenson, Mark
dc.contributor.authorSanson, Robert L.
dc.contributor.authorRawdon, Thomas G.
dc.contributor.authorBradhurst, Richard A.
dc.contributor.authorRoche, Sharon
dc.contributor.authorPham, Van (Ha)
dc.contributor.authorKompas, Tom
dc.date.accessioned2018-11-29T22:57:22Z
dc.date.available2018-11-29T22:57:22Z
dc.date.issued2016
dc.date.updated2018-11-29T08:17:31Z
dc.description.abstractDisease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot-and-mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited. A modeling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration, and the total area under control (AUC). The study involved two modeling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree, and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration, and the total AUC. The number of infected premises (IPs), number of pending culls, AUC, estimated dissemination ratio, and cattle density around the index herd at days 7, 14, and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the AUC had the highest predictive value (R2 = 0.51–0.9) followed by the number of IPs (R2 = 0.3–0.75) and outbreak duration (R2 = 0.28–0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85–0.98 and negative predictive values of 0.52–0.91, with 79–97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations. Our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions.
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2297-1769
dc.identifier.urihttp://hdl.handle.net/1885/153844
dc.publisherFrontiers Research Foundation
dc.sourceFrontiers in Veterinary Science
dc.titleEARLY DECISION INDICATORS FOR FOOT AND MOUTH DISEASE OUTBREAKS IN NON ENDEMIC COUNTRIES
dc.typeJournal article
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.issue109
local.bibliographicCitation.lastpage109
local.bibliographicCitation.startpage109
local.contributor.affiliationGarner, Michael, Commonwealth Department of Agriculture, Fisheries and Forestry
local.contributor.affiliationEast, Iain, DAFF
local.contributor.affiliationStevenson, Mark, University of Melbourne
local.contributor.affiliationSanson, Robert L., AsureQuality Limited
local.contributor.affiliationRawdon, Thomas G., Ministry of Primary Industries, Wellington
local.contributor.affiliationBradhurst, Richard A., University of Melbourne
local.contributor.affiliationRoche, Sharon, Government Department of Agriculture, Fisheries and Forestry
local.contributor.affiliationPham, Van (Ha), College of Asia and the Pacific, ANU
local.contributor.affiliationKompas, Tom, University of Melbourne
local.contributor.authoruidPham, Van (Ha), u3207038
local.description.notesImported from ARIES
local.identifier.absfor110309 - Infectious Diseases
local.identifier.ariespublicationu4430637xPUB470
local.identifier.citationvolume3
local.identifier.doi10.3389/fvets.2016.00109
local.identifier.thomsonIDMEDLINE:27965969
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
01_Garner_EARLY_DECISION_INDICATORS_FOR_2016.pdf
Size:
1.06 MB
Format:
Adobe Portable Document Format