Early decision indicators for foot-and-mouth disease outbreaks in non-endemic countries

Autor: Michael Graeme Garner, Iain East, Mark Stevenson, Robert Sanson, Thomas Rawdon, Richard Bradhurst, Sharon Roche, Pham van Ha, Thomas Kompas
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Frontiers in Veterinary Science, Vol 3 (2016)
Druh dokumentu: article
ISSN: 2297-1769
DOI: 10.3389/fvets.2016.00109
Popis: Disease 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 modelling 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. The study involved two modelling 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 area under control. The number of infected premises, number of pending culls, area under control, 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 area under control had the highest predictive value (R2 = 0.51-0.9) followed by the number of infected premises (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.
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