Early Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries

被引:16
作者
Garner, Michael G. [1 ]
East, Iain J. [1 ]
Stevenson, Mark A. [2 ]
Sanson, Robert L. [3 ]
Rawdon, Thomas G. [4 ,5 ]
Bradhurst, Richard A. [6 ]
Roche, Sharon E. [1 ]
Pham Van Ha [7 ]
Kompas, Tom [6 ]
机构
[1] Dept Agr & Water Resources, Anim Hlth Policy Branch, Canberra, ACT, Australia
[2] Univ Melbourne, Fac Vet & Agr Sci, Parkville, Vic, Australia
[3] AsureQuality Ltd, Palmerston North, New Zealand
[4] Minist Primary Ind, Invest & Diagnost Ctr, Wellington, New Zealand
[5] Minist Primary Ind, Response Directorate, Wellington, New Zealand
[6] Univ Melbourne, Ctr Excellence Biosecur Risk Anal, Parkville, Vic, Australia
[7] Australian Natl Univ, Crawford Sch Publ Policy, Acton, ACT, Australia
来源
FRONTIERS IN VETERINARY SCIENCE | 2016年 / 3卷
关键词
FMD; early decision indicators; vaccination; simulation models; decision-support; regression analysis;
D O I
10.3389/fvets.2016.00109
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
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 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 (AUG). 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 AUG. 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 AUG had the highest predictive value (R-2 = 0.51-0.9) followed by the number of IPs (R-2 = 0.3-0.75) and outbreak duration (R-2 = 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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页数:14
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