Key result
Early decision indicator triggers predict large foot-and-mouth disease outbreaks with ~100% sensitivity in simulated models.
Why the study?
The study was conducted to define and evaluate an early decision indicator trigger operating within the first 5 weeks of a response to indicate whether a large or long foot-and-mouth disease outbreak was developing, informing control options within an adaptive management framework.
An early decision indicator trigger showed high sensitivity and negative predictive value for detecting large foot-and-mouth disease outbreaks in simulated models, supporting its potential use in adaptive management.
Answers are grounded in this paper and cite their sources.
May aid adaptive management in FMD simulations; leaves open prospective validation before field use.
The objective of the study was to define and then evaluate an early decision indicator (EDI) trigger that operated within the first 5 weeks of a response that would indicate a large and/or long outbreak of FMD was developing, to be able to inform control options within an adaptive management framework. To define the EDI trigger, a previous dataset of 10,000 simulated FMD outbreaks in New Zealand, controlled by the standard stamping-out approach, was re-analysed at various time points between Days 11 and 35 of each response to find threshold values of cumulative detected infected premises (IPs) that indicated upper quartile sized outbreaks and estimated dissemination rate (EDR) values that indicated sustained spread. Both sets of thresholds were then parameterized within the InterSpread Plus modelling framework, such that if either the cumulative IPs or the EDR exceeded the defined thresholds, the EDI trigger would fire. A new series of simulations were then generated. The EDI trigger was like two diagnostic tests interpreted in parallel, with the diagnostic outcome positive if either test was positive at any time point between Days 11 and 35 inclusive. The diagnostic result was then compared to the final size of each outbreak, to see if the outbreak was an upper quartile outbreak in terms of cumulative IPs and/or final duration. The performance of the EDI trigger was then evaluated across the population of outbreaks, and the sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were calculated. The Se, Sp, PPV and NPV for predicting large outbreaks were 0.997, 0.513, 0.404 and 0.998, respectively. The study showed that the EDI trigger was very sensitive to detecting large outbreaks, although not all outbreaks predicted to be large were so, whereas outbreaks predicted to be small invariably were small. Therefore, it shows promise as a mechanism that could support an adaptive management approach to FMD control.
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Sanson et al. (2020) studied Foot-and-mouth disease (FMD) outbreaks (n=10,000). Early decision indicator (EDI) trigger vs. Final outbreak size was evaluated on Predicting large outbreaks (upper quartile sized outbreaks) (Sensitivity 0.997, Specificity 0.513, PPV 0.404, NPV 0.998). An early decision indicator trigger was highly sensitive (0.997) and had a high negative predictive value (0.998) for predicting large foot-and-mouth disease outbreaks in simulated models.
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