Informing adaptive management strategies: Evaluating a mechanism to
predict the likely qualitative size of foot-and-mouth disease outbreaks
in New Zealand using data available in the early response phase of
simulated outbreaks
Abstract
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 outbreak of FMD was
developing, in order to be able to inform control options within an
adaptive management framework. To define the 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 11–35 of each response. The two predictive metrics adopted
comprised the mean third quartiles of cumulative numbers of infected
premises (IPs) at weekly time points, and estimated dissemination rate
(EDR) values indicating sustained spread, specifically >
2.0 between days 11-14 or > 1.5 at any time point between
days 15–35 of the response. To evaluate the trigger, the trigger was
parameterized within the InterSpread Plus modelling framework, and a new
series of simulation generated. The trigger was treated like a series of
diagnostic tests that were applied during days 11–35 of each simulated
outbreak, and its results recorded and then compared to the final size
of each outbreak. The performance of the test was then evaluated across
the population of outbreaks, and the sensitivity (Se), specificity (Sp),
positive predictive value (PPV) and negative predictive value (NPV)
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
complex EDI incorporating both the cumulative number of IPs and EDR 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 tool that could
support an adaptive management approach to FMD control.