The objective of the study was to simulate New Zealand’s foot-and-mouth disease (FMD) operational plan to determine personnel requirements for a FMD response and understand how the numbers of frontline staff available could affect the size and duration of FMD outbreaks, when using stamping-out (SO) measures with or without vaccination. The model utilized a national dataset of all known livestock farms. Each simulation randomly seeded infection into a single farm. Transmission mechanisms included direct and indirect contacts, local and airborne spread. Prior to each simulation, the numbers of personnel for front-line tasks were set randomly. In a random subset of simulations, vaccination was allowed to be deployed as an adjunct to SO. Front-line tasks included contact tracing, surveillance of at-risk farms, depopulation and vaccination using teams comprising personnel of the different types required by New Zealand’s operational plans. The effect of personnel numbers on the size and duration of epidemics were explored using machine learning methods. In the second stage of the study, using a subset of iterations where numbers of personnel were unconstrained, the number of personnel used each day were quantified. When personnel resources were unconstrained, the 95 th percentile and maximum number of infected places (IPs) were 78 and 462 respectively, and the 95 th percentile and maximum duration were 69 and 217 days respectively. However, severe constraints on personnel resources allowed some outbreaks to exceed the size of the UK 2001 FMD epidemic which had 2026 IPs. The number of veterinarians available had a major influence on the size and duration of outbreaks, while the availability of other personnel types did not. A shortage of veterinarians was associated with an increase in time to detect and depopulate IPs, allowing for continued transmission. Emergency vaccination placed a short-term demand for additional staff at the start of the vaccination programme, but the overall number of person days used were similar to SO-only strategies. This study determined the optimal numbers of front-line personnel required to implement the current operational plans to support an FMD response in New Zealand. A shortage of veterinarians was identified as the most influential factor to impact disease control outcomes. Emergency vaccination led to earlier control of an FMD outbreak, but also resulted in a short-term spike in demand for personnel. A successful response needs to have access to sufficient personnel, particularly veterinarians, trained in response roles and available at short notice.

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.