M.G. Garner

Evaluating the effectiveness of early vaccination in the control and eradication of equine influenza—A modelling approach

In August 2007, Australia which had previously been free of equine influenza, experienced a large outbreak that lasted approximately 4 months before it was eradicated. The outbreak required a significant national response by government and the horse industries. The main components of the response were movement controls, biosecurity measures, risk-based zoning and, subsequently, vaccination to contain the outbreak. Although not initially used, vaccination became a key element in the eradication program, with approximately 140000 horses vaccinated. Vaccination is recognised as a valuable tool for managing EI in endemically infected countries but there is little experience using it in situations where the objective is disease eradication. Vaccination was undoubtedly an important factor in 2007 as it enabled movements of some horses and associated industry activities to recommence. However, its contribution to containment and eradication is less clear. A premises-level equine influenza model, based on an epidemiological analysis of the 2007 outbreak, was developed to evaluate effectiveness of the mitigation strategies used and to investigate whether vaccination, if applied earlier, would have had an effect on the course of the outbreak. The results indicate that early use of strategic vaccination could have significantly reduced the size of the outbreak. The four vaccination strategies evaluated had, by 1 month into the control program, reduced the number of new infections on average by 60% and the size of the infected area by 8-9%. If resources are limited, a 1 km suppressive ring vaccination around infected premises gave the best results, but with greater vaccination capacity, a 3 km ring vaccination was the most effective strategy. The findings suggest that as well as reducing clinical and economic impacts, vaccination when used with biosecurity measures and movement controls could play an important role in the containment and eradication of equine influenza.

A comparison of predictions made by three simulation models of foot-and-mouth disease.

Abstract AIMS: To describe results of a relative validation exercise using the three simulation models of foot-and-mouth disease (FMD) in use by the quadrilateral countries (QUADS; Australia, Canada, New Zealand, and United States of America; USA). METHODS: A hypothetical population of farms was constructed and, following the introduction of an FMD-like disease into a single farm, spread of disease was simulated using each of the three FMD simulation models used by the QUADS countries. A series of 11 scenarios was developed to systematically evaluate the key processes of disease transmission and control used by each of the three models. The predicted number of infected units and the size of predicted outbreak areas for each scenario and each model were compared using the Kruskal-Wallis test. Agreement among the three models in terms of geographical areas predicted to become infected were quantified using Fleiss Kappa statistic. RESULTS: Although there were statistically significant differences in model outputs in terms of the numbers of units predicted to become infected, the temporal onset of infection throughout the simulation period, and the spatial distribution of infected units, these differences were generally small and would have resulted in the same (or similar) management decisions being adopted in each case. CONCLUSIONS: Agreement among the three models in terms of the numbers of premises predicted to become infected, the temporal onset of infection throughout the simulation period, and the spatial distribution of infected premises provides evidence that each of the model developers are consistent in their approach to simulating the spread of disease throughout a population of susceptible individuals. This consistency implies that the assumptions taken by each development team are appropriate, which in turn serves to increase end-user confidence in model predictions. CLINICAL RELEVANCE: Relative validation is one of a number of steps that can be undertaken to increase end-user confidence in predictions made by infectious disease models.

Evaluating vaccination strategies to control foot-and-mouth disease: a model comparison study.

Simulation models can offer valuable insights into the effectiveness of different control strategies and act as important decision support tools when comparing and evaluating outbreak scenarios and control strategies. An international modelling study was performed to compare a range of vaccination strategies in the control of foot-and-mouth disease (FMD). Modelling groups from five countries (Australia, New Zealand, USA, UK, The Netherlands) participated in the study. Vaccination is increasingly being recognized as a potentially important tool in the control of FMD, although there is considerable uncertainty as to how and when it should be used. We sought to compare model outputs and assess the effectiveness of different vaccination strategies in the control of FMD. Using a standardized outbreak scenario based on data from an FMD exercise in the UK in 2010, the study showed general agreement between respective models in terms of the effectiveness of vaccination. Under the scenario assumptions, all models demonstrated that vaccination with stamping-out of infected premises led to a significant reduction in predicted epidemic size and duration compared to the stamping-out strategy alone. For all models there were advantages in vaccinating cattle-only rather than all species, using 3-km vaccination rings immediately around infected premises, and starting vaccination earlier in the control programme. This study has shown that certain vaccination strategies are robust even to substantial differences in model configurations. This result should increase end-user confidence in conclusions drawn from model outputs. These results can be used to support and develop effective policies for FMD control.

Decision-making for foot-and-mouth disease control: objectives matter

Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.

Are the Australian poultry industries vulnerable to large outbreaks of highly pathogenic avian influenza

OBJECTIVEnTo describe the structure of the Australian poultry industry and discuss the potential for highly pathogenic avian influenza (HPAI) to spread between Australian poultry farms.nnnPROCEDUREnHigh densities of poultry farms, frequent contacts between farms by service providers, the supply of live poultry markets (LPM) and the presence of free-range duck flocks in affected regions have been identified as risk factors for the spread of HPAI between flocks in outbreaks causing the death or destruction of over 1 million poultry overseas. Data on 1,594 commercial Australian chicken meat, chicken egg, duck and turkey farms were collected by a telephone questionnaire of farm managers to assess the risk of a HPAI outbreak in Australia.nnnRESULTS AND DISCUSSIONnFive regions of Australia had farm densities comparable to overseas regions that experienced widespread HPAI. Common service providers routinely contacted different classes and types of farms over wide geographic areas. However, no responding farms supplied LPM and the majority of duck farms did not produce free-range ducks.nnnCONCLUSIONnOutbreaks of HPAI have the potential to cause serious impacts on the Australian poultry industry. The risk posted by LPM and free-range ducks is limited, but the movement of genetic stock and common service providers could spread infection between companies, industries or geographical regions. Biosecurity measures are therefore considered critical to limit the secondary spread of infection should an outbreak occur.

Evaluating the effectiveness of the response to equine influenza in the Australian outbreak and the potential role of early vaccination.

OBJECTIVEnTo use modelling and epidemiological analyses to assess the effectiveness of control strategies employed during the equine influenza outbreak and determine if early vaccination might have had a beneficial effect.nnnMETHODSnTransmission of infection was modelled using stochastic, spatial simulation, based on data from 16 regions in New South Wales and Queensland over the first month of the outbreak.nnnRESULTSnThe model accurately represented the spread of infection in both space and time and showed that vaccination strategies would have reduced new infections by ∼60% and reduced the size of the infected area by 8-9%, compared to the non-vaccination baseline.nnnCONCLUSIONnWhen used in conjunction with biosecurity measures and movement controls, early vaccination could play an important role in the containment and eradication of equine influenza.

Improving the computational efficiency of an agent-based spatiotemporal model of livestock disease spread and control

Abstract Agent-based models (ABMs) are well suited to representing the spatiotemporal spread and control of disease in a population. The explicit modelling of individuals in a large population, however, can be computationally intensive, especially when models are stochastic and/or spatially-explicit. Large-scale ABMs often require a highly parallel platform such as a high-performance computing cluster, which tends to confine their utility to university, defence and scientific research environments. This poses a challenge for those interested in modelling the spread of disease on a large scale with access only to modest hardware platforms. The Australian Animal DISease (AADIS) model is a spatiotemporal ABM of livestock disease spread and control. The AADIS ABM is able to complete complex national-scale simulations of disease spread and control on a personal computer. Computational efficiency is achieved through a hybrid model architecture that embeds equation-based models inside herd agents, an asynchronous software architecture, and a grid-based spatial indexing scheme.

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

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 (AUC). 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 AUC. 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 AUC had the highest predictive value (R2 =u20090.51–0.9) followed by the number of IPs (R2 =u20090.3–0.75) and outbreak duration (R2 =u20090.28–0.57). 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.

Comparison of alternatives to passive surveillance to detect foot and mouth disease incursions in Victoria, Australia.

This study aimed to evaluate strategies to enhance the early detection of foot and mouth disease incursions in Australia. Two strategies were considered. First, improving the performance of the current passive surveillance system. Second, supplementing the current passive system with active surveillance strategies based on testing animals at saleyards or through bulk milk testing of dairy herds. Simulation modelling estimated the impact of producer education and awareness by either increasing the daily probability that a farmer will report the presence of diseased animals or by reducing the proportion of the herd showing clinical signs required to trigger a disease report. Both increasing the probability of reporting and reducing the proportion of animals showing clinical signs resulted in incremental decreases in the time to detection, the size and the duration of the outbreak. A gold standard system in which all producers reported the presence of disease once 10% of the herd showed clinical signs reduced the median time to detection of the outbreak from 20 to 15days, the duration of the subsequent outbreak from 53 to 42days and the number of infected farms from 46 to 32. Bulk milk testing reduced the median time to detection by two days and the number of infected farms by six but had no impact on the duration of the outbreak. Screening of animals at saleyards provided no improvement over the current passive surveillance system alone while having significant resource issues. It is concluded that the most effective way to achieve early detection of incursions of foot and mouth disease into Victoria, Australia is to invest in improving producer reporting.