The objective of the study was to simulate New Zealand's foot-and-mouth disease (FMD) operational plan to determine personnel requirements for an FMD response and understand how the numbers of front-line 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 available for front-line tasks (including contact tracing, surveillance of at-risk farms, depopulation and vaccination) were set randomly. In a random subset of simulations, vaccination was allowed to be deployed as an adjunct to SO. The effects 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 95th percentile and maximum number of infected places (IPs) were 78 and 462, respectively, and the 95th 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, whereas 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 was 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 FMD outbreaks but at the cost of a short-term spike in demand for personnel. In conclusion, a successful response needs to have access to sufficient personnel, particularly veterinarians, trained in response roles and available at short notice.

fi eld of livestock mineral nutrition, is justly famous for both authority and enthusiasm. When it comes to his science, he good data and good He is driven to solve problems for the intellectual challenge and has the con fi dence to refute shonky or half-baked misinformation that is in the public domain. He then delivers answers and understanding to the people who need it most; the veterinarians, farmers, consultants and students directly responsible for making New Zealand agriculture successful

Aims To investigate an adaptive management approach to the deployment of emergency vaccination as an additional measure to stamping out (SO) during simulated outbreaks of foot-and-mouth disease (FMD) in New Zealand. Methods A simulation modelling (n=6000 simulations) approach was used. The study population comprised all known farms in New Zealand with FMD-susceptible livestock. Each simulation started with infection seeded into a single randomly selected farm. Each outbreak was randomly assigned to one of four control strategies, comprising SO only; trigger-based vaccination (TRV) where SO was augmented with vaccination if an early decision indicator trigger operating between Days 11-35 of the response indicated a large outbreak was developing; SO plus vaccination started randomly on Days 11-35 of the response (VACr); and SO plus vaccination with a fixed start on Day 21 of the response (VACf). Other parameters, such as the number of personnel available were also varied randomly. Generalised additive models (GAM) were used to evaluate variables associated with the number of infected premises (IP) and epidemic duration. Results The mean number of IP was 29 (median 9, min 1, max 757), while epidemics lasted on average 26.9 (median 18, min 1, max 220) days. These excluded 303 extreme outbreaks larger than the UK 2001 FMD epidemic (2,030 cases). Univariable analysis of the pooled vaccination results vs. SO, showed that vaccination significantly reduced the number of IP (p<0.001) and outbreak duration (p<0.001). GAM of large outbreaks revealed that only the TRV strategy was significantly protective compared to SO alone, reducing the odds of a large outbreak by 22% (OR=0.78; 95% CI=0.63-0.96). The number of veterinarians was non-linearly associated with large outbreaks, with low numbers increasing the odds of a large outbreak, but above 200 veterinarians, the odds reduced. Time to first detection was also non-linearly associated with large outbreaks, with detections <13 days protective and longer detection times increasing the odds of a large outbreak. GAM of long outbreaks showed similar findings, except that all three vaccination strategies significantly reduced duration. Overall, the TRV strategy resulted in the smallest and shortest epidemics.

AIMS: To test 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 can affect the size and duration of FMD outbreaks.METHODS: The study involved simulation modelling, utilizing a national dataset of all known livestock farms. Each simulation randomly seeded infection into one 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 regression trees. 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.RESULTS: When personnel resources were unconstrained, the maximum size and duration was 462 infected places (IPs) and 217 days, respectively. However, severe constraints on personnel resources allowed some outbreaks to exceed the size of the UK 2001 FMD epidemic.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, due to the beneficial effects of vaccination.CONCLUSIONS: This study determined the optimal numbers of front-line personnel required to support an FMD response in NZ, when implementing current operational plans. This study highlighted the consequences a shortage of veterinarians could have on disease control outcomes if New Zealand were to suffer an incursion of FMD. New Zealand needs to ensure it has access to sufficient personnel, particularly veterinarians, trained in response roles and available at short notice to respond to FMD and other transboundary animal diseases. The use of emergency vaccination led to a short-term spike in demand for personnel, but the overall person days were similar for an FMD response with or without emergency vaccination.

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.

An incursion of an important exotic transboundary animal disease requires a prompt and intensive response. The routine analysis of up-to-date data, as near to real time as possible, is essential for the objective assessment of the patterns of disease spread or effectiveness of control measures and the formulation of alternative control strategies. In this paper, we describe the Standard Analysis of Disease Investigation (SADI), a toolbox for informing disease outbreak response, which was developed as part of New Zealand's biosecurity preparedness. SADI was generically designed on a web-based software platform, Integrated Real-time Information System (IRIS). We demonstrated the use of SADI for a hypothetical foot-and-mouth disease (FMD) outbreak scenario in New Zealand. The data standards were set within SADI, accommodating a single relational database that integrated the national livestock population data, outbreak data, and tracing data. We collected a well-researched, standardised set of 16 epidemiologically relevant analyses for informing the FMD outbreak response, including farm response timelines, interactive outbreak/network maps, stratified epidemic curves, estimated dissemination rates, estimated reproduction numbers, and areal attack rates. The analyses were programmed within SADI to automate the process to generate the reports at a regular interval (daily) using the most up-to-date data. Having SADI prepared in advance and the process streamlined for data collection, analysis and reporting would free a wider group of epidemiologists during an actual disease outbreak from solving data inconsistency among response teams, daily "number crunching," or providing largely retrospective analyses. Instead, the focus could be directed into enhancing data collection strategies, improving data quality, understanding the limitations of the data available, interpreting the set of analyses, and communicating their meaning with response teams, decision makers and public in the context of the epidemic.

Foot-and-mouth disease (FMD) is a highly infectious viral disease of cloven-hoofed animals. FMD outbreaks have the potential to cause significant economic consequences, and effective control strategies are needed to minimize the damage to livestock systems and the economy. Although not the predominant route of infection, airborne transmission has been implicated in previous outbreaks. Under favorable weather conditions, airborne spread of FMD can make the rapid containment of an outbreak more difficult. Our objective was to identify seasonal and geographic differences in patterns of conditions favorable to airborne FMD spread in the United States. Data from a national network of surface weather stations were examined for three study years (December 2011 November 2012, December 2012 November 2013, December 2014 November 2015). Weather conditions were found to be most frequently favorable to airborne spread during the winter (December, January, February). Geographically, conditions were most frequently favorable to airborne FMD spread in the upper Midwestern United States, a region where swine and cattle populations are common. Across study years, conditions for airborne FMD spread were more frequently favorable when weather conditions were generally mild with few extremes with respect to temperature and precipitation (e.g., 2014-2015). However, national patterns in risk areas for airborne FMD spread were similar across study years even though the degree of risk differed based on variations in weather patterns among study years. Our findings suggest that airborne transmission could contribute to FMD spread between livestock premises in the event of an outbreak in the coterminous United States, and that some geographic areas are at an increased risk particularly in seasons with conducive weather conditions. To our knowledge, this is the first study to characterize the risk of airborne FMD spread on a national scale in the United States. The findings presented here can be used to enhance preparedness and surveillance activities by identifying specific geographic areas in the United States where airborne spread is most likely to be a risk factor for transmission during an outbreak.

Commencing in 2012, an epidemic of infectious bovine anaemia associated with Theileria orientalis Ikeda type has been present in New Zealand. The aims of this study were to analyse the temporal and spatial effects of T. orientalis Ikeda type infection on the sample submission rates and haematocrits of infected cattle over the first two years of the New Zealand epidemic. The data were collected from 30/08/2012 to 28/11/2014 and included all samples that met the case definition for Theileria associated bovine anaemia (TABA) and tested positive for T. orientalis Ikeda type by PCR. The sample submission rates by month and farm type were highly seasonal with dairy farm submissions peaking in September a month before beef farm submissions peaked. A second lesser peak of dairy farm submissions in April was absent for beef farms. A mixed effects model was fitted to the data and showed a significant interaction between farm production type (dairy or beef) and month of sampling (p = 0.006) and between latitude and month of sampling (p = 0.024). The estimated haematocrit, adjusted for month and latitude, for dairy cattle = 0.125 (95%CI 0.121-0.129) and for beef cattle = 0.151 (95% CI 0.138-0.165), p < 0.0001. This research shows that infected beef animals tend to be less severely affected than dairy animals and that the month of sampling and latitude of the sampled farm have significant and interacting effects on the level of anaemia associated with T. orientalis Ikeda type infection.

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 modelling 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. The study involved two modelling 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 area under control. The number of infected premises, number of pending culls, area under control, 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 area under control had the highest predictive value (R2 = 0.51-0.9) followed by the number of infected premises (R2 = 0.3-0.75) and outbreak duration (R2 = 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.

AIMS: To evaluate the benefits of vaccination against simulated outbreaks of foot-and-mouth disease (FMD) in New Zealand, when applied as an additional measure to stamping-out.METHODS: A simulation modelling approach was used. The study population comprised all known farms in New Zealand with FMD-susceptible livestock. Infection was seeded into three different areas of New Zealand. Transmission mechanisms included direct and indirect contacts, local spread and airborne spread. Efficacies of some of the stamping-out measures were varied. Vaccination strategies involved different start times, size and type of vaccination zone, and species vaccinated. Personnel resources for vaccination were varied as was the herd immunity profile following vaccination. Altogether, 336 models were specified, with 100 iterations conducted for each model. Generalised linear modelling and boosted regression trees were used to evaluate which variables had the biggest effect on the number of infected premises (IP), epidemic duration and area under control.RESULTS: Vaccination, when used as an adjunct to the standard stamping-out programme, significantly reduced the outbreak size. Vaccination reduced the median number of IP by 26 (95% CI=18-35), epidemic duration by 16 (95% CI=13-19) days and area under control by 474 (95% CI=250-699)km(2) when there was no airborne spread; and when there was airborne spread the median reduction was 87 (95% CI=70-105) IP, 32 (95% CI=28-35) days and 898 (95% CI=665-1139)km(2), respectively. Multivariable analyses showed that starting vaccination 11 days after first detection of FMD produced greater benefits than starting 16 or 21 days after detection. Increasing vaccination zones resulted in increased benefits. Boosted regression tree analyses showed that the most influential variables on the outcome measures were interval to first detection, incursion location, whether there was airborne spread or not and herd immunity profile.CONCLUSIONS AND CLINICAL RELEVANCE: This study showed that there are benefits to the use of vaccination in combination with a stamping-out policy for control of FMD outbreaks under New Zealand conditions. The optimal vaccination strategy was identified as being a 3-5km radius suppressive vaccination zone deployed between 11-16 days after first detection. Vaccination had a greater benefit during larger outbreaks, such as when there was airborne transmission. The key factors which were identified from this study will help inform New Zealand's competent authority on how best to deploy vaccination to further strengthen its approach to FMD eradication should New Zealand ever experience an outbreak.

Vaccination is increasingly being recognised as a potential tool to supplement stamping out' for controlling foot-and-mouth disease (FMD) outbreaks in non-endemic countries. Infectious disease simulation models provide the opportunity to determine how vaccination might be used in the face of an FMD outbreak. Previously, consistent relative benefits of specific vaccination strategies across different FMD simulation modelling platforms have been demonstrated, using a UK FMD outbreak scenario. We extended this work to assess the relative effectiveness of selected vaccination strategies in five countries: Australia, New Zealand, the USA, the UK and Canada. A comparable, but not identical, FMD outbreak scenario was developed for each country with initial seeding of Pan Asia type O FMD virus into an area with a relatively high density of livestock farms. A series of vaccination strategies (in addition to stamping out (SO)) were selected to evaluate key areas of interest from a disease response perspective, including timing of vaccination, species considerations (e.g. vaccination of only those farms with cattle), risk area vaccination and resources available for vaccination. The study found that vaccination used with SO was effective in reducing epidemic size and duration in a severe outbreak situation. Early vaccination and unconstrained resources for vaccination consistently outperformed other strategies. Vaccination of only those farms with cattle produced comparable results, with some countries demonstrating that this could be as effective as all species vaccination. Restriction of vaccination to higher risk areas was less effective than other strategies. This study demonstrates consistency in the relative effectiveness of selected vaccination strategies under different outbreak start up conditions conditional on the assumption that each of the simulation models provide a realistic estimation of FMD virus spread. Preferred outbreak management approaches must however balance the principles identified in this study, working to clearly defined outbreak management objectives, while having a good understanding of logistic requirements and the socio-economic implications of different control measures.

This study describes the use of simulation modelling to evaluate the predicted benefits of an effective livestock traceability system in responding to a hypothetical introduction of foot-and-mouth disease (FMD) in to the province of Alberta, Canada, and whether or not the implementation of emergency ring vaccination in addition to a standard stamping-out (SO) strategy would lead to smaller and shorter epidemics. Three introduction scenarios were defined, with the primary case in either an intensive beef feedlot operation, an extensive cow–calf operation or in a swine operation. Disease spread was simulated using, three levels of tracing effectiveness, five types of vaccination zone, three different vaccination start times, three lengths of vaccination campaigns, two levels of culling resource and using FMD strains with two different virulence levels. Using standard SO procedures (without vaccination), improving traceability effectiveness from a level whereby only 65% of movements were traced within 5–7 days, to a capability whereby all movements were traced within 1 day, led to a reduction in the number of infected premises (IPs) between 18.7 and 64.5%, an average saving of CAN$29,000,000 in livestock compensation costs alone, and a reduction in the length of epidemics ranging from 1 to 22 days. The implementation of emergency vaccination also led to a reduction in the number of IPs and a shortening of epidemics. The effects were more pronounced when the higher virulence settings were used, with a predicted reduction in IPs of 16.6–68.7% (mean=48.6%) and epidemics shortened by up to 37 days. Multi-variable analyses showed these effects were highly significant, after accounting for the incursion location, virulence of virus and time of first detection. The results clearly demonstrated the benefits of having effective traceability systems with rapid query and reporting functionality. The results also supported the value of early vaccination as an adjunct to SO in reducing the number of IPs and shortening the length of the epidemics. The most effective vaccination strategy involved a 3km or larger suppressive vaccination zone around all IPs, begun as soon as practicable after first detection, and which continued until the last IP was detected.

We describe the spatially explicit, stochastic simulation model of disease spread, InterSpread Plus, in terms of its epidemiological framework, operation, and mode of use. The input data required by the model, the method for simulating contact and infection spread, and methods for simulating disease control measures are described. Data and parameters that are essential for disease simulation modelling using InterSpread Plus are distinguished from those that are non-essential, and it is suggested that a rational approach to simulating disease epidemics using this tool is to start with core data and parameters, adding additional layers of complexity if and when the specific requirements of the simulation exercise require it. We recommend that simulation models of disease are best developed as part of epidemic contingency planning so decision makers are familiar with model outputs and assumptions and are well-positioned to evaluate their strengths and weaknesses to make informed decisions in times of crisis.

AIMS:The study was conducted to identify movement patterns of disease conveyors in the New Zealand pig industry. The principal objective of the study was to identify data relating to the frequency and distance of movements of pigs and semen amongst pig holdings. A secondary objective of the study was to generate criteria suitable for categorisation of different pig breeding or raising operations.METHODS:Prospective data were collected by a census of all known pig holdings in New Zealand using a mailed-out questionnaire.RESULTS:The survey yielded 1,477 responses (114 commercial and 1,363 non-commercial pig holdings) for descriptive analysis. Seven farm-types were created to describe typical pig holdings and were based on pig herd inventory, herd type, and participation in the movement of pigs or semen: Commercial genetic supplier, commercial feeder, commercial weaner producer, para-commercial genetic supplier, para-commercial feeder, para-commercial weaner producer, and non-commercial herd. The farm-type with the highest frequency of movements off the piggery was the para-commercial genetic suppliers with a median of 5.3 movements off per month. Commercial feeders had the second highest off farm movement with a median of 4.6 movements per month; these primarily represented movements to an abattoir. The highest frequencies of movements on to a piggery were experienced by commercial genetic suppliers (3.5 per month) and were due to the delivery of semen or replacement gilt/boars. Para-commercial and non-commercial farm-types reported less frequent movement activities both onto and off the piggery compared to their commercial counterparts. Most movements of pigs and semen occurred over distances of less than 100 km.CONCLUSIONS:The study showed that New Zealand has a relatively small but widely dispersed commercial pig industry with a large number of non-commercial pig holdings and there was a substantial geographic overlap between these industry sectors. Knowledge of the frequency of movements of pigs and semen among different pig farm-types and the distance over which these movements occur helps to assess the likely connectivity between piggeries, abattoirs, and sale yards. However, the study also highlighted the knowledge deficiencies that result in the absence of mandatory livestock identification and tracking schemes.CLINICAL RELEVANCE:In an industry with substantially more non-commercial pig holdings than commercial pig-holdings, key issues such as biosecurity education, ensuring sufficient veterinary involvement in non-commercial sectors, and building robust systems to ensure border security will remain critical in the effort to keep the pig industry at its current level of high health.

Disease simulation models can be a valuable tool for planning a response to exotic disease incursions, as they provide a fast, low-cost mechanism for identifying the likely outcomes of a range of outbreak scenarios and disease control strategies. To use these tools effectively and with confidence, decision-makers must understand the simplifications and framing assumptions that underlie a model's structure. Sensitivity analysis, the analytical process of identifying which input variables are the key drivers of the model's output, is a crucial process in developing this understanding. This paper describes the application of a sampling-based sensitivity analysis to the New Zealand standard model (NZSM). This model is a parameter set developed for the InterSpread Plus model platform to allow the exploration of different outbreak scenarios for an epidemic of foot and mouth disease in New Zealand. Based on 200 iterations of the NZSM, run for a simulation period of 60 days, settings related to farm-to-saleyard movements and the detection of disease during the active surveillance phase of the epidemic had the greatest influence on the predicted number of infected premises. A small number of counter-intuitive findings indicated areas of model design, implementation and/or parameterisation that should be investigated further. A potentially useful result from this work would be information to aid the grouping or elimination of non-influential model settings. This would go some way towards reducing the overall complexity of the NZSM, while still allowing it to remain fit for purpose.

Researchers from Australia, New Zealand, Canada and the United States collaborated to validate their foot and mouth disease models--AusSpread, InterSpread Plus and the North American Animal Disease Spread Model--in an effort to build confidence in their use as decision-support tools. The final stage of this project involved using the three models to simulate a number of disease outbreak scenarios, with data from the Republic of Ireland. The scenarios included an uncontrolled epidemic, and epidemics managed by combinations of stamping out and vaccination. The predicted numbers of infected premises, the duration of each epidemic, and the size of predicted outbreak areas were compared. Relative within-model between-scenario changes resulting from different control strategies or resource constraints in different scenarios were quantified and compared. Although there were differences between the models in absolute outcomes, between-scenario comparisons within each model were similar. In all three models, early use of ring vaccination resulted in the largest drop in number of infected premises compared with the standard stamping-out regimen. This consistency implies that the assumptions made by each of the three modelling teams were appropriate, which in turn serves to increase end-user confidence in predictions made by these models.

The aims of this study were to statistically reassess the likelihood that windborne spread of foot-and-mouth disease (FMD) virus (FMDV) occurred at the start of the UK 1967 to 1968 FMD epidemic at Oswestry, Shropshire, and to derive dose-response probability of infection curves for farms exposed to airborne FMDV. To enable this, data on all farms present in 1967 in the parishes near Oswestry were assembled. Cases were infected premises whose date of appearance of first clinical signs was within 14 days of the depopulation of the index farm. Logistic regression was used to evaluate the association between infection status and distance and direction from the index farm. The UK Met Office's NAME atmospheric dispersion model (ADM) was used to generate plumes for each day that FMDV was excreted from the index farm based on actual historical weather records from October 1967. Daily airborne FMDV exposure rates for all farms in the study area were calculated using a geographical information system. Probit analyses were used to calculate dose-response probability of infection curves to FMDV, using relative exposure rates on case and control farms. Both the logistic regression and probit analyses gave strong statistical support to the hypothesis that airborne spread occurred. There was some evidence that incubation period was inversely proportional to the exposure rate.

Atmospheric dispersion models can be used to assess the likely airborne spread of both plant and animal diseases. These models, often initially developed for other purposes, can be adapted and used to study past outbreaks of disease as well as operationally to provide advice to those responsible for containing or eradicating disease in the event of a specific emergency. The models can be run over short periods of time where emissions and infection periods can be accurately determined or in situations requiring a statistical approach perhaps covering many weeks or even months. They can also be embedded within other simulation models, i.e. models which seekto represent a wider variety of disease transmission mechanisms. Whilst atmospheric dispersion models have been used successfully in a number of instances, they have the potential for wider application in the future. To achieve maximum success in these ventures, close collaboration between the modellers and scientists from the appropriate range of disciplines is required.

(1) AsureQuality Limited, P.O. Box 585, Palmerston North 4440, New Zealand (2) Department of Computing and Information Science, University of Guelph, Guelph, Ontario N1G 2W1, Canada (3) Office of the Chief Veterinary Officer, Department of Agriculture, Fisheries and Forestry, G.P.O. Box 858, ACT 2601, Australia (4) EpiCentre, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11-222, Palmerston North, New Zealand (5) Institute of Fundamental Sciences, Massey University, Private Bag 11-222, Palmerston North, New Zealand (6) Embassy of Ireland, Piazza di Campitelli 3, 00186 Rome, Italy (7) Animal Health and Management Section, Canadian Food Inspection Agency, 59 Camelot Drive, Ottawa, Ontario K1A 0Y9, Canada (8) Centers for Epidemiology and Animal Health, 2150 Centre Avenue, Building B, Fort Collins, Colorado, United States of America (9) MAF Biosecurity New Zealand, Pastoral House, P.O. Box 2526, Wellington, New Zealand