Assessing the efficacy of general surveillance for detection of incursions of livestock diseases in Australia

Surveillance for lumpy skin disease and foot and mouth disease in the Kimberley, Western Australia

We quantified the sensitivity of surveillance for lumpy skin disease (LSD) and foot and mouth disease (FMD) in cattle in the Kimberley region of Western Australia. We monitored producer and veterinary activity with cattle for 3 years commencing January 2020. Each year, ~274,000 cattle of 685,540 present on 92 pastoral leases (stations) were consigned to other stations, live export or slaughter. Veterinarians examined 103,000 cattle on the stations, 177,000 prior to live export, and 10,000 prior to slaughter. Detection probabilities for the disease prior to transport or during veterinary procedures and inspections were elicited by survey of 17 veterinarians working in Northern Australia. The veterinarians estimated the probabilities that they would notice, recognise, and submit samples from clinical cases of LSD and FMD, given a 5% prevalence of clinical signs in the herd. We used scenario tree methodology to estimate monthly surveillance sensitivity of observations made by producers and by veterinarians during herd management visits, pre-export inspections, and ante-mortem inspections. Average monthly combined sensitivities were 0.49 for FMD and 0.37 for LSD. Sensitivity was high for both diseases during the dry season and low in the wet season. We estimated the confidence in freedom from the estimated surveillance sensitivity given one hypothetically infected herd, estimated probability of introduction, and prior confidence in freedom. This study provided assurance that the Kimberley is free of these diseases and that routine producer and veterinary interactions with cattle are adequate for the timely detection of the disease should they be introduced.

The influence of trust and social identity in farmers' intentions to report suspected emergency disease outbreaks

This study examines the influence of trust on farmers' intentions to report suspected disease on their farm. Disease reporting is essential to detect and respond to disease early, thereby minimising its impacts on agriculture businesses, the economy, and the environment. Trust has been identified as an important factor influencing farmers' disease reporting intentions but has not been quantitatively investigated. We use an established model of trust-the Integrative Model of Organisational Trust (IMOT)-to conceptualise how trust influences disease reporting intentions. We also examine how social identity is related to trust and disease reporting. Australian plant, livestock, and aquaculture farmers (N = 41) completed an online questionnaire developed from existing validated measures and we also developed two new measures for disease reporting intentions. Trust in government positively and significantly predicted farmer intentions to report suspected disease outbreaks, explaining 26% of the variance. For every one-unit increase in trust, disease reporting intentions increased by over four times. Results also support the role of shared values and group membership as aspects of social identity that influence trust and disease reporting. These results highlight the importance of government decision-makers developing and maintaining trust with farmers to support early detection and response to emergency disease outbreaks.

FMD vaccine allocation and surveillance resourcing options for a potential Australian incursion

Australian Animal Disease Spread (AADIS) epidemiological simulation modelling of potential foot-and-mouth disease outbreaks in the state of Victoria, Australia examined the targeted use of limited vaccine supplies in combination with varying surveillance resources. Updated, detailed estimates of government response costs were prepared based on state level data inputs of required and available resources. Measures of outbreak spread such as duration and numbers of animals removed through depopulation of infected and vaccinated herds from the epidemiological modelling were compared to summed government response costs. This comparison illustrated the trade-offs between targeted control strategies combining vaccination-to-remove and varying surveillance capacities and their corresponding costs. For this intensive cattle and sheep producing region: (1) Targeting vaccination toward intensive production areas or toward specialized cattle operations had outbreak control and response cost advantages similar to vaccination of all species. The median duration was reduced by 27% and response costs by 11%. (2) Adding to the pool of outbreak surveillance resources available further decreased outbreak duration and outbreak response costs. The median duration was reduced by an additional 13% and response costs declined by an additional 8%. (3) Pooling of vaccine resources overcame the very early binding constraints under proportional allocation of vaccines to individual states with similar reductions in outbreak duration to those with additional surveillance resources. However, government costs rose substantially by over 40% and introduced additional risk of a negative consumer response. Increased knowledge of the outbreak situation obtained from more surveillance led to better-informed vaccination deployment decisions in the short timeframe they needed to be made.

Factors influencing the performance of voluntary farmer disease reporting in passive surveillance systems: A scoping review

The impacts of exotic disease incursions on livestock industries can be mitigated by having robust surveillance systems in place that decrease the time between disease introduction and detection. An important component of this is having farmers routinely observe their animals for indications of clinical disease, recognise the existence of problems, and then decide to notify their veterinarian or animal health authorities. However, as highlighted by this literature review, farmers are believed to be underreporting clinical events due to factors such as (1) uncertainty around the clinical signs and situations that warrant reporting, (2) fear over the social and economic consequences from both positive and false positive reports, (3) negative beliefs regarding the efficacy and outcomes of response measures, (4) mistrust and dissatisfaction with animal health authorities, (5) absence of sufficiently attractive financial and non-financial incentives for submitting reports, and (6) poor awareness of the procedures involved with the submission, processing, and response to reports. There have been few formal studies evaluating the efficacy of different approaches to increasing farmer engagement with disease reporting. However, there is a recognised need for any proposed solutions to account for farmer knowledge and experience with assessing their own farm situation as well as the different identities, motivations, and beliefs that farmers have about their role in animal health surveillance systems. Empowering farmers to take a more active role in developing these solutions is likely to become even more important as animal health authorities increasingly look to establish public-private partnerships for biosecurity governance.

A Simulation Study of the Use of Vaccination to Control Foot-and-Mouth Disease Outbreaks Across Australia

This study examines the potential for foot-and-mouth disease (FMD) control strategies that incorporate vaccination to manage FMD spread for a range of incursion scenarios across Australia. Stakeholder consultation was used to formulate control strategies and incursion scenarios to ensure relevance to the diverse range of Australian livestock production regions and management systems. The Australian Animal Disease Spread model (AADIS) was used to compare nine control strategies for 13 incursion scenarios, including seven control strategies incorporating vaccination. The control strategies with vaccination differed in terms of their approaches for targeting areas and species. These strategies are compared with two benchmark strategies based on stamping out only. Outbreak size and duration were compared in terms of the total number of infected premises, the duration of the control stage of an FMD outbreak, and the number of vaccinated animals. The three key findings from this analysis are as follows: (1) smaller outbreaks can be effectively managed by stamping out without vaccination, (2) the size and duration of larger outbreaks can be significantly reduced when vaccination is used, and (3) different vaccination strategies produced similar reductions in the size and duration of an outbreak, but the number of animals vaccinated varied. Under current international standards for regaining FMD-free status, vaccinated animals need to be removed from the population at the end of the outbreak to minimize trade impacts. We have shown that selective, targeted vaccination strategies could achieve effective FMD control while significantly reducing the number of animals vaccinated.

Comparing surveillance approaches to support regaining free status after a foot-and-mouth disease outbreak

Following an FMD eradication program, surveillance will be required to demonstrate that the program has been successful. The World Organization for Animal Health (OIE) provides guidelines including waiting periods and appropriate surveillance to support regaining FMD-free status. Serological surveillance is the recommended method for demonstrating freedom but is time consuming and expensive. New technologies such as real-time reverse transcription polymerase chain reaction (RT-qPCR) tests and sampling techniques such as bulk milk testing (BMT) of dairy cattle, oral swabs, and saliva collection with rope tethers in piggeries could enable surveillance to be done more efficiently. Epidemiological modelling was used to simulate FMD outbreaks, with and without emergency vaccination as part of the response, in Australia. Baseline post-outbreak surveillance approaches for unvaccinated and vaccinated animals based on the European FMD directive were compared with alternative approaches in which the sampling regime, sampling approaches and/or the diagnostic tests used were varied. The approaches were compared in terms of the resources required, time taken, cost, and effectiveness i.e., ability of the surveillance regime to correctly identify the infection status of herds. In the non-vaccination scenarios, the alternative approach took less time to complete and cost less, with the greatest benefits seen with larger outbreaks. In vaccinated populations, the alternative surveillance approaches significantly reduced the number of herds sampled, the total number of tests done and costs of the post-outbreak surveillance. There was no reduction in effectiveness using the alternative approaches, with one of the benefits being a reduction in the number of false positive herds. Alternative approaches to FMD surveillance based on non-invasive sampling methods and RT-qPCR tests have the potential to enable post outbreak surveillance substantiating FMD freedom to be done more quickly and less expensively than traditional approaches based on serological surveys.

Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak

To maintain and strengthen Australia's competitive international advantage in sheep meat and wool markets, the biosecurity systems that support these industries need to be robust and effective. These systems, strengthened by jurisdictional and livestock industry investments, can also be enhanced by a deeper understanding of individual producer risk of exposure to animal diseases and capacity to respond to these risks. This observational study developed a Vulnerability framework, built from current data from Australian sheep producers around behaviors and beliefs that may impact on their likelihood of Exposure and Response Capacity (willingness and ability to respond) to an emergency animal disease (EAD). Using foot and mouth disease (FMD) as a model, a cross-sectional survey gathered information on sheep producers' demographics, and their practices and beliefs around animal health management and biosecurity. Using the Vulnerability framework, a Bayesian Network (BN) model was developed as a first attempt to develop a decision making tool to inform risk based surveillance resource allocation. Populated by the data from 448 completed questionnaires, the BN model was analyzed to investigate relationships between variables and develop producer Vulnerability profiles. Respondents reported high levels of implementation of biosecurity practices that impact the likelihood of exposure to an EAD, such as the use of appropriate animal movement documentation (75.4%) and isolation of incoming stock (64.9%). However, adoption of other practices relating to feral animal control and biosecurity protocols for visitors were limited. Respondents reported a high uptake of Response Capacity practices, including identifying themselves as responsible for observing (94.6%), reporting unusual signs of disease in their animals (91.0%) and daily/weekly inspection of animals (90.0%). The BN analysis identified six Vulnerability typologies, with three levels of Exposure (high, moderate, low) and two levels of Response Capacity (high, low), as described by producer demographics and practices. The most influential Exposure variables on producer Vulnerability included adoption levels of visitor biosecurity and visitor access protocols. Findings from this study can guide decisions around resource allocation to improve Australia's readiness for EAD incursion and strengthen the country's biosecurity system.

Stakeholder mapping in animal health surveillance: A comparative assessment of networks in intensive dairy cattle and extensive sheep production in Australia

The capacity to rapidly identify and respond to suspicion of animal disease is fundamental to protecting the integrity of the Australian livestock industry. An incursion of a nationally significant endemic, emerging or exotic animal disease could be disruptive and economically damaging for the industry, broader community and national economy. To counter this potential threat, a surveillance system that includes general and targeted activities exists at a jurisdictional and national level. Such a system requires a collaborative effort from all involved to work towards a common goal, reflecting the notion of shared responsibility. As in all systems, the animal health surveillance system can be enhanced or constrained by the relationships of the players involved. This study focusses on two livestock industries, dairy cattle and sheep, exploring the interrelationships between all stakeholders, and their role within the Australian animal health surveillance system. A stakeholder mapping exercise was undertaken, including a depiction of the perceived level of stakeholder interest and influence on producers' animal health surveillance practices and/or the surveillance system. Results from these activities were expanded upon through interviews. The findings reveal complex networks and a system that is, at times, constrained by institutional and individual barriers such as communication between and within stakeholders, and uncertainty about the consequences of reporting a suspected emergency disease. Whilst these challenges have the potential to negatively impact the robustness of the animal disease surveillance system, the study also provides clear evidence of strong and effective relationships amongst many of the key individuals and organisations.

Using farmer observations for animal health syndromic surveillance: Participation and performance of an online enhanced passive surveillance system

The challenge of animal health surveillance is to provide the information necessary to appropriately inform disease prevention and control activities within the constraints of available resources. Syndromic surveillance of farmers' disease observations can improve animal health data capture from extensive livestock farming systems, especially where data are not otherwise being systematically collected or when data on confirmed aetiological diagnoses are unavailable at the disease level. As it is rarely feasible to recruit a truly random sample of farmers to provide observational reports, directing farmer sampling to align with the surveillance objectives is a reasonable and practical approach. As long as potential bias is recognised and managed, farmers who will report reliably can be desirable participants in a surveillance system. Thus, one early objective of a surveillance program should be to identify characteristics associated with reporting behaviour. Knowledge of the demographic and managerial characteristics of good reporters can inform efforts to recruit additional farms into the system or aid understanding of potential bias of system reports. We describe the operation of a farmer syndromic surveillance system in Victoria, Australia, over its first two years from 2014 to 2016. Survival analysis and classification and regression tree analysis were used to identify farm level factors associated with 'reliable' participation (low non-response rates in longitudinal reporting). Response rate and timeliness were not associated with whether farmers had disease to report, or with different months of the year. Farmers keeping only sheep were the most reliable and timely respondents. Farmers < 43 years of age had lower response rates than older farmers. Farmers with veterinary qualifications and those working full-time on-farm provided less timely reports than other educational backgrounds and farmers who worked part-time on-farm. These analyses provide a starting point to guide recruitment of participants for surveillance of farmers' observations using syndromic surveillance, and provide examples of strengths and weaknesses of syndromic surveillance systems for extensively-managed livestock. Once farm characteristics associated with reliable participation are known, they can be incorporated into surveillance system design in accordance with the objectives of the system.

The goat industry in Australia: Using Bayesian network analysis to understand vulnerability to a foot and mouth disease outbreak

Australia's goat industry is one of the largest goat product exporters in the world, managing both farmed and wild caught animals. To protect and maintain the competitive advantage afforded to the Australian goat industry by the absence of many diseases endemic elsewhere, it is important to identify the vulnerability of producers to livestock disease incursions. This study developed a framework of producer vulnerability built from the beliefs and practices of producers that may impact on their likelihood of exposure and response capacity to an emergency animal disease (EAD), using foot and mouth disease as a model. A cross-sectional questionnaire gathered information on producer/enterprise demographics, animal health management and biosecurity practices, with 107 participating in the study. The biosecurity measures that were most commonly implemented by producers were always using animal movement documentation for purchased stock (74.7 %) and isolating new stock (73.1 %). However, moderate to low uptake of biosecurity protocols related to visitors to the property were reported. Response capacity variables such as checking animals daily (72.0 %) and record keeping (91.7 %) were reported by the majority of respondents, with 40.7 % reporting yearly veterinary inspection of their animals. Using the vulnerability framework, a Bayesian Network model was developed and populated by the survey data, and the relationships between variables were investigated. Six vulnerability profiles were developed, with three levels of exposure (high, moderate, low) and two levels of response capacity (high, low), as described by producer demographics and practices. The most sensitive exposure variables on producer vulnerability included implementation of visitor biosecurity and control of feral animals. Results from this study can inform risk based perspectives and decisions around biosecurity and surveillance resource allocation within the goat industry. The results also highlight opportunities for improving Australia's preparedness for a future EAD incursion by considering producer behaviour and beliefs by applying a vulnerability framework.

Quantification of the sensitivity of early detection surveillance

Early detection surveillance is used for various purposes, including the early detection of non-communicable diseases (e.g. cancer screening), of unusual increases of disease frequency (e.g. influenza or pertussis outbreaks), and the first occurrence of a disease in a previously free population. This latter purpose is particularly important due to the high consequences and cost of delayed detection of a disease moving to a new population. Quantifying the sensitivity of early detection surveillance allows important aspects of the performance of different systems, approaches and authorities to be evaluated, compared and improved. While quantitative evaluation of the sensitivity of other branches of surveillance has been available for many years, development has lagged in the area of early detection, arguably one of the most important purposes of surveillance. This paper, using mostly animal health examples, develops a simple approach to quantifying the sensitivity of early detection surveillance, in terms of population coverage, temporal coverage and detection sensitivity. This approach is extended to quantify the benefits of risk-based approaches to early detection surveillance. Population-based clinical surveillance (based on either farmers and their veterinarians, or patients and their local health services) provides the best combination of sensitivity, practicality and cost-effectiveness. These systems can be significantly enhanced by removing disincentives to reporting, for instance by implementing effective strategies to improve farmer awareness and engagement with health services and addressing the challenges of well-intentioned disease notification policies that inadvertently impose barriers to reporting.

Understanding the vulnerability of beef producers in Australia to an FMD outbreak using a Bayesian Network predictive model

Effective and adaptable biosecurity and surveillance systems are crucial for maintaining and increasing Australia's competitive advantages in international markets, and for the production of high quality, safe animal products. These systems are continuously strengthened by ongoing government and industry investment. However, a better understanding of evolving disease risks and the country's capacity to respond to these risks is needed. This study developed a vulnerability framework based on characteristics and behaviours of livestock producers that impact exposure and response capacity to an emergency animal disease (EAD) outbreak among beef producers in Australia, with a focus on foot and mouth disease (FMD). This framework articulated producer vulnerability typologies to better inform surveillance resource allocation and future research direction. A cross-sectional study of beef producers in Australia was conducted to gather information on producers' demographics, husbandry characteristics, biosecurity and animal health management practices and beliefs, including those specific to FMD risk and response capacity. A Bayesian Network (BN) model was developed from the vulnerability framework, to investigate the complex interrelationships between variables and identify producer typologies. A total of 375 usable responses were obtained from the cross-sectional study. Regarding EAD exposure, producers implemented appropriate biosecurity practices for incoming stock, such as isolation (72.0 %), inspection for disease (88.7 %) and the use of vendor declarations (78.5 %); however, other biosecurity practices were limited, such as restriction of visitor access, visitor biosecurity requirements or feral animal control. In relation to response capacity, a moderate uptake of practices was observed. Whilst daily or weekly visual inspection of animals was reported by most producers (90.1 %), physical inspection was less frequent. Most producers would call a private veterinarian in response to unusual signs of disease in their cattle; however, over 40 % of producers did not cite calling a government veterinarian as a priority action. Most producers believe an FMD outbreak would have extremely serious consequences; however, their level of concern was moderate and their confidence in identifying FMD symptoms was low. The BN analysis identified six vulnerability typologies, with three levels of exposure (high, moderate, low) and two levels of response capacity (high, low), as described by producer demographics and practices. The model identified property size, number of cattle and exposure variables as the most influential to the overall producer vulnerability. Results from this study can inform how to best use current biosecurity and surveillance resources and identify where opportunities exist for improving Australia's preparedness for future EAD incursions.

Animal Health Management Practices Among Smallholder Livestock Producers in Australia and Their Contribution to the Surveillance System

The risks posed for disease introduction and spread are believed to be higher for smallholder livestock producers than commercial producers. Possible reasons for this is the notion that smallholders do not implement appropriate animal health management practices and are not part of traditional livestock communication networks. These factors contribute to the effectiveness of passive disease surveillance systems. A cross-sectional study, using a postal survey (n = 1,140) and group interviews (28 participants in three groups), was conducted to understand the animal health management and communication practices of smallholders keeping sheep, cattle, pigs, dairy goats and alpacas in Australia. These practices are crucial for an effective passive surveillance system. Findings indicate that there is a need for improvement in animal health management practices, such as contact with veterinarians and attitudes toward reporting. Results also indicate that these practices differ depending on the livestock species kept, with sheep ownership being associated with lower engagement with surveillance activities and smallholders keeping dairy goats and alpacas having in general better practices. Other factors associated with surveillance practices among participant smallholders are gender and years of experience raising livestock. Despite the differences observed, over 80% of all smallholders actively seek information on the health of their livestock, with private veterinarians considered to be a trusted source. Emergency animal diseases are not a priority among smallholders, however they are concerned about the health of their animals. The finding that veterinarians were identified by producers to be the first point of contact in the event of unusual signs of disease, strengthens the argument that private veterinarians play a vital role in improving passive surveillance. Other producers are also a point of contact for animal health advice, with government agencies less likely to be contacted. The effectiveness of on-farm passive surveillance could be enhanced by developing strategies involving both private veterinarians and producers as key stakeholders, which aim to improve awareness of disease and disease reporting responsibilities.

A framework for reviewing livestock disease reporting systems in high-risk areas: assessing performance and perceptions towards foot and mouth disease reporting in the Thrace region of Greece, Bulgaria and Turkey

Disease reporting is an essential frontline component of surveillance systems, particularly for detecting incursions of new and emerging diseases. It has the advantages of being comprehensive and continuous, with the potential to reduce the time of disease detection and the extent of consequent spread. A number of exotic diseases, including sheep and goat pox, lumpy skin disease, peste des petits ruminants and foot and mouth disease have historically entered into south-eastern Europe through the Thrace region, which extends across neighbouring areas of Greece, Bulgaria and Turkey. In this high-risk area, multiple factors can reduce the sensitivity of disease reporting across the diverse production systems and animal health services need robust and effective disease reporting systems. While describing a training exercise designed to provide animal health services of the three countries with the knowledge and skills for conducting comprehensive in-country assessments, we provide an initial evaluation of the sensitivity of foot and mouth disease reporting and identify gaps and constraints in the Thrace region. An expert elicitation approach was used to consult official veterinarians from central and local animal health authorities of the three countries, and scenario trees modelling was applied to analyse the collected data. The reported sensitivity of disease reporting often varied between the central and local veterinary authorities within the three countries. Awareness of clinical disease, of reporting procedures and of biosecurity measures affected the early stages of disease reporting, particularly in the production systems identified at lower reporting sensitivity such as small ruminant's herds, mixed bovine herds and backyard herds. Despite its limitations this training exercise provided an effective framework (a) to develop capacities of the veterinary services in the region and (b) to supply initial evidence for guiding further interventions targeting those sectors and stakeholders at lower reporting sensitivity to reduce risks of disease introduction.

Sellers' Revisited: A Big Data Reassessment of Historical Outbreaks of Bluetongue and African Horse Sickness due to the Long-Distance Wind Dispersion of Culicoides Midges

The possibility that outbreaks of bluetongue (BT) and African horse sickness (AHS) might occur via long-distance wind dispersion (LDWD) of their insect vector (Culicoides spp.) was proposed by R. F. Sellers in a series of papers published between 1977 and 1991. These investigated the role of LDWD by means of visual examination of the wind direction of synoptic weather charts. Based on the hypothesis that simple wind direction analysis, which does not allow for wind speed, might have led to spurious conclusions, we reanalyzed six of the outbreak scenarios described in Sellers' papers. For this reanalysis, we used a custom-built Big Data application ("TAPPAS") which couples a user-friendly web-interface with an established atmospheric dispersal model ("HYSPLIT"), thus enabling more sophisticated modeling than was possible when Sellers undertook his analyzes. For the two AHS outbreaks, there was strong support from our reanalysis of the role of LDWD for that in Spain (1966), and to a lesser degree, for the outbreak in Cyprus (1960). However, for the BT outbreaks, the reassessments were more complex, and for one of these (western Turkey, 1977) we could discount LDWD as the means of direct introduction of the virus. By contrast, while the outbreak in Cyprus (1977) showed LDWD was a possible means of introduction, there is an apparent inconsistency in that the outbreaks were localized while the dispersion events covered much of the island. For Portugal (1956), LDWD from Morocco on the dates suggested by Sellers is very unlikely to have been the pathway for introduction, and for the detection of serotype 2 in Florida (1982), LDWD from Cuba would require an assumption of a lengthy survival time of the midges in the air column. Except for western Turkey, the BT reanalyses show the limitation of LDWD modeling when used by itself, and indicates the need to integrate susceptible host population distribution (and other covariate) data into the modeling process. A further refinement, which will become increasingly important to assess LDWD, will be the use of virus and vector genome sequence data collected from potential source and the incursion sites.

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 = 0.51-0.9) followed by the number of IPs (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.

A Comparative Assessment of the Risks of Introduction and Spread of Foot-and-Mouth Disease among Different Pig Sectors in Australia

Small-scale pig producers are believed to pose higher biosecurity risks for the introduction and spread of exotic diseases than commercial pig producers. However, the magnitude of these risks is poorly understood. This study is a comparative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) through different sectors of the pig industry: (1) large-scale pig producers; (2) small-scale producers (<100 sows) selling at saleyards and abattoirs; and (3) small-scale producers selling through informal means. An exposure and consequence assessments were conducted using the World Organization for Animal Health methodology for risk analysis, assuming FMD virus was introduced into Australia through illegal importation of infected meat. A quantitative assessment, using scenario trees and Monte Carlo stochastic simulation, was used to calculate the probabilities of exposure and spread. Input data for these assessments were obtained from a series of data gathering exercises among pig producers, industry statistics, and literature. Findings of this study suggest there is an Extremely low probability of exposure (8.69 × 10⁻⁶ to 3.81 × 10⁻⁵) for the three sectors of the pig industry, with exposure through direct swill feeding being 10–100 times more likely to occur than through contact with infected feral pigs. Spread of FMD from the index farm is most likely to occur through movement of contaminated fomites, pigs, and ruminants. The virus is more likely to spread from small-scale piggeries selling at saleyards and abattoirs than from other piggeries. The most influential factors on the spread of FMD from the index farm is the ability of the farmer to detect FMD, the probability of FMD spread through contaminated fomites and the presence of ruminants on the farm. Although small-scale producers selling informally move animals less frequently and do not use external staff, movement of pigs to non-commercial pathways could jeopardize animal traceability in the event of a disease outbreak. This study suggests that producers’ awareness on and engagement with legislative and industry requirements in relation to biosecurity and emergency animal disease management needs to be improved. Results from this study could be used by decision-makers to prioritize resource allocation for improving animal biosecurity in the pig industry.

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.

Assessing the delay to detection and the size of the outbreak at the time of detection of incursions of foot and mouth disease in Australia

The time delay to detection of an outbreak of an emergency animal disease directly affects the size of the outbreak at detection and the likelihood that the disease can be eradicated. This time delay is a direct function of the efficacy of the surveillance system in the country involved. Australia has recently completed a comprehensive review of its general surveillance system examining regional variation in both the behaviour of modelled outbreaks of foot and mouth disease and the likelihood that each outbreak will be detected and reported to government veterinary services. The size of the outbreak and the time delay from introduction to the point where 95% confidence of detection was reached showed significant (p < 0.05) regional variation with the more remote northern areas experiencing smaller outbreaks that are less likely to spread and less likely to be reported to government services than outbreaks in the more developed southern areas of Australia. Outbreaks in the more densely populated areas may take up to 43 days until a 95% confidence of detection is achieved and at that time, the outbreak may involve up to 53 farms.