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

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.

Patterns of foot-and-mouth disease virus detection in environmental samples in an endemic setting

Foot-and-Mouth Disease virus (FMDV) is endemic in several regions and is a virus that can persist in the environment dependent on pH, relative humidity (RH), temperature, and matrix (i.e., soil, water, or air). Our previously published analysis of available viral persistence data showed that persistence is likely affected by interactions between RH, temperature, and matrix. Understanding these relationships will aid efforts to eliminate FMD, which has significant impacts on economies and food security. In Cameroon, West Africa, the livestock system consists of mobile (transhumant), transboundary trade and sedentary herds. Studying this system can provide information about the patterns of environmental detection of FMDV RNA that may influence approaches to virus elimination on premises during an outbreak. To improve our understanding of these patterns, we collected samples from individuals, vehicles, and along cattle pathways at three sedentary herds beginning on day one of owner-reported outbreaks, ending by day 30, and tested for the presence of FMD viral RNA using rRT-PCR. Our analysis suggests that detection decreases in soil surface samples with increased distance from herd and time from the first report of disease. Whereas time but not distance decreases detection in air samples. Interaction of RH and temperature suggests increased detection at high temperatures (>24°C) and RH (>75%), providing us with new information about the patterns of FMD viral RNA detection in and around cattle herds that could help to inform targeted virus elimination strategies, such as location and application of disinfectants.

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.

Australian veterinarians' perspectives on the contribution of the veterinary workforce to the Australian animal health surveillance system

This study investigated the involvement of private veterinarians in surveillance activities and the veterinary workforce's contribution to the Australian animal health surveillance system. The perception that there is overall a decreased engagement by veterinarians in surveillance outcomes at a time when there is increased need for bolstering of surveillance systems was investigated. Three key questions were considered: (1) What is the current contribution of private veterinarians to the Australian surveillance system? (2) What is the veterinary professions capacity to assume a more prominent role in surveillance? (3) What is the interest and ability of the veterinary profession in Australia to undertake this surveillance role now and into the future? Semi-structured telephone interviews were conducted with 17 private veterinarians with data analyzed qualitatively to identify key themes. Results demonstrate that private veterinarians are aware of their responsibilities and are engaged in surveillance activities at both formal and informal levels. The key challenges associated with current and future contributions were related to workload, remuneration, conflicts of interest and clarity over how responsibility for surveillance is shared amongst those involved in the system. The study has demonstrated that even amongst an engaged population, barriers do need to be addressed if private veterinarians are to be tasked with increasing their involvement in animal health surveillance activities.

Proof of Proficiency of Decentralized Foot-and-Mouth Disease Virus Diagnostics in Germany

A proficiency test was performed to verify that the regional veterinary laboratories in Germany can provide reliable foot-and-mouth disease virus (FMDV) diagnostics. Overall, 24 samples were to be analyzed for FMDV-specific nucleic acids by real-time RT-PCR, and 16 samples had to be tested by ELISA for antibodies against non-structural proteins of FMDV. For both methods, a range of dilutions of the original materials (inactivated FMDV vaccine or convalescent serum from infected animals, respectively) was prepared, and negative samples were included as well. All 23 participating laboratories were able to detect FMDV genome down to a dilution of 1:100,000 of the vaccine preparation. Even at a dilution of 1:1,000,000, FMDV genome was detected by more than half of the participants. With the antibody ELISA, all sera were correctly identified by all participating laboratories. No false-positive results were returned with either method. All participating laboratories were found to be fully proficient in FMDV diagnostics.

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.

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.

Challenges to the Application of Spatially Explicit Stochastic Simulation Models for Foot-and-Mouth Disease Control in Endemic Settings: A Systematic Review

Simulation modeling has become common for estimating the spread of highly contagious animal diseases. Several models have been developed to mimic the spread of foot-and-mouth disease (FMD) in specific regions or countries, conduct risk assessment, analyze outbreaks using historical data or hypothetical scenarios, assist in policy decisions during epidemics, formulate preparedness plans, and evaluate economic impacts. Majority of the available FMD simulation models were designed for and applied in disease-free countries, while there has been limited use of such models in FMD endemic countries. This paper's objective was to report the findings from a study conducted to review the existing published original research literature on spatially explicit stochastic simulation (SESS) models of FMD spread, focusing on assessing these models for their potential use in endemic settings. The goal was to identify the specific components of endemic FMD needed to adapt these SESS models for their potential application in FMD endemic settings. This systematic review followed the PRISMA guidelines, and three databases were searched, which resulted in 1176 citations. Eighty citations finally met the inclusion criteria and were included in the qualitative synthesis, identifying nine unique SESS models. These SESS models were assessed for their potential application in endemic settings. The assessed SESS models can be adapted for use in FMD endemic countries by modifying the underlying code to include multiple cocirculating serotypes, routine prophylactic vaccination (RPV), and livestock population dynamics to more realistically mimic the endemic characteristics of FMD. The application of SESS models in endemic settings will help evaluate strategies for FMD control, which will improve livestock health, provide economic gains for producers, help alleviate poverty and hunger, and will complement efforts to achieve the Sustainable Development Goals.

Non-discriminatory Exclusion Testing as a Tool for the Early Detection of Foot-and-Mouth Disease Incursions

Endemic circulation of foot-and-mouth disease (FMD) in Africa and Asia poses a continuous risk to countries in Europe, North America, and Oceania which are free from the disease. Introductions of the disease into a free region have dramatic economic impacts, especially if they are not detected at an early stage and controlled rapidly. However, farmers and veterinarians have an obvious disincentive to report clinical signs that are consistent with FMD, due to the severe consequences of raising an official suspicion, such as farm-level quarantine. One way that the risk of late detection can be mitigated is offering non-discriminatory exclusion testing schemes for differential diagnostics, wherein veterinarians can submit samples without the involvement of the competent authority and without sanctions or costs for the farmer. This review considers the benefits and limitations of this approach to improve the early detection of FMD in free countries and gives an overview of the FMD testing schemes currently in use in selected countries in Europe and the Americas as well as in Australia.

Informing adaptive management strategies: Evaluating a mechanism to predict the likely qualitative size of foot-and-mouth disease outbreaks in New Zealand using data available in the early response phase of simulated outbreaks

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.

Estimating the introduction time of highly pathogenic avian influenza into poultry flocks

The estimation of farm-specific time windows for the introduction of highly-pathogenic avian influenza (HPAI) virus can be used to increase the efficiency of disease control measures such as contact tracing and may help to identify risk factors for virus introduction. The aims of this research are to (1) develop and test an accurate approach for estimating farm-specific virus introduction windows and (2) evaluate this approach by applying it to 11 outbreaks of HPAI (H5N8) on Dutch commercial poultry farms during the years 2014 and 2016. We used a stochastic simulation model with susceptible, infectious and recovered/removed disease stages to generate distributions for the period from virus introduction to detection. The model was parameterized using data from the literature, except for the within-flock transmission rate, which was estimated from disease-induced mortality data using two newly developed methods that describe HPAI outbreaks using either a deterministic model (A) or a stochastic approach (B). Model testing using simulated outbreaks showed that both method A and B performed well. Application to field data showed that method A could be successfully applied to 8 out of 11 HPAI H5N8 outbreaks and is the most generally applicable one, when data on disease-induced mortality is scarce.

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.

Environmental persistence of foot-and-mouth disease virus applied to endemic regions

The consequences of foot-and-mouth disease impact regional economies and food security through animal mortality and morbidity, trade restrictions and burdens to veterinary infrastructure. Despite efforts to control the disease, some regions, mostly in warmer climates, persistently report disease outbreaks. Consequently, it is necessary to understand how environmental factors influence transmission, of this economically devastating disease. Extensive research covers basic aetiology and transmission potential of livestock and livestock products for foot-and-mouth disease virus (FMDV), with a subset evaluating environmental survival. However, this subset, completed in the early to mid-20th century in Northern Europe and the United States, is not easily generalized to today's endemic locations. This review uncovered 20 studies, to assess current knowledge and analyse the effects of environmental variables on FMDV survival, using a Cox proportional hazards (Coxph) model. However, the dataset is limited, for example pH was included in three studies and only five studies reported both relative humidity (RH) and temperature. After dropping pH from the analysis, our results suggest that temperature alone does not describe FMDV survival; instead, interactions between RH and temperature have broader impacts across various conditions. For instance, FMDV is expected to survive longer during the wet season (survival at day 50 is ~90% at 16°C and 86% RH) versus the dry season (survival at day 50 approaches 0% at 16°C and 37.5% RH) or comparatively in the UK versus the Southwestern United States. Additionally, survival on vegetation topped 70% on day 75 when conditions exceeded 20°C with high RH (86%), drastically higher than the survival on inanimate surfaces at the same temperature and RH (~0%). This is important in tropical regions, where high temperatures can persist throughout the year, but RH varies. Therefore, parameter estimates, for disease modelling and control in endemic areas, require environmental survival data from a wider range of conditions.

Dairy goat producers' understanding, knowledge and attitudes towards biosecurity and Q-fever in Australia

The Australian dairy goat sector is an emerging animal industry undergoing rapid expansion. Limited information is available within this industry in relation to socio-demographic characteristics and biosecurity implementation. Q-Fever, caused by the bacterium Coxiella burnetii, is a zoonotic disease endemic in Australia, with a range of domestic and wild-animal reservoir species, including goats, with infected pregnant goats posing a significant public health risk. The aim of the current study was to investigate the socio-demographics of Australian dairy goat producers, their biosecurity implementation and levels of understanding, knowledge and attitudes towards Q-Fever. To achieve this aim, a cross-sectional study was conducted, using an online survey and follow-up semi-structured interviews among dairy goat producers. A total of 106 goat producers participated in the online survey (35.3% response rate) and 14 participated in the semi-structured interviews. Findings from this study suggest that most goat producers implement biosecurity practices related to direct animal husbandry, such as separating sick goats (86%), vaccinations (79%) and providing separate kidding space (75%); and, practices minimizing the risk of disease introduction, such as maintaining boundary fences (86%) and isolating incoming animals (67%). However, implementation of other biosecurity practices, such as keeping records of visitors and visitor biosecurity requirements, was inadequate. Furthermore, this study identifies a deficit of knowledge and understanding surrounding Q-Fever in the Australian dairy goat sector, and a disconnect between producers' perception of risk and implementation of known appropriate biosecurity measures. The research has identified that producers rely on 'trusted' community networks to provide advice on biosecurity implementation, due to a perceived absence of industry-specific, reputable information sources. Producers identified those outside of these networks as the 'other'. The creation of this other allows producers to deflect responsibility for individual biosecurity on to the other. A multifaceted approach is necessary to increase knowledge, understanding and perception of risk surrounding Q-fever, and promote positive uptake of biosecurity measures, for improved outcomes for animal and human health.

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.

Reconstructing foot-and-mouth disease outbreaks: a methods comparison of transmission network models

A number of transmission network models are available that combine genomic and epidemiological data to reconstruct networks of who infected whom during infectious disease outbreaks. For such models to reliably inform decision-making they must be transparently validated, robust, and capable of producing accurate predictions within the short data collection and inference timeframes typical of outbreak responses. A lack of transparent multi-model comparisons reduces confidence in the accuracy of transmission network model outputs, negatively impacting on their more widespread use as decision-support tools. We undertook a formal comparison of the performance of nine published transmission network models based on a set of foot-and-mouth disease outbreaks simulated in a previously free country, with corresponding simulated phylogenies and genomic samples from animals on infected premises. Of the transmission network models tested, Lau’s systematic Bayesian integration framework was found to be the most accurate for inferring the transmission network and timing of exposures, correctly identifying the source of 73% of the infected premises (with 91% accuracy for sources with model support >0.80). The Structured COalescent Transmission Tree Inference provided the most accurate inference of molecular clock rates. This validation study points to which models might be reliably used to reconstruct similar future outbreaks and how to interpret the outputs to inform control. Further research could involve extending the best-performing models to explicitly represent within-host diversity so they can handle next-generation sequencing data, incorporating additional animal and farm-level covariates and combining predictions using Ensemble methods and other approaches.

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.