How do resources influence control measures during a simulated outbreak of foot and mouth disease in Australia?

Critically appraised topic: the use of vaccination to control the spread of foot-and-mouth disease in Australian livestock in the event of an incursion

With recent outbreaks of foot-and-mouth disease (FMD) in Indonesia and Bali, industry, government and public concern for its incursion into Australia is increasing. The potential impact of an outbreak on the agricultural industry and national economy could be devastating. To date, research conducted in relation to FMD in Australia predominantly concerns simulations and models performed to predict various outcomes. This project critically appraises the current literature regarding the simulated use of vaccination and its effectiveness for controlling the spread of FMD in Australia in the event of an outbreak. Findings from 10 modelling studies suggest that vaccination is effective at controlling the size and duration of an outbreak (under certain conditions), however, there is less clarity about cost-effectiveness.

Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France

We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R0), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R0 values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination.

ASAS-NANP symposium: mathematical modeling in animal nutrition: agent-based modeling for livestock systems: the mechanics of development and application

Over the last three decades, agent-based modeling/model (ABM) has been one of the most powerful and valuable simulation-based decision modeling techniques used to study the complex dynamic interactions between animals and their environment. ABM is a relatively new modeling technique in the animal research arena, with immense potential for routine decision-making in livestock systems. We describe ABM's fundamental characteristics for developing intelligent modeling systems, exemplify its use for livestock production, and describe commonly used software for designing and developing ABM. After that, we discuss several aspects of the developmental mechanics of an ABM, including (1) how livestock researchers can conceptualize and design a model, (2) the main components of an ABM, (3) different statistical methods of analyzing the outputs, and (4) verification, validation, and replication of an ABM. Then, we perform an overall analysis of the utilities of ABM in different subsystems of the livestock systems ranging from epidemiological prediction to nutritional management to livestock market dynamics. Finally, we discuss the concept of hybrid intelligent models (i.e., merging real-time data streams with intelligent ABM), which have applications in artificial intelligence-based decision-making for precision livestock farming. ABM captures individual agents' characteristics, interactions, and the emergent properties that arise from these interactions; thus, animal scientists can benefit from ABM in multiple ways, including understanding system-level outcomes, analyzing agent behaviors, exploring different scenarios, and evaluating policy interventions. Several platforms for building ABM exist (e.g., NetLogo, Repast J, and AnyLogic), but they have unique features making one more suitable for solving specific problems. The strengths of ABM can be combined with other modeling approaches, including artificial intelligence, allowing researchers to advance our understanding further and contribute to sustainable livestock management practices. There are many ways to develop and apply mathematical models in livestock production that might assist with sustainable development. However, users must be experienced when choosing the appropriate modeling technique and computer platform (i.e., modeling development tool) that will facilitate the adoption of mathematical models by certifying that the model is field-ready and versatile enough for untrained users.

Modelling the field personnel resources to control foot-and-mouth disease outbreaks in New Zealand

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 95^th percentile and maximum number of infected places (IPs) were 78 and 462, respectively, and the 95^th percentile and maximum duration were 69 and 217 days, respectively. However, severe constraints on personnel resources allowed some outbreaks to exceed the size of the UK 2001 FMD epidemic which had 2026 IPs. The number of veterinarians available had a major influence on the size and duration of outbreaks, 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.

What Are the Human Resources Required to Control a Foot-and-Mouth Disease Outbreak in Austria?

Contingency planning allows veterinary authorities to prepare a rapid response in the event of a disease outbreak. A recently published foot-and-mouth disease (FMD) simulation study indicated concerns whether capacity was sufficient to control a potential FMD epidemic in Austria. The objectives of the study presented here were to estimate the human resources required to implement FMD control measures and to identify areas of the operational activities that could potentially delay successful control of the disease. The stochastic spatial simulation model EuFMDiS (The European Foot-and-Mouth Disease Spread Model) was used to simulate a potential FMD outbreak and its economic impact, including different control scenarios based on variations of culling, vaccination, and pre-emptive depopulation. In this context, the utilization of human resources was assessed based on the associated EuFMDiS output regarding the performance of operational activities. The assessments show that the number of personnel needed in an outbreak with a stamping-out policy would reach the peak at the end of the second week of control with a median of 540 (257–926) individuals, out of which 31% would be veterinarians. Approximately 58% of these human resources would be attributable to surveillance, followed by staff for cleaning and disinfection activities. Our analysis demonstrates that, of the operational activities, surveillance personnel were the largest factor influencing the magnitude of the outbreak. The aim of the assessment presented here is to assist veterinary authorities in the contingency planning of required human resources to respond effectively to an outbreak of animal diseases such as FMD.

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.

Development of a transboundary model of livestock disease in Europe

Epidemiological models of notifiable livestock disease are typically framed at a national level and targeted for specific diseases. There are inherent difficulties in extending models beyond national borders as details of the livestock population, production systems and marketing systems of neighbouring countries are not always readily available. It can also be a challenge to capture heterogeneities in production systems, control policies, and response resourcing across multiple countries, in a single transboundary model.

In this paper, we describe EuFMDiS, a continental‐scale modelling framework for transboundary animal disease, specifically designed to support emergency animal disease planning in Europe. EuFMDiS simulates the spread of livestock disease within and between countries and allows control policies to be enacted and resourced on a per‐country basis. It provides a sophisticated decision support tool that can be used to look at the risk of disease introduction, establishment and spread; control approaches in terms of effectiveness and costs; resource management; and post‐outbreak management issues.

Causes of delayed outbreak responses and their impacts on epidemic spread

Livestock diseases have devastating consequences economically, socially and politically across the globe. In certain systems, pathogens remain viable after host death, which enables residual transmissions from infected carcasses. Rapid culling and carcass disposal are well-established strategies for stamping out an outbreak and limiting its impact; however, wait-times for these procedures, i.e. response delays, are typically farm-specific and time-varying due to logistical constraints. Failing to incorporate variable response delays in epidemiological models may understate outbreak projections and mislead management decisions. We revisited the 2001 foot-and-mouth epidemic in the United Kingdom and sought to understand how misrepresented response delays can influence model predictions. Survival analysis identified farm size and control demand as key factors that impeded timely culling and disposal activities on individual farms. Using these factors in the context of an existing policy to predict local variation in response times significantly affected predictions at the national scale. Models that assumed fixed, timely responses grossly underestimated epidemic severity and its long-term consequences. As a result, this study demonstrates how general inclusion of response dynamics and recognition of partial controllability of interventions can help inform management priorities during epidemics of livestock diseases.

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.

Parallels, differences and lessons: a comparison of the management of foot-and-mouth disease and COVID-19 using UK 2001/2020 as points of reference

Foot-and-mouth disease (FMD) is an extremely infectious viral infection of cloven-hoofed animals which is highly challenging to control and can give rise to national animal health crises, especially if there is a lack of pre-existing immunity due to the emergence of new strains or following incursions into disease-free regions. The 2001 FMD epidemic in the UK was on a scale that initially overwhelmed the national veterinary services and was eventually controlled by livestock lockdown and slaughter on an unprecedented scale. In 2020, the rapid emergence of COVID-19 has led to a human pandemic unparalleled in living memory. The enormous logistics of multi-agency control efforts for COVID-19 are reminiscent of the 2001 FMD epidemic in the UK, as are the use of movement restrictions, not normally a feature of human disease control. The UK experience is internationally relevant as few countries have experienced national epidemic crises for both diseases. In this review, we reflect on the experiences and lessons learnt from UK and international responses to FMD and COVID-19 with respect to their management, including the challenge of preclinical viral transmission, threat awareness, early detection, different interpretations of scientific information, lockdown, biosecurity behaviour change, shortage of testing capacity and the choices for eradication versus living with infection. A major lesson is that the similarity of issues and critical resources needed to manage large-scale outbreaks demonstrates that there is benefit to a ‘One Health’ approach to preparedness, with potential for greater cooperation in planning and the consideration of shared critical resources.

Controlling emerging zoonoses at the animal-human interface

BACKGROUND

For many emerging or re-emerging pathogens, cases in humans arise from a mixture of introductions (via zoonotic spillover from animal reservoirs or geographic spillover from endemic regions) and secondary human-to-human transmission. Interventions aiming to reduce incidence of these infections can be focused on preventing spillover or reducing human-to-human transmission, or sometimes both at once, and typically are governed by resource constraints that require policymakers to make choices. Despite increasing emphasis on using mathematical models to inform disease control policies, little attention has been paid to guiding rational disease control at the animal-human interface.

METHODS

We introduce a modeling framework to analyze the impacts of different disease control policies, focusing on pathogens exhibiting subcritical transmission among humans (i.e. pathogens that cannot establish sustained human-to-human transmission). We quantify the relative effectiveness of measures to reduce spillover (e.g. reducing contact with animal hosts), human-to-human transmission (e.g. case isolation), or both at once (e.g. vaccination), across a range of epidemiological contexts.

RESULTS

We provide guidelines for choosing which mode of control to prioritize in different epidemiological scenarios and considering different levels of resource and relative costs. We contextualize our analysis with current zoonotic pathogens and other subcritical pathogens, such as post-elimination measles, and control policies that have been applied.

CONCLUSIONS

Our work provides a model-based, theoretical foundation to understand and guide policy for subcritical zoonoses, integrating across disciplinary and species boundaries in a manner consistent with One Health principles.

Evaluation of strategies using simulation model to control a potential outbreak of highly pathogenic avian influenza among poultry farms in Central Luzon, Philippines

The Philippines confirmed its first epidemic of Highly Pathogenic Avian Influenza (HPAI) on August 11, 2017. It ended in November of 2017. Despite the successful management of the epidemic, reemergence is a continuous threat. The aim of this study was to conduct a mathematical model to assess the spatial transmission of HPAI among poultry farms in Central Luzon. Different control strategies and the current government protocol of 1 km radius pre-emptive culling (PEC) from infected farms were evaluated. The alternative strategies include 0.5km PEC, 1.5km PEC, 2 km PEC, 2.5 km PEC, and 3 km PEC, no pre-emptive culling (NPEC). The NPEC scenario was further modeled with a time of government notification set at 24hours, 48 hours, and 72 hours after the detection. Disease spread scenarios under each strategy were generated using an SEIR (susceptible-exposed-infectious-removed) stochastic model. A spatial transmission kernel was calculated and used to represent all potential routes of infection between farms. We assumed that the latent period occurs between 1–2 days, disease detection at 5–7 days post-infection, notification of authorities at 5–7 days post-detection and start of culling at 1–3 days post notification. The epidemic scenarios were compared based on the number of infected farms, the total number of culled farms, and the duration of the epidemic. Our results revealed that the current protocol is the most appropriate option compared with the other alternative interventions considered among farms with reproductive ratio (R_i) > 1. Shortening the culling radius to 0.5 km increased the duration of the epidemic. Further increase in the PEC zone decreased the duration of the epidemic but may not justify the increased number of farms to be culled. Nonetheless, the no-pre-emptive culling (NPEC) strategy can be an effective alternative to the current protocol if farm managers inform the government immediately within 24 hours of observation of the presence of HPAI in their farms. Moreover, if notification is made on days 1–3 after the detection, the scale and length of the outbreak have been significantly reduced. In conclusion, this study provided a comparison of various control measures for confronting the spread of HPAI infection using the simulation model. Policy makers can use this information to enhance the effectiveness of the current control strategy.

Evaluation of human resources needed and comparison with human resources available to implement emergency vaccination in case of foot and mouth disease outbreaks in Tunisia

Foot and mouth disease (FMD) is a highly contagious viral disease that affects domestic and wild artiodactyl animals and causes considerable economic losses related to outbreak management, production losses and trade impacts. In Tunisia, the last FMD outbreak took place in 2018-2019. The effectiveness of control measures implemented to control FMD depends, in particular, on the human resources used to implement them. Tunisia has the ultimate objective of obtaining OIE status as 'FMD-free with vaccination'. The aim of this study was to determine and compare the necessary and available human resources to control FMD outbreaks in Tunisia using emergency vaccination and to assess the gaps that would play a role in the implementation of the strategy. We developed a resources-requirement grid of necessary human resources for the management of the emergency vaccination campaign launched after the identification of a FMD-infected premises in Tunisia. Field surveys, conducted in the 24 governorates of Tunisia, allowed quantifying the available human resources for several categories of skills considered in the resources-requirement grid. For each governorate, we then compared available and necessary human resources to implement vaccination according to eight scenarios mixing generalised or cattle-targeted vaccination and different levels of human resources. The resources-requirement grid included 11 tasks in three groups: management of FMD-infected premises, organisational tasks and vaccination implementation. The available human resources for vaccination-related tasks included veterinarians and technicians from the public sector and appointed private veterinarians. The comparison of available and necessary human resources showed vaccination-related tasks to be the most time-consuming in terms of managing a FMD outbreak. Increasing the available human resources using appointed private veterinarians allowed performing the emergency vaccination of animals in the governorate in due time, especially if vaccination was targeted on cattle. The overall approach was validated by comparing the predicted and observed durations of a vaccination campaign conducted under the same conditions as during the 2014 Tunisian outbreak. This study could provide support to the Tunisian Veterinary Services or to other countries to optimise the management of a FMD outbreak.

Management strategies for vaccinated animals after an outbreak of foot-and-mouth disease and the impact on return to trade

An incursion of Foot-and-mouth disease (FMD) in a previously FMD-free country can cause significant economic damage from immediate and prolonged closure of FMD-sensitive markets. Whilst emergency vaccination may help contain disease, the presence of vaccinated animals complicates post-outbreak management and the recovery of FMD-free status for return to trade. We present enhancements to the Australian Animal DISease (AADIS) model that allow comparisons of post-outbreak management strategies for vaccinated animals, for the purposes of securing the earliest possible return to trade. Two case studies are provided that compare the retention of vaccinated animals with removal for waste/salvage, and the impact on recovery of FMD-sensitive markets per OIE guidelines. It was found that a vaccinate-and-retain strategy was associated with lower post-outbreak management costs, however this advantage was outweighed by significantly higher trade losses. Under the assumptions of the study there was no cost advantage to salvaging the removed vaccinated animals.

Optimal control of epidemic size and duration with limited resources

The total number of infections (epidemic size) and the time needed for the infection to go extinct (epidemic duration) represent two of the main indicators for the severity of infectious disease epidemics in human and livestock. However, few attempts have been made to address the problem of minimizing at the same time the epidemic size and duration from a theoretical point of view by using optimal control theory. Here, we investigate the multi-objective optimal control problem aiming to minimize, through either vaccination or isolation, a suitable combination of epidemic size and duration when both maximum control effort and total amount of resources available during the entire epidemic period are limited. Application of Pontryagin's Maximum Principle to a Susceptible-Infected-Removed epidemic model, shows that, when the resources are not sufficient to maintain the maximum control effort for the entire duration of the epidemic, the optimal vaccination control admits only bang-bang solutions with one or two switches, while the optimal isolation control admits only bang-bang solutions with one switch. We also find that, especially when the maximum control effort is low, there may exist a trade-off between the minimization of the two objectives. Consideration of this conflict among objectives can be crucial in successfully tackling real-world problems, where different stakeholders with potentially different objectives are involved. Finally, the particular case of the minimum time optimal control problem with limited resources is discussed.

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.

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

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.

Does Size Matter to Models? Exploring the Effect of Herd Size on Outputs of a Herd-Level Disease Spread Simulator

Disease spread modeling is widely used by veterinary authorities to predict the impact of emergency animal disease outbreaks in livestock and to evaluate the cost-effectiveness of different management interventions. Such models require knowledge of basic disease epidemiology as well as information about the population of animals at risk. Essential demographic information includes the production system, animal numbers, and their spatial locations yet many countries with significant livestock industries do not have publically available and accurate animal population information at the farm level that can be used in these models. The impact of inaccuracies in data on model outputs and the decisions based on these outputs is seldom discussed. In this analysis, we used the Australian Animal Disease model to simulate the spread of foot-and-mouth disease seeded into high-risk herds in six different farming regions in New Zealand. We used three different susceptible animal population datasets: (1) a gold standard dataset comprising known herd sizes, (2) a dataset where herd size was simulated from a beta-pert distribution for each herd production type, and (3) a dataset where herd size was simplified to the median herd size for each herd production type. We analyzed the model outputs to compare (i) the extent of disease spread, (ii) the length of the outbreaks, and (iii) the possible impacts on decisions made for simulated outbreaks in different regions. Model outputs using the different datasets showed statistically significant differences, which could have serious implications for decision making by a competent authority. Outbreak duration, number of infected properties, and vaccine doses used during the outbreak were all significantly smaller for the gold standard dataset when compared with the median herd size dataset. Initial outbreak location and disease control strategy also significantly influenced the duration of the outbreak and number of infected premises. The study findings demonstrate the importance of having accurate national-level population datasets to ensure effective decisions are made before and during disease outbreaks, reducing the damage and cost.

Estimation of the transmission dynamics of African swine fever virus within a swine house

The spread of African swine fever virus (ASFV) threatens to reach further parts of Europe. In countries with a large swine production, an outbreak of ASF may result in devastating economic consequences for the swine industry. Simulation models can assist decision makers setting up contingency plans. This creates a need for estimation of parameters. This study presents a new analysis of a previously published study. A full likelihood framework is presented including the impact of model assumptions on the estimated transmission parameters. As animals were only tested every other day, an interpretation was introduced to cover the weighted infectiousness on unobserved days for the individual animals (WIU). Based on our model and the set of assumptions, the within- and between-pen transmission parameters were estimated to βw = 1·05 (95% CI 0·62–1·72), βb = 0·46 (95% CI 0·17–1·00), respectively, and the WIU = 1·00 (95% CI 0–1). Furthermore, we simulated the spread of ASFV within a pig house using a modified SEIR-model to establish the time from infection of one animal until ASFV is detected in the herd. Based on a chosen detection limit of 2·55% equivalent to 10 dead pigs out of 360, the disease would be detected 13–19 days after introduction.

Resource Estimations in Contingency Planning for Foot-and-Mouth Disease

Preparedness planning for a veterinary crisis is important to be fast and effective in the eradication of disease. For countries with a large export of animals and animal products, each extra day in an epidemic will cost millions of Euros due to the closure of export markets. This is important for the Danish husbandry industry, especially the swine industry, which had an export of €4.4 billion in 2012. The purposes of this project were to (1) develop an iterative tool with the aim of estimating the resources needed during an outbreak of foot-and-mouth disease (FMD) in Denmark, (2) identify areas, which can delay the control of the disease. The tool developed should easily be updated, when knowledge is gained from other veterinary crises or during an outbreak of FMD. The stochastic simulation model DTU-DADS was used to simulate spread of FMD in Denmark. For each task occurring during an epidemic of FMD, the time and personnel needed per herd was estimated by a working group with expertise in contingency and crisis management. By combining this information, an iterative model was created to calculate the needed personnel on a daily basis during the epidemic. The needed personnel was predicted to peak within the first week with a requirement of approximately 123 (65–175) veterinarians, 33 (23–64) technicians, and 36 (26–49) administrative staff on day 2, while the personnel needed in the Danish Emergency Management Agency (responsible for the hygiene barrier and initial cleaning and disinfection of the farm) was predicted to be 174 (58–464), mostly recruits. The time needed for surveillance visits was predicted to be the most influential factor in the calculations. Based on results from a stochastic simulation model, it was possible to create an iterative model to estimate the requirements for personnel during an FMD outbreak in Denmark. The model can easily be adjusted, when new information on resources appears from management of other crisis or from new model runs.

Estimating the scale of adverse animal welfare consequences of movement restriction and mitigation strategies in a classical swine fever outbreak

Background

The study aim was to quantify the impact of movement restriction on the well-being of pigs and the associated mitigation responses during a classical swine fever (CSF) outbreak. We developed a stochastic risk assessment model and incorporated Indiana swine industry statistics to estimate the timing and number of swine premises that would encounter overcrowding or feed interruption resulting from movement restriction. Our model also quantified the amount of on-farm euthanasia and movement of pigs to slaughter plants required to alleviate those conditions. We simulated various single-site (i.e., an outbreak initiated from one location) and multiple-site (i.e., an outbreak initiated from more than one location) outbreak scenarios in Indiana to estimate outputs.

Results

The study estimated that 14% of the swine premises in Indiana would encounter overcrowding or feed interruption due to movement restriction implemented during a CSF outbreak. The number of premises that would experience animal welfare conditions was about 2.5 fold of the number of infected premises. On-farm euthanasia needed to be performed on 33% of those swine premises to alleviate adverse animal welfare conditions, and more than 90% of on-farm euthanasia had to be carried out within 2 weeks after the implementation of movement restriction. Conversely, movement of pigs to slaughter plants could alleviate 67% of adverse animal welfare conditions due to movement restriction, and only less than 1% of movement of pigs to slaughter plants had to be initiated in the first 2 weeks of movement restrictions. The risk of secondary outbreaks due to movement of pigs from movement restriction areas to slaughter plants was low and only seven pigs from each shipment needed to be tested for CSF infection to prevent a secondary outbreak.

Conclusions

We found that the scale of adverse animal welfare consequences of movement restriction during a CSF outbreak in Indiana was substantial, and controlled movement of pigs to slaughter plants was an efficient and low-risk alternative mitigation response to on-farm euthanasia. The output estimates generated from this study provide empirical evidence for decision makers to properly incorporate required resources for mitigating adverse animal welfare conditions in CSF outbreak management strategic planning.

Evaluation of Movement Restriction Zone Sizes in Controlling Classical Swine Fever Outbreaks

The objective of this study was to compare the impacts of movement restriction zone sizes of 3, 5, 9, and 11 km with that of 7 km (the recommended zone size in the United States) in controlling a classical swine fever (CSF) outbreak. In addition to zone size, different compliance assumptions and outbreak types (single site and multiple site) were incorporated in the study. Three assumptions of compliance level were simulated: baseline, baseline ± 10%, and baseline ± 15%. The compliance level was held constant across all zone sizes in the baseline simulation. In the baseline ± 10% and baseline ± 15% simulations, the compliance level was increased for 3 and 5 km and decreased for 9 and 11 km from the baseline by the indicated percentages. The compliance level remained constant in all simulations for the 7-km zone size. Four single-site (i.e., with one index premises at the onset of outbreak) and four multiple-site (i.e., with more than one index premises at the onset of outbreak) CSF outbreak scenarios in Indiana were simulated incorporating various zone sizes and compliance assumptions using a stochastic between-premises disease spread model to estimate epidemic duration, percentage of infected, and preemptively culled swine premises. Furthermore, a risk assessment model that incorporated the results from the disease spread model was developed to estimate the number of swine premises under movement restrictions that would experience animal welfare outcomes of overcrowding or feed interruption during a CSF outbreak in Indiana. Compared with the 7-km zone size, the 3-km zone size resulted in a longer median epidemic duration, larger percentages of infected premises, and preemptively culled premises (P’s < 0.001) across all compliance assumptions and outbreak types. With the assumption of a higher compliance level, the 5-km zone size significantly (P < 0.001) reduced the epidemic duration and percentage of swine premises that would experience animal welfare outcomes in both outbreak types, whereas assumption of a lower compliance level for 9- and 11-km zone sizes significantly (P < 0.001) increased the epidemic duration and percentage of swine premises with animal welfare outcomes compared with the 7-km zone size. The magnitude of impact due to a zone size varied across the outbreak types (single site and multiple site). Overall, the 7-km zone size was found to be most effective in controlling CSF outbreaks, whereas the 5-km zone size was comparable to the 7-km zone size in some circumstances.

Ensemble modelling and structured decision-making to support Emergency Disease Management

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application.

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.

Modelling the time at which overcrowding and feed interruption emerge on the swine premises under movement restrictions during a classical swine fever outbreak

A stochastic risk model was developed to estimate the time elapsed before overcrowding (TOC) or feed interruption (TFI) emerged on the swine premises under movement restrictions during a classical swine fever (CSF) outbreak in Indiana, USA. Nursery (19 to 65 days of age) and grow-to-finish (40 to 165 days of age) pork production operations were modelled separately. Overcrowding was defined as the total weight of pigs on premises exceeding 100% to 115% of the maximum capacity of the premises, which was computed as the total weight of the pigs at harvest/transition age. Algorithms were developed to estimate age-specific weight of the pigs on premises and to compare the daily total weight of the pigs with the threshold weight defining overcrowding to flag the time when the total weight exceeded the threshold (i.e. when overcrowding occurred). To estimate TFI, an algorithm was constructed to model a swine producer's decision to discontinue feed supply by incorporating the assumptions that a longer estimated epidemic duration, a longer time interval between the age of pigs at the onset of the outbreak and the harvest/transition age, or a longer progression of an ongoing outbreak would increase the probability of a producer's decision to discontinue the feed supply. Adverse animal welfare conditions were modelled to emerge shortly after an interruption of feed supply. Simulations were run with 100 000 iterations each for a 365-day period. Overcrowding occurred in all simulated iterations, and feed interruption occurred in 30% of the iterations. The median (5th and 95th percentiles) TOC was 24 days (10, 43) in nursery operations and 78 days (26, 134) in grow-to-finish operations. Most feed interruptions, if they emerged, occurred within 15 days of an outbreak. The median (5th and 95th percentiles) time at which either overcrowding or feed interruption emerged was 19 days (4, 42) in nursery and 57 days (4, 130) in grow-to-finish operations. The study findings suggest that overcrowding and feed interruption could emerge early during a CSF outbreak among swine premises under movement restrictions. The outputs derived from the risk model could be used to estimate and evaluate associated mitigation strategies for alleviating adverse animal welfare conditions resulting from movement restrictions.

Simulation of Spread of African Swine Fever, Including the Effects of Residues from Dead Animals

To study the spread of African swine fever (ASF) within a pig unit and the impact of unit size on ASF spread, a simulation model was created. In the model, an animal can be in one of the following stages: susceptible, latent, subclinical, clinical, or recovered. Animals can be infectious during the subclinical stage and are fully infectious during the clinical stage. ASF virus (ASFV) infection through residues of dead animals in the slurries was also modeled in an exponentially fading-out pattern. Low and high transmission rates for ASFV were tested in the model. Robustness analysis was carried out in order to study the impact of uncertain parameters on model predictions. The results showed that the disease may fade out within the pig unit without a major outbreak. Furthermore, they showed that spread of ASFV is dependent on the infectiousness of subclinical animals and the residues of dead animals, the transmission rate of the virus, and importantly the unit size. Moreover, increasing the duration of the latent or the subclinical stages resulted in longer time to disease fade out. The proposed model is a simple and robust tool simulating the spread of ASFV within a pig house taking into account dynamics of ASFV spread and the unit size. The tool can be implemented in simulation models of ASFV spread between herds.

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.

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

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

Species Authentication of Common Meat Based on PCR Analysis of the Mitochondrial COI Gene

Adulteration of meat products and costly animal-derived commodities with their inferior/cheaper counterparts is a grievous global problem. Species authentication is still technical challenging, especially to those deep processed products. The present study described the design of seven sets of species-specific primer based on a high heterozygous region of mitochondrial cytochrome c oxidase subunit I (COI) gene. These primers were proven to have high species specificity and no cross-reactions and unexpected products to different DNA source. Multiplex PCR assay was achieved for rapid and economical identification of four commonly consumed meats (pork, beef, chicken, and mutton). The conventional PCR assay was sensitive down to 0.001 ng of DNA template in the reactant. The developed method was also powerful in detecting as low as 0.1-mg adulterated pork (0.05 % in wt/wt) in an artificial counterfeited mutton. Validation test showed that the assay is specific, reproducible, and robust in commercial deep processed meats, leatherware, and feather commodities. This proposed method will be greatly beneficial to the consumers, food industry, leather, and feather commodity manufacture.

An approach for de-identification of point locations of livestock premises for further use in disease spread modeling

We describe a method for de-identifying point location data used for disease spread modeling to allow data custodians to share data with modeling experts without disclosing individual farm identities. The approach is implemented in an open-source software program that is described and evaluated here. The program allows a data custodian to select a level of de-identification based on the K-anonymity statistic. The program converts a file of true farm locations and attributes into a file appropriate for use in disease spread modeling with the locations randomly modified to prevent re-identification based on location. Important epidemiological relationships such as clustering are preserved to as much as possible to allow modeling similar to those using true identifiable data. The software implementation was verified by visual inspection and basic descriptive spatial analysis of the output. Performance is sufficient to allow de-identification of even large data sets on desktop computers available to any data custodian.

Options for managing animal welfare on intensive pig farms confined by movement restrictions during an outbreak of foot and mouth disease

An outbreak of foot and mouth disease in Australia would trigger a major disease control and eradication program that would include restriction of movement of live animals within defined disease control zones. Experiences from outbreaks in other countries show that restrictions that limit the ability to turn off stock can lead to animal welfare compromise on intensively managed farms that are not infected with the disease. Intensive pig farms are considered to be at high risk of developing welfare problems during a control program due to the imposed movement restrictions and limited space available to house growing pigs. This study was designed to investigate strategies that could be used to mitigate animal welfare problems on intensive pig farms during a simulated outbreak of foot and mouth disease in a livestock dense region of Australia. Three strategies for managing farms affected by animal welfare problems were assessed, including on-farm culling of grower and finisher pigs, on-farm culling of finisher pigs only, and permit-based movement of finisher pigs to slaughter at abattoir. Under traditional approaches of giving infected premises (IP) priority over culling of farms with welfare problems (WP), delays of up to 25 days were experienced prior to culling of WPs. Deployment of vaccination did little to reduce the delay to culling of WPs. These delays were sensitive to resources available for control, with reduced resources increasing the time until welfare problems were addressed. Assigning equal priority to all farms requiring culling regardless of status as IP or WP and culling each as they arose reduced the delay to culling of WPs to no more than 4 days without large increases in either the duration or the size of the outbreaks observed.

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

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