The impact of local heterogeneity on alternative control strategies for foot-and-mouth disease

The 2001 epidemic of foot-and-mouth disease (FMD) in the UK resulted in the death of nearly 10 million livestock at a cost that was estimated to be up to 8 billion pounds. Owing to the controversy surrounding the epidemic, the question of whether or not alternative policies would have resulted in significantly better control of the epidemic remains of great interest. A hexagonal lattice simulation of FMD in Cumbria is used to address the central question of whether or not better use could have been made of expert knowledge of FMD transmission to target pre-emptive culling, by assuming that the premises at greatest risk of becoming infected can be targeted for culling. The 2000 UK census and the epidemiological database collected during the epidemic are used to describe key characteristics of disease transmission, and the model is fit to the epidemic time-series. Under the assumptions of the model, the parameters that best fit the epidemic in Cumbria indicate that a policy based on expert knowledge would have exacerbated the epidemic compared with the policy as implemented. However, targeting more distant, high-risk farms could be more valuable under different epidemic conditions, notably, if risk factors of sufficient magnitude could be identified to aid in prioritizing vaccination or culling of farms at high risk of becoming infected.     

Adaptive Management and the Value of Information: Learning Via Intervention in Epidemiology

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding.     

Herd-level risk factors associated with tuberculosis breakdowns among cattle herds in England before the 2001 foot-and-mouth disease epidemic

A case-control study of the factors associated with the risk of a bovine tuberculosis (TB) breakdown in cattle herds was undertaken within the randomized badger culling trial (RBCT). TB breakdowns occurring prior to the 2001 foot-and-mouth disease epidemic in three RBCT triplets were eligible to be cases; controls were selected from the same RBCT area. Data from 151 case farms and 117 control farms were analysed using logistic regression. The strongest factors associated with an increased TB risk were movement of cattle onto the farm from markets or farm sales, operating a farm over multiple premises and the use of either covered yard or 'other' housing types. Spreading artificial fertilizers or farmyard manure on grazing land were both associated with decreased risk. These first case-control results from the RBCT will be followed by similar analyses as more data become available.     

Risk maps for the spread of highly pathogenic avian influenza in poultry

Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens. Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner. A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. The authors show how an estimate of the transmission kernel naturally provides estimates of the critical farm density and local reproduction numbers, which allows one to evaluate the effectiveness of control strategies. For avian influenza, the analyses show that there are two poultry-dense areas in The Netherlands where epidemic spread is possible, and in which local control measures are unlikely to be able to halt an unfolding epidemic. In these regions an epidemic can only be brought to an end by the depletion of susceptible farms by infection or massive culling. The analyses provide an estimate of the spatial range over which highly pathogenic avian influenza viruses spread between farms, and emphasize that control measures aimed at controlling such outbreaks need to take into account the local density of farms.     

React or wait: which optimal culling strategy to control infectious diseases in wildlife

We applied optimal control theory to an SI epidemic model to identify optimal culling strategies for diseases management in wildlife. We focused on different forms of the objective function, including linear control, quadratic control, and control with limited amount of resources. Moreover, we identified optimal solutions under different assumptions on disease-free host dynamics, namely: self-regulating logistic growth, Malthusian growth, and the case of negligible demography. We showed that the correct characterization of the disease-free host growth is crucial for defining optimal disease control strategies. By analytical investigations of the model with negligible demography, we demonstrated that the optimal strategy for the linear control can be either to cull at the maximum rate at the very beginning of the epidemic (reactive culling) when the culling cost is low, or never to cull, when culling cost is high. On the other hand, in the cases of quadratic control or limited resources, we demonstrated that the optimal strategy is always reactive. Numerical analyses for hosts with logistic growth showed that, in the case of linear control, the optimal strategy is always reactive when culling cost is low. In contrast, if the culling cost is high, the optimal strategy is to delay control, i.e. not to cull at the onset of the epidemic. Finally, we showed that for diseases with the same basic reproduction number delayed control can be optimal for acute infections, i.e. characterized by high disease-induced mortality and fast dynamics, while reactive control can be optimal for chronic ones.     

Epidemiological consequences of an incursion of highly pathogenic H5N1 avian influenza into the British poultry flock

Highly pathogenic avian influenza and in particular the H5N1 strain has resulted in the culling of millions of birds and continues to pose a threat to poultry industries worldwide. The recent outbreak of H5N1 in the UK highlights the need for detailed assessment of the consequences of an incursion and of the efficacy of control strategies. Here, we present results from a model of H5N1 propagation within the British poultry industry. We find that although the majority of randomly seeded incursions do not spread beyond the initial infected premises, there is significant potential for widespread infection. The efficacy of the European Union strategy for disease control is evaluated and our simulations emphasize the pivotal role of duck farms in spreading H5N1.     

Control of a highly pathogenic H5N1 avian influenza outbreak in the GB poultry flock

The identification of H5N1 in domestic poultry in Europe has increased the risk of infection reaching most industrialized poultry populations. Here, using detailed data on the poultry population in Great Britain (GB), we show that currently planned interventions based on movement restrictions can be expected to control the majority of outbreaks. The probability that controls fail to keep an outbreak small only rises to significant levels if most transmission occurs via mechanisms which are both untraceable and largely independent of the local density of premises. We show that a predictor of the need to intensify control efforts in GB is whether an outbreak exceeds 20 infected premises. In such a scenario neither localized reactive vaccination nor localized culling are likely to have a substantial impact. The most effective of these contingent interventions are large radius (10 km) localized culling and national vaccination. However, the modest impact of these approaches must be balanced against their substantial inconvenience and cost.     

Disease Prevention versus Data Privacy: Using Landcover Maps to Inform Spatial Epidemic Models

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock.     

Contact structures in the poultry industry in Great Britain: Exploring transmission routes for a potential avian influenza virus epidemic

Background  

The commercial poultry industry in United Kingdom (UK) is worth an estimated ￡3.4 billion at retail value, producing over 174 million birds for consumption per year. An epidemic of any poultry disease with high mortality or which is zoonotic, such as avian influenza virus (AIV), would result in the culling of significant numbers of birds, as seen in the Netherlands in 2003 and Italy in 2000. Such an epidemic would cost the UK government millions of pounds in compensation costs, with further economic losses through reduction of international and UK consumption of British poultry. In order to better inform policy advisers and makers on the potential for a large epidemic in GB, we investigate the role that interactions amongst premises within the British commercial poultry industry could play in promoting an AIV epidemic, given an introduction of the virus in a specific part of poultry industry in Great Britain (GB).     

Forecasting the 2001 Foot-and-Mouth Disease Epidemic in the UK

Near real-time epidemic forecasting approaches are needed to respond to the increasing number of infectious disease outbreaks. In this paper, we retrospectively assess the performance of simple phenomenological models that incorporate early sub-exponential growth dynamics to generate short-term forecasts of the 2001 foot-and-mouth disease epidemic in the UK. For this purpose, we employed the generalized-growth model (GGM) for pre-peak predictions and the generalized-Richards model (GRM) for post-peak predictions. The epidemic exhibits a growth-decelerating pattern as the relative growth rate declines inversely with time. The uncertainty of the parameter estimates \( (r{\text{ and }}p) \) narrows down and becomes more precise using an increasing amount of data of the epidemic growth phase. Indeed, using only the first 10–15 days of the epidemic, the scaling of growth parameter (p) displays wide uncertainty with the confidence interval for p ranging from values ~ 0.5 to 1.0, indicating that less than 15 epidemic days of data are not sufficient to discriminate between sub-exponential (i.e., p < 1) and exponential growth dynamics (i.e., p = 1). By contrast, using 20, 25, or 30 days of epidemic data, it is possible to recover estimates of p around 0.6 and the confidence interval is substantially below the exponential growth regime. Local and national bans on the movement of livestock and a nationwide cull of infected and contiguous premises likely contributed to the decelerating trajectory of the epidemic. The GGM and GRM provided useful 10-day forecasts of the epidemic before and after the peak of the epidemic, respectively. Short-term forecasts improved as the model was calibrated with an increasing length of the epidemic growth phase. Phenomenological models incorporating generalized-growth dynamics are useful tools to generate short-term forecasts of epidemic growth in near real time, particularly in the context of limited epidemiological data as well as information about transmission mechanisms and the effects of control interventions.     

Neighbourhood control policies and the spread of infectious diseases

We present a model of a control programme for a disease outbreak in a population of livestock holdings. Control is achieved by culling infectious holdings when they are discovered and by the pre-emptive culling of livestock on holdings deemed to be at enhanced risk of infection. Because the pre-emptive control programme cannot directly identify exposed holdings, its implementation will result in the removal of both infected and uninfected holdings. This leads to a fundamental trade-off: increased levels of control produce a greater reduction in transmission by removing more exposed holdings, but increase the number of uninfected holdings culled. We derive an expression for the total number of holdings culled during the course of an outbreak and demonstrate that there is an optimal control policy, which minimizes this loss. Using a metapopulation model to incorporate local clustering of infection, we examine a neighbourhood control programme in a locally spreading outbreak. We find that there is an optimal level of control, which increases with increasing basic reproduction ratio, R(0); moreover, implementation of control may be optimal even when R(0) < 1. The total loss to the population is relatively insensitive to the level of control as it increases beyond the optimal level, suggesting that over-control is a safer policy than under-control.     

Accuracy of models for the 2001 foot-and-mouth epidemic

Since 2001 models of the spread of foot-and-mouth disease, supported by the data from the UK epidemic, have been expounded as some of the best examples of problem-driven epidemic models. These claims are generally based on a comparison between model results and epidemic data at fairly coarse spatio-temporal resolution. Here, we focus on a comparison between model and data at the individual farm level, assessing the potential of the model to predict the infectious status of farms in both the short and long terms. Although the accuracy with which the model predicts farms reporting infection is between 5 and 15%, these low levels are attributable to the expected level of variation between epidemics, and are comparable to the agreement between two independent model simulations. By contrast, while the accuracy of predicting culls is higher (20-30%), this is lower than expected from the comparison between model epidemics. These results generally support the contention that the type of the model used in 2001 was a reliable representation of the epidemic process, but highlight the difficulties of predicting the complex human response, in terms of control strategies to the perceived epidemic risk.     

The importance of culling in Johne's disease control

Johne's disease is caused by Mycobacterium avium subsp. paratuberculosis (MAP) infection and results in economic losses in the dairy industry. To control MAP transmission in herds, test-based culling has been recommended and immediate culling of high shedding animals is typically implemented. In this study, we quantified the effects of MAP control in US dairy herds, using the basic reproduction ratio R₀. The effectiveness of culling strategies was evaluated for good and poor herd management (low- and high-transmission rates, respectively) by a phase diagram approach. To establish a quantitative relationship between culling rates and test properties, we defined the average detection times for low and high shedding animals. The effects of various culling strategies and test characteristics, such as test sensitivity, test turnaround time, and testing interval, were analyzed. To understand the overall effect of model parameters on R₀, we performed global uncertainty and sensitivity analyses. We also evaluated the effectiveness of culling only high shedding animals by comparing three test methods (fecal culture, fecal polymerase chain reaction, PCR, and enzyme-linked immunosorbent assay, ELISA). Our study shows that, in the case of good herd management, culling of only high shedding animals may be effective in controlling MAP transmission. However, in the case of poor management, in addition to immediate culling of high shedding animals, culling of low shedding animals (based on the fecal culture test) will be necessary. Culling of low shedding animals may be delayed 6-12 months, however, if a shorter testing interval is applied. This study suggests that if farmers prefer culling only high shedding animals, faster MAP detection tests (such as the fecal PCR and ELISA) of higher sensitivity should be applied with high testing frequency, particularly on farms with poor management. Culling of infectious animals with a longer testing interval is generally not effective to control MAP.     

Landscape scale impacts of culling upon a European grey squirrel population: can trapping reduce population size and decrease the threat of squirrelpox virus infection for the native red squirrel?

The control of grey squirrels (Sciurus carolinensis) is widely undertaken as a conservation measure to protect red squirrel (Sciurus vulgaris) populations in the UK. However, inconsistencies and omissions in data collection, as well as fluctuating financial resourcing of control efforts, have meant that it has to date proved difficult to quantify the impact of any regional control initiative upon populations. Here we have scrutinized a 13 years period (1998–2010) within an ongoing grey squirrel control project that reflects the resource challenges typically faced by red squirrel conservation programmes. We present evidence that despite variation in grey squirrel control intensity, the abundance of grey squirrels ultimately decreased significantly. Trapping success was significantly higher in spring and summer months and a greater abundance of grey squirrels was found in deciduous woodland and hazel dominated scrub relative to other habitats; two findings that reinforce existing guidance within national control best practice. Grey squirrels carry an infection that causes epidemic pathogenic disease if spread to the native red squirrel. We observed that the proportion of seropositive grey squirrels decreased constantly from 2003 to 2010 when only 4 % of sampled animals were seropositive. This discovery indicates that culling can in parallel remove both the competitive and disease threat posed to red by grey squirrels. The historical paucity of scientific data on the effectiveness of grey squirrel control as a tactic in UK red squirrel conservation means that the findings of this study will significantly advance conservation best practice and inform the development of future national strategy.     

An analysis of the possible effects of the 2001 foot and mouth disease epidemic on grass pollen concentrations in the Midlands, UK

The 2001 grass pollen season in the United Kingdom was notably severe. An epidemic of foot and mouth disease (FMD) occurred in the UK during February and spread through the country during the summer. The media claimed that the control measures of culling infected animals and the restricted movement of stock, led to reduced grazing allowing pastures to flower more than in previous years. This study aimed to examine whether the severity was due only to weather factors or if the control measures also contributed. Three pollen sites from the FMD-affected Midlands region were investigated and compared with two sites from regions unaffected for differences in pollen catches, culling levels and weather. The June pollen catch in the Midlands was particularly high but this pattern also features in areas such as Cambridge in the East that were minimally affected by the epidemic. In most of the catchment areas affected by FMD the quantity of animals culled was less than 10% of the total livestock. In areas where culling was concentrated we can assume that there would have been some localized affect on the pollen levels. The results show that the main influencing variable on the 2001 grass pollen counts in the Midlands was the weather and that culling due to the foot and mouth epidemic did not exert an important influence at the regional level.     

An analysis of the possible effects of the 2001 foot and mouth disease epidemic on grass pollen concentrations in the Midlands, UK

The 2001 grass pollen season in the United Kingdom was notably severe. An epidemic of foot and mouth disease (FMD) occurred in the UK during February and spread through the country during the summer. The media claimed that the control measures of culling infected animals and the restricted movement of stock, led to reduced grazing allowing pastures to flower more than in previous years. This study aimed to examine whether the severity was due only to weather factors or if the control measures also contributed. Three pollen sites from the FMD-affected Midlands region were investigated and compared with two sites from regions unaffected for differences in pollen catches, culling levels and weather. The June pollen catch in the Midlands was particularly high but this pattern also features in areas such as Cambridge in the East that were minimally affected by the epidemic. In most of the catchment areas affected by FMD the quantity of animals culled was less than 10% of the total livestock. In areas where culling was concentrated we can assume that there would have been some localized affect on the pollen levels. The results show that the main influencing variable on the 2001 grass pollen counts in the Midlands was the weather and that culling due to the foot and mouth epidemic did not exert an important influence at the regional level.     

An analysis of the possible effects of the 2001 foot and mouth disease epidemic on grass pollen concentrations in the Midlands,UK

The 2001 grass pollen season in the United Kingdom was notably severe. An epidemic of foot and mouth disease (FMD) occurred in the UK during February and spread through the country during the summer. The media claimed that the control measures of culling infected animals and the restricted movement of stock, led to reduced grazing allowing pastures to flower more than in previous years. This study aimed to examine whether the severity was due only to weather factors or if the control measures also contributed. Three pollen sites from the FMD-affected Midlands region were investigated and compared with two sites from regions unaffected for differences in pollen catches, culling levels and weather. The June pollen catch in the Midlands was particularly high but this pattern also features in areas such as Cambridge in the East that were minimally affected by the epidemic. In most of the catchment areas affected by FMD the quantity of animals culled was less than 10% of the total livestock. In areas where culling was concentrated we can assume that there would have been some localized affect on the pollen levels. The results show that the main influencing variable on the 2001 grass pollen counts in the Midlands was the weather and that culling due to the foot and mouth epidemic did not exert an important influence at the regional level.     

Balancing Detection and Eradication for Control of Epidemics: Sudden Oak Death in Mixed-Species Stands

Culling of infected individuals is a widely used measure for the control of several plant and animal pathogens but culling first requires detection of often cryptically-infected hosts. In this paper, we address the problem of how to allocate resources between detection and culling when the budget for disease management is limited. The results are generic but we motivate the problem for the control of a botanical epidemic in a natural ecosystem: sudden oak death in mixed evergreen forests in coastal California, in which species composition is generally dominated by a spreader species (bay laurel) and a second host species (coast live oak) that is an epidemiological dead-end in that it does not transmit infection but which is frequently a target for preservation. Using a combination of an epidemiological model for two host species with a common pathogen together with optimal control theory we address the problem of how to balance the allocation of resources for detection and epidemic control in order to preserve both host species in the ecosystem. Contrary to simple expectations our results show that an intermediate level of detection is optimal. Low levels of detection, characteristic of low effort expended on searching and detection of diseased trees, and high detection levels, exemplified by the deployment of large amounts of resources to identify diseased trees, fail to bring the epidemic under control. Importantly, we show that a slight change in the balance between the resources allocated to detection and those allocated to control may lead to drastic inefficiencies in control strategies. The results hold when quarantine is introduced to reduce the ingress of infected material into the region of interest.     

Moral Convictions and Culling Animals: A Survey in the Netherlands

ABSTRACT

In this paper the results are presented of a national survey in the Netherlands. The aim was to identify and describe the convictions about animals that people have in Dutch society and the role of these in judgments on the culling of healthy animals during an animal disease epidemic. A total of 1,999 responses was received and two groups of respondents were distinguished: A profile (50% of the respondents) and B profile (28%). The A profile respondents considered humans to be superior to animals, whereas the B profile respondents considered both to be equal. Both groups were of the opinion that animals have value, that people have a duty to care for and protect all animals, and that all animals have a right to life. These convictions were based on a number of values, such as animal life, the ability of animals to feel pain and emotions (sentience), and the importance of animal species in the ecosystem. The results of a case study suggest that convictions play a role in judgment. More A respondents agreed with the culling of healthy animals during an animal disease epidemic. More B respondents partly (dis)agreed or disagreed with this. Most respondents (A: 81%, B: 61%) agreed with culling to protect human life. The most important argument against culling was the value of animal life. The A respondents rated all arguments against culling significantly lower than did the B respondents.