The UK foot-and-mouth disease outbreak - the aftermath

Networks and Models with Heterogeneous Population Structure in Epidemiology

Heterogeneous population structure can have a profound effect on infectious disease dynamics, and is particularly important when investigating “tactical” disease control questions. At times, the nature of the network involved in the transmission of the pathogen (bacteria, virus, macro-parasite, etc.) appears to be clear; however, the nature of the network involved is dependent on the scale (e.g. within-host, between-host, or between-population), the nature of the contact, which ranges from the highly specific (e.g. sexual acts or needle sharing at the person-to-person level) to almost completely non-specific (e.g. aerosol transmission, often over long distances as can occur with the highly infectious livestock pathogen foot-and-mouth disease virus—FMDv—at the farm-to-farm level, e.g. Schley et al. in J. R. Soc. Interface 6:455–462, 2008), and the timescale of interest (e.g. at the scale of the individual, the typical infectious period of the host). Theoretical approaches to examining the implications of particular network structures on disease transmission have provided critical insight; however, a greater challenge is the integration of network approaches with data on real population structures. In this chapter, some concepts in disease modelling will be introduced, the relevance of selected network phenomena discussed, and then results from real data and their relationship to network analyses summarised. These include examinations of the patterns of air traffic and its relation to the spread of SARS in 2003 (Colizza et al. in BMC Med., 2007; Hufnagel et al. in Proc. Natl. Acad. Sci. USA 101:15124–15129, 2004), the use of the extensively documented Great Britain livestock movements network (Green et al. in J. Theor. Biol. 239:289–297, 2008; Robinson et al. in J. R. Soc. Interface 4:669–674, 2007; Vernon and Keeling in Proc. R. Soc. Lond. B, Biol. Sci. 276:469–476, 2009) and the growing interest in combining contact structure data with phylogenetics to identify real contact patterns as they directly relate to diseases of interest (Cottam et al. in PLoS Pathogens 4:1000050, 2007; Hughes et al. in PLoS Pathogens 5:1000590, 2009).

The role of pre-emptive culling in the control of foot-and-mouth disease

The 2001 foot-and-mouth disease epidemic was controlled by culling of infectious premises and pre-emptive culling intended to limit the spread of disease. Of the control strategies adopted, routine culling of farms that were contiguous to infected premises caused the most controversy. Here we perform a retrospective analysis of the culling of contiguous premises as performed in 2001 and a simulation study of the effects of this policy on reducing the number of farms affected by disease. Our simulation results support previous studies and show that a national policy of contiguous premises (CPs) culling leads to fewer farms losing livestock. The optimal national policy for controlling the 2001 epidemic is found to be the targeting of all contiguous premises, whereas for localized outbreaks in high animal density regions, more extensive fixed radius ring culling is optimal. Analysis of the 2001 data suggests that the lowest-risk CPs were generally prioritized for culling, however, even in this case, the policy is predicted to be effective. A sensitivity analysis and the development of a spatially heterogeneous policy show that the optimal culling level depends upon the basic reproductive ratio of the infection and the width of the dispersal kernel. These analyses highlight an important and probably quite general result: optimal control is highly dependent upon the distance over which the pathogen can be transmitted, the transmission rate of infection and local demography where the disease is introduced.

Use of expert opinion for animal disease decisions: an example of foot-and-mouth disease status designation

When data representing a preferred measurement of risk cannot be obtained, as is often the case for global animal diseases, decisions that affect millions of people and their animals are typically made based on expert opinion. Expert opinion can be and has been used to address the critical lack of data existing for prevalence and incidence of many global diseases, including foot-and-mouth disease (FMD). However, when a conclusion based on expert opinion applies to a topic as sensitive as FMD, which has tremendous economic, political, and social implications, care should be taken to understand the accuracy of and differences in the opinion data. The differences in experts' opinions and the relative accuracy of an expert opinion elicitation for "diagnosing" country-level FMD presence were examined for the years 1997-2003 using Bayesian methods. A formal survey of eight international FMD experts revealed that individual experts had different opinions as to the probability of finding FMD in a country. However, a weighted average of the experts' responses was relatively accurate (91% sensitivity and 85% specificity) at identifying the FMD status of a country, compared to using a method that employed information available from World Organization for Animal Health (OIE). The most apparent disagreements between individual experts and available information were found for Indonesia, South Korea, and South America, and, in general, the experts seemed to believe that countries in South Asia were more likely to be positive than other countries that reported FMD cases to OIE. This study highlights new methodology that offers a standardized, quantitative, and systematic means by which expert opinion can be used and assessed.

Quantifying the risk of localised animal movement bans for foot-and-mouth disease

The maintenance of disease-free status from Foot-and-Mouth Disease is of significant socio-economic importance to countries such as the UK. The imposition of bans on the movement of susceptible livestock following the discovery of an outbreak is deemed necessary to prevent the spread of what is a highly contagious disease, but has a significant economic impact on the agricultural community in itself. Here we consider the risk of applying movement restrictions only in localised zones around outbreaks in order to help evaluate how quickly nation-wide restrictions could be lifted after notification. We show, with reference to the 2001 and 2007 UK outbreaks, that it would be practical to implement such a policy provided the basic reproduction ratio of known infected premises can be estimated. It is ultimately up to policy makers and stakeholders to determine the acceptable level of risk, involving a cost benefit analysis of the potential outcomes, but quantifying the risk of spread from different sized zones is a prerequisite for this. The approach outlined is relevant to the determination of control zones and vaccination policies and has the potential to be applied to future outbreaks of other diseases.

Predicting undetected infections during the 2007 foot-and-mouth disease outbreak

Active disease surveillance during epidemics is of utmost importance in detecting and eliminating new cases quickly, and targeting such surveillance to high-risk individuals is considered more efficient than applying a random strategy. Contact tracing has been used as a form of at-risk targeting, and a variety of mathematical models have indicated that it is likely to be highly efficient. However, for fast-moving epidemics, resource constraints limit the ability of the authorities to perform, and follow up, contact tracing effectively. As an alternative, we present a novel real-time Bayesian statistical methodology to determine currently undetected (occult) infections. For the UK foot-and-mouth disease (FMD) epidemic of 2007, we use real-time epidemic data synthesized with previous knowledge of FMD outbreaks in the UK to predict which premises might have been infected, but remained undetected, at any point during the outbreak. This provides both a framework for targeting surveillance in the face of limited resources and an indicator of the current severity and spatial extent of the epidemic. We anticipate that this methodology will be of substantial benefit in future outbreaks, providing a compromise between targeted manual surveillance and random or spatially targeted strategies.

Transient inhibition of foot-and-mouth disease virus replication by siRNAs silencing VP1 protein coding region

Foot-and-mouth disease virus (FMDV) is the causative agent of foot-and-mouth disease, a severe, clinically acute, vesicular disease of cloven-hoofed animals. RNA interference (RNAi) is a mechanism for silencing gene expression post-transcriptionally that is being exploited as a rapid antiviral strategy. To identify efficacious small interfering RNAs (siRNAs) to inhibit the replication of FMDV, candidate siRNAs corresponding to FMDV VP1 gene were designed and synthesized in vitro using T7 RNA polymerase. In reporter assays, five siRNAs showed significant sequence-specific silencing effects on the expression of VP1-EGFP fusion protein from plasmid pVP1-EGFP-N1, which was cotransfected with siRNA into 293T cells. Furthermore, using RT-qPCR, viral titration and viability assay, we identified VP1-siRNA517, VP1-siRNA113 and VP1-siRNA519 that transiently acted as potent inhibitors of FMDV replication when BHK-21 cells were infected with FMDV. In addition, variations within multiple regions of the quasispecies of FMDV were retrospectively revealed by sequencing of FMDV genes, and a single nucleotide substitution was identified as the main factor in resistance to RNAi. Our data demonstrated that the three siRNA molecules synthesized with T7 RNA polymerase could have transient inhibitory effects on the replication of FMDV.

Epidemiological inference for partially observed epidemics: the example of the 2001 foot and mouth epidemic in Great Britain

This paper develops a statistical framework for a retrospective analysis for well-observed livestock epidemics during which intervention policies may conceal cases, thus potentially biasing naively derived parameter and final size estimates. We apply the methods to the 2001 foot and mouth epidemic (FMD) in Great Britain, during which a large number of farms (about 7500) were pre-emptively culled as part of the control effort without ever being diagnosed as being infected. We infer farm-level infectivity and susceptibility parameters, a distribution for the delay from infection to report, together with a time varying farm infectivity profile for farms. Hidden infections among proactively culled farms were accounted for using a data augmentation approach utilising reversible jump MCMC methods. Simulated epidemics derived using the parameter estimates obtained reproduced the 2001 epidemic well. Our analysis demonstrates that time-varying infectivity profiles fit the 2001 data better than naive assumptions of constant infectiousness. We estimate that around 210 (or 2.8%) of the farms proactively culled in the 2001 epidemic were infected. However, for the parameter estimated obtained, preliminary simulation results indicate that had contiguous culling not been applied in 2001, the epidemic might have been substantially larger.

The North American Animal Disease Spread Model: A simulation model to assist decision making in evaluating animal disease incursions

The North American Animal Disease Spread Model is a stochastic, spatial, state-transition simulation model for the spread of highly contagious diseases of animals. It was developed with broad international support to assist policy development and decision making involving disease incursions. User-established parameters define model behavior in terms of disease progression; disease spread by animal-to-animal contact, contact with contaminated personnel or equipment, and airborne dissemination; and the implementation of control measures such as destruction and vaccination. Resources available to implement disease control strategies, as well as the direct costs associated with these strategies, are taken into consideration. The model records a wide variety of measures of the extent of simulated outbreaks and other characteristics. The graphical interface and output visualization features also make it a useful tool for training and preparedness exercises. This model is now being used to evaluate outbreak scenarios and potential control strategies for several economically important exotic animal diseases in the United States, Canada, and elsewhere. NAADSM is freely available via the Internet at http://www.naadsm.org.

Disease dynamics over very different time-scales: foot-and-mouth disease and scrapie on the network of livestock movements in the UK

We analyse the relationship between the network of livestock movements in the UK and the dynamics of two diseases: foot-and-mouth disease (FMD), which has an incubation period of days, and scrapie, which incubates over years. For FMD, the time-scale of expected epidemics is similar to the time-scale of the evolution of the network. We argue that, under appropriate conditions, a static network analysis can be an appropriate tool for gaining insights into disease dynamics even when the relevant time-scales are similar, as with FMD. We show that a subclass of ‘linkage moves’ maintains the network structure, and so removing these links has a dramatic effect on the number of potentially infected farms, an effect corroborated by simulations. In contrast, because scrapie has a low probability of transmission per contact and a long incubation period, a static network representation is probably appropriate; however, the signature of the network in the pattern of transmission is likely to be faint. Scrapie-notifying farms were more likely to be associated with each other via trading at markets than were control farms; however, network community structure proves to be less representative of prevalence patterns than geographical region. These contradictory indicators emphasize that appropriate observation time frames and good discrimination among types of potentially infectious contacts are vital in order for network analysis to be a valuable epidemiological tool.

Transmission heterogeneity and control strategies for infectious disease emergence

Background

The control of emergence and spread of infectious diseases depends critically on the details of the genetic makeup of pathogens and hosts, their immunological, behavioral and ecological traits, and the pattern of temporal and spatial contacts among the age/stage-classes of susceptible and infectious host individuals.

Methods and Findings

We show that failing to acknowledge the existence of heterogeneities in the transmission rate among age/stage-classes can make traditional eradication and control strategies ineffective, and in some cases, policies aimed at controlling pathogen emergence can even increase disease incidence in the host. When control strategies target for reduction in numbers those subsets of the population that effectively limit the production of new susceptible individuals, then control can produce a flush of new susceptibles entering the population. The availability of a new cohort of susceptibles may actually increase disease incidence. We illustrate these general points using Classical Swine Fever as a reference disease.

Conclusion

Negative effects of culling are robust to alternative formulations of epidemiological processes and underline the importance of better assessing transmission structure in the design of wildlife disease control strategies.

Space–time interaction as an indicator of local spread during the 2001 FMD outbreak in the UK

During the 2001 FMD outbreak in the UK, decisions on the level of implementation of control measures were supported by predictive models. Models were mainly used as macro-level tools to predict the behaviour of the disease in the whole country rather than at the local level. Here we explore the use of the magnitude and characteristics of the space-time interaction as an indicator of local spread and, indirectly, of the effectiveness of control measures aimed at reducing short-range transmission during the course of a major livestock disease epidemic. The spatiotemporal evolution patterns are described in the four main clusters that were observed during the outbreak by means of the hazard rate and space-time K-function (K(s,t)). For each local outbreak, the relative measure D(0)(s,t), derived from K(s,t), which represents the excess risk attributable to the space-time interaction was calculated for consecutive 20-day temporal windows to represent the dynamics of the space-time interaction. The dynamics of the spatiotemporal interaction were very different among the four local clusters, suggesting that the intensity of local spread, and therefore the effectiveness of control measures, markedly differed between local outbreaks. The large heterogeneity observed in the relative impact of being close in time and space to an infected premises suggests that the decision making in relation to control of the outbreak would have benefited from indicators of local spread which could be used to complement global predictive modelling results. Despite its limitations, our results suggest that the real-time analysis of the space-time interaction can be a valuable decision support tool during the course of a livestock disease epidemic.

Demographic structure and pathogen dynamics on the network of livestock movements in Great Britain

Using a novel interpretation of dynamic networks, we analyse the network of livestock movements in Great Britain in order to determine the risk of a large epidemic of foot-and-mouth disease (FMD). This network is exceptionally well characterized, as there are legal requirements that the date, source, destination and number of animals be recorded and held on central databases. We identify a percolation threshold in the structure of the livestock network, indicating that, while there is little possibility of a national epidemic of FMD in winter when the catastrophic 2001 epidemic began, there remains a risk in late summer or early autumn. These predictions are corroborated by a non-parametric simulation in which the movements of livestock in 2003 and 2004 are replayed as they occurred. Despite the risk, we show that the network displays small-world properties which can be exploited to target surveillance and control and drastically reduce this risk.

Infectious disease control using contact tracing in random and scale-free networks

Contact tracing aims to identify and isolate individuals that have been in contact with infectious individuals. The efficacy of contact tracing and the hierarchy of traced nodes-nodes with higher degree traced first-is investigated and compared on random and scale-free (SF) networks with the same number of nodes N and average connection K. For values of the transmission rate larger than a threshold, the final epidemic size on SF networks is smaller than that on corresponding random networks. While in random networks new infectious and traced nodes from all classes have similar average degrees, in SF networks the average degree of nodes that are in more advanced stages of the disease is higher at any given time. On SF networks tracing removes possible sources of infection with high average degree. However a higher tracing effort is required to control the epidemic than on corresponding random networks due to the high initial velocity of spread towards the highly connected nodes. An increased latency period fails to significantly improve contact tracing efficacy. Contact tracing has a limited effect if the removal rate of susceptible nodes is relatively high, due to the fast local depletion of susceptible nodes.

Multiplexed Detection of Antibodies to Nonstructural Proteins of Foot-and-Mouth Disease Virus

Liquid array technology was used to develop a multiplexed assay for the detection of antibodies to viral nonstructural proteins (NSPs), raised in cattle in response to infection with foot-and-mouth disease (FMD) virus. Two assays, one based on recombinant NSPs and the other on synthetically produced peptides, were developed and compared side-by-side. Serum samples from serial bleeds of cattle, each experimentally infected with one of the seven serotypes (C, A, O, Asia, SAT1, SAT2, SAT3) of FMD virus were analyzed. A distinct pattern in the detection of NSP antibodies and a close correlation of the recombinant protein and peptide-based assays were observed. The detection of antibodies to NSPs is a method to differentiate FMD-infected and FMD-vaccinated animals, and a high-throughput assay would be an invaluable tool in the case of an outbreak of FMD in North America, when emergency vaccination may be utilized to spare vaccinated, noninfected animals from slaughter and subsequent disposal.

Disease contact tracing in random and clustered networks

The efficacy of contact tracing, be it between individuals (e.g. sexually transmitted diseases or severe acute respiratory syndrome) or between groups of individuals (e.g. foot-and-mouth disease; FMD), is difficult to evaluate without precise knowledge of the underlying contact structure; i.e. who is connected to whom? Motivated by the 2001 FMD epidemic in the UK, we determine, using stochastic simulations and deterministic 'moment closure' models of disease transmission on networks of premises (nodes), network and disease properties that are important for contact tracing efficiency. For random networks with a high average number of connections per node, little clustering of connections and short latency periods, contact tracing is typically ineffective. In this case, isolation of infected nodes is the dominant factor in determining disease epidemic size and duration. If the latency period is longer and the average number of connections per node small, or if the network is spatially clustered, then the contact tracing performs better and an overall reduction in the proportion of nodes that are removed during an epidemic is observed.