Infectious disease modelling to inform policy.

With modelling becoming increasingly important in helping to inform decisions about animal diseases, it is essential that the process be optimised to gain the maximum benefit for the decision-maker. Here, the authors set out ten steps that can improve this process for all concerned. Four steps describe initialisation to ensure that the question, answer and timescale are defined; two steps describe the modelling process and quality assurance; and four steps describe the reporting stage. The authors believe that this greater emphasis at the beginning and end of a modelling project will increase the relevance of the work and understanding of the results, and thus contribute towards better decision-making.

Compte tenu de l'importance croissante de la modélisation pour documenter les décisions sur les maladies animales, il est essentiel d'optimiser le processus afin de le rendre le plus profitable possible pour les personnes décisionnaires. Les auteurs définissent dix étapes permettant d'améliorer le processus pour tous les intervenants. Quatre étapes concernent la phase de démarrage et visent à s'assurer que les questions posées, les réponses obtenues et le calendrier sont bien définis ; les deux étapes suivantes portent sur le processus de modélisation et sur l'assurance qualité ; les quatre dernières décrivent la phase d'élaboration des rapports. Les auteurs estiment que cette attention particulière accordée aux phases de démarrage et d'achèvement d'un projet de modélisation rend l'exercice plus pertinent et améliore la compréhension des résultats, ce qui contribue à une meilleure prise de décisions.

Dada la creciente importancia que está cobrando la modelización como herramienta para ayudar a fundamentar las decisiones relativas a enfermedades animales, es esencial optimizar el proceso para que las instancias decisorias puedan aprovecharlo al máximo. Los autores exponen diez pasos que pueden mejorar el proceso para cuantos trabajan en este ámbito. En cuatro pasos se describe la inicialización, que sirve para definir debidamente la pregunta, la respuesta y la escala temporal de que se trate. En otros dos pasos se describe el proceso de modelización y de garantía de calidad, mientras que en los últimos cuatro pasos se describe la fase de producción de informes. Los autores consideran que el hecho de otorgar mayor peso a las fases iniciales y finales de un proyecto de modelización hará que el trabajo gane en pertinencia y que se entiendan mejor sus resultados, lo que a su vez contribuye a un proceso más eficaz de adopción de decisiones.

Risk-based strategies for surveillance of tuberculosis infection in cattle for low-risk areas in England and Scotland.

Disease surveillance can be made more effective by either improving disease detection, providing cost savings, or doing both. Currently, cattle herds in low-risk areas (LRAs) for bovine tuberculosis (bTB) in England are tested once every 4 years. In Scotland, the default herd testing frequency is also 4 years, but a risk-based system exempts some herds from testing altogether. To extend this approach to other areas, a bespoke understanding of at-risk herds and how risk-based surveillance can affect bTB detection is required. Here, we use a generalized linear mixed model to inform a Bayesian probabilistic model of freedom from infection and explore risk-based surveillance strategies in LRAs and Scotland. Our analyses show that in both areas the primary herd-level risk factors for bTB infection are the size of the herd and purchasing cattle from high-risk areas of Great Britain and/or Ireland. A risk-based approach can improve the current surveillance system by both increasing detection (9% and 7% fewer latent infections), and reducing testing burden (6% and 26% fewer animal tests) in LRAs and Scotland, respectively. Testing at-risk herds more frequently can also improve the level of detection by identifying more infected cases and reducing the hidden burden of the disease, and reduce surveillance effort by exempting low-risk herds from testing.

Plasmodium knowlesi transmission: integrating quantitative approaches from epidemiology and ecology to understand malaria as a zoonosis.

The public health threat posed by zoonotic Plasmodium knowlesi appears to be growing: it is increasingly reported across South East Asia, and is the leading cause of malaria in Malaysian Borneo. Plasmodium knowlesi threatens progress towards malaria elimination as aspects of its transmission, such as spillover from wildlife reservoirs and reliance on outdoor-biting vectors, may limit the effectiveness of conventional methods of malaria control. The development of new quantitative approaches that address the ecological complexity of P. knowlesi, particularly through a focus on its primary reservoir hosts, will be required to control it. Here, we review what is known about P. knowlesi transmission, identify key knowledge gaps in the context of current approaches to transmission modelling, and discuss the integration of these approaches with clinical parasitology and geostatistical analysis. We highlight the need to incorporate the influences of fine-scale spatial variation, rapid changes to the landscape, and reservoir population and transmission dynamics. The proposed integrated approach would address the unique challenges posed by malaria as a zoonosis, aid the identification of transmission hotspots, provide insight into the mechanistic links between incidence and land use change and support the design of appropriate interventions.

Use of genomics to track bovine tuberculosis transmission.

The control of any infectious disease of livestock is made more difficult by the presence of a wildlife reservoir, as the reservoir is often poorly observed and difficult to manage. This problem is particularly acute for bovine tuberculosis (bTB) because the long duration of infection and low levels of infectiousness make tracing the sources of infection difficult. For over 30 years, the process of contact tracing has been aided by the exploitation of molecular markers in the pathogen, but this has largely only been capable of characterising broad associations between large communities of similar types. However, the recent advent of mass high-throughput 'whole-genome' sequencing (WGS) has revolutionised forensic epidemiology for other diseases, and now it has the potential to do so for bTB. In this review, the authors consider the historical context of WGS use and look at what prior molecular techniques have already achieved. They outline the key approaches to interpreting WGS data and consider both the role of advanced analytical techniques that exploit the evolutionary and epidemiological properties of the system and the problems associated with quantifying the role of hidden reservoirs of disease. Finally, they consider the particular difficulties associated with developing this technology for routine diagnostics and its potential for mass use.

Les maladies infectieuses affectant les animaux d'élevage sont plus difficiles à contrôler lorsqu'il existe un réservoir sauvage, celui-ci étant souvent difficile à observer et à gérer. Ce problème est particulièrement crucial dans le cas de la tuberculose bovine en raison de la durée prolongée de l'infection et des faibles niveaux d'infectiosité qui rendent difficile le traçage des sources d'infection. Pendant plus de 30 ans, le processus de traçage des contacts s'est appuyé sur l'exploitation de marqueurs moléculaires au sein de l'agent pathogène, mais cette technique n'a guère pu aller au-delà d'une caractérisation d'associations générales entre vastes communautés de types similaires. L'avènement récent du séquençage massif à haut débit du génome entier a toutefois révolutionné l'épidémiologie légale appliquée à d'autres maladies, et il en ira bientôt probablement de même pour la tuberculose bovine. Les auteurs de cette synthèse s'intéressent au contexte historique de la mise au point du séquençage du génome entier en relevant ce que les techniques moléculaires antérieures avaient déjà accompli. Ils soulignent les principales méthodes pour interpréter les données générées par le séquençage du génome entier et examinent aussi bien le rôle des techniques analytiques les plus avancées basées sur l'exploitation des propriétés évolutionnistes et épidémiologiques du système que les problèmes qui se posent lorsqu'on cherche à quantifier le rôle joué par les réservoirs inapparents d'une maladie. Enfin, ils exposent les difficultés particulières liées à la mise en oeuvre de cette technologie pour des applications diagnostiques de routine ainsi que son potentiel d'utilisation à grande échelle.

La presencia de un reservorio en la fauna salvaje siempre complica la lucha contra las enfermedades infecciosas del ganado, en la medida en que esos reservorios son observados con poca frecuencia y resultan difíciles de gestionar. Este problema cobra especial gravedad en el caso de la tuberculosis bovina, pues la larga duración de la infección y los bajos niveles de infecciosidad hacen difícil localizar el origen de los focos. Durante más de 30 años se han empleado marcadores moleculares del patógeno como método auxiliar en el proceso de localización de los contactos, pero ello casi siempre ha servido únicamente para caracterizar correlaciones más bien laxas entre grandes comunidades de tipos parecidos. En los últimos tiempos, sin embargo, el advenimiento de la secuenciación masiva de alto rendimiento de genomas completos ha revolucionado la epidemiología forense aplicada a otras enfermedades, y ahora puede ocurrir otro tanto con la tuberculosis bovina. Los autores, tras repasar el contexto histórico del uso de la secuenciación de genomas completos, exponen los resultados que hasta la fecha se han podido obtener con las técnicas moleculares anteriores. Asimismo, describen brevemente los principales métodos para interpretar los datos de secuenciación de genomas completos y examinan tanto la función de las técnicas analíticas avanzadas que explotan las propiedades evolutivas y epidemiológicas del sistema como los problemas que surgen para cuantificar la intervención de reservorios ocultos de enfermedad. Por último, exponen las especiales dificultades que plantea el desarrollo de esta tecnología para efectuar diagnósticos sistemáticos y las posibilidades que ofrece para una utilización generalizada.

Estimating epidemiological parameters for bovine tuberculosis in British cattle using a Bayesian partial-likelihood approach.

Fitting models with Bayesian likelihood-based parameter inference is becoming increasingly important in infectious disease epidemiology. Detailed datasets present the opportunity to identify subsets of these data that capture important characteristics of the underlying epidemiology. One such dataset describes the epidemic of bovine tuberculosis (bTB) in British cattle, which is also an important exemplar of a disease with a wildlife reservoir (the Eurasian badger). Here, we evaluate a set of nested dynamic models of bTB transmission, including individual- and herd-level transmission heterogeneity and assuming minimal prior knowledge of the transmission and diagnostic test parameters. We performed a likelihood-based bootstrapping operation on the model to infer parameters based only on the recorded numbers of cattle testing positive for bTB at the start of each herd outbreak considering high- and low-risk areas separately. Models without herd heterogeneity are preferred in both areas though there is some evidence for super-spreading cattle. Similar to previous studies, we found low test sensitivities and high within-herd basic reproduction numbers (R0), suggesting that there may be many unobserved infections in cattle, even though the current testing regime is sufficient to control within-herd epidemics in most cases. Compared with other, more data-heavy approaches, the summary data used in our approach are easily collected, making our approach attractive for other systems.

A metapopulation model for highly pathogenic avian influenza: implications for compartmentalization as a control measure.

Although the compartmentalization of poultry industry components has substantial economic implications, and is therefore a concept with huge significance to poultry industries worldwide, the current requirements for compartment status are generic to all OIE member countries. We examined the consequences for potential outbreaks of highly pathogenic avian influenza in the British poultry industry using a metapopulation modelling framework. This framework was used to assess the effectiveness of compartmentalization relative to zoning control, utilizing empirical data to inform the structure of potential epidemiological contacts within the British poultry industry via network links and spatial proximity. Conditions were identified where, despite the efficient isolation of poultry compartments through the removal of network-mediated links, spatially mediated airborne spread enabled spillover of infection with nearby premises making compartmentalization a more 'risky' option than zoning control. However, when zoning control did not effectively inhibit long-distance network links, compartmentalization became a relatively more effective control measure than zoning. With better knowledge of likely distance ranges for airborne spread, our approach could help define an appropriate minimum inter-farm distance to provide more specific guidelines for compartmentalization in Great Britain.

The utility of whole-genome sequencing to identify likely transmission pairs for pathogens with slow and variable evolution.

Pathogen whole-genome sequencing (WGS) has been used to track the transmission of infectious diseases in extraordinary detail, especially for pathogens that undergo fast and steady evolution, as is the case with many RNA viruses. However, for other pathogens evolution is less predictable, making interpretation of these data to inform our understanding of their epidemiology more challenging and the value of densely collected pathogen genome data uncertain. Here, we assess the utility of WGS for one such pathogen, in the "who-infected-whom" identification problem. We study samples from hosts (130 cattle, 111 badgers) with confirmed infection of M. bovis (causing bovine Tuberculosis), which has an estimated clock rate as slow as ∼0.1-1 variations per year. For each potential pathway between hosts, we calculate the relative likelihood that such a transmission event occurred. This is informed by an epidemiological model of transmission, and host life history data. By including WGS data, we shrink the number of plausible pathways significantly, relative to those deemed likely on the basis of life history data alone. Despite our uncertainty relating to the evolution of M. bovis, the WGS data are therefore a valuable adjunct to epidemiological investigations, especially for wildlife species whose life history data are sparse.

Developing a framework for risk-based surveillance of tuberculosis in cattle: a case study of its application in Scotland.

Due to its substantially lower prevalence of bovine tuberculosis (bTB) relative to other areas of Great Britain, Scotland was designated as an officially (bovine) TB-free region in 2009. This paper investigates resultant possibilities for reducing surveillance by developing risk-based alternatives to current 4-year testing of eligible herds. A model of freedom of infection was used to develop strategies that specifically tested herds that are at risk of infection but would probably not be identified by slaughterhouse meat inspection. The performance of current testing is mimicked by testing all herds that slaughter fewer than 25% of their total stock per year and regularly import animals from high-incidence areas of England and Wales or from Ireland. This system offers a cost reduction by requiring 25% fewer herd and animal tests and 25% fewer false positives.

Use of a preclinical test in the control of classical scrapie.

Scrapie control in Great Britain (GB) was originally based on the National Scrapie Plan's Ram Genotyping scheme aimed at reducing the susceptibility of the national flock. The current official strategy to control scrapie in the national flock involves culling susceptible genotypes in individual, known affected flocks (compulsory scrapie flock scheme or CSFS). However, the recent development of preclinical test candidates means that a strategy based on disease detection may now be feasible. Here, a deterministic within-flock model was used to demonstrate that only large flocks with many home-bred ewes are likely to be a significant risk for flock-to-flock transmission of scrapie. For most other flocks, it was found that the CSFS could be replaced by a strategy using a currently available live test without excessive risk to other farmers, even if the proportion of susceptible genotypes in the flock is unusually large. Even for flocks that represent a high risk of harbouring a high prevalence of infection, there would be limited probability of onward transmission if scrapie is detected soon after disease introduction (typically less than 5 years). However, if detection of disease is delayed, the existing CSFS strategy may be the most appropriate control measure in these cases.

Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies.

Livestock movements are an important mechanism of infectious disease transmission. Where these are well recorded, network analysis tools have been used to successfully identify system properties, highlight vulnerabilities to transmission, and inform targeted surveillance and control. Here we highlight the main uses of network properties in understanding livestock disease epidemiology and discuss statistical approaches to infer network characteristics from biased or fragmented datasets. We use a 'hurdle model' approach that predicts (i) the probability of movement and (ii) the number of livestock moved to generate synthetic 'complete' networks of movements between administrative wards, exploiting routinely collected government movement permit data from northern Tanzania. We demonstrate that this model captures a significant amount of the observed variation. Combining the cattle movement network with a spatial between-ward contact layer, we create a multiplex, over which we simulated the spread of 'fast' ( R0 = 3) and 'slow' ( R0 = 1.5) pathogens, and assess the effects of random versus targeted disease control interventions (vaccination and movement ban). The targeted interventions substantially outperform those randomly implemented for both fast and slow pathogens. Our findings provide motivation to encourage routine collection and centralization of movement data to construct representative networks. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Identifying genotype specific elevated-risk areas and associated herd risk factors for bovine tuberculosis spread in British cattle.

Bovine tuberculosis (bTB) is a chronic zoonosis with major health and economic impact on the cattle industry. Despite extensive control measures in cattle and culling trials in wildlife, the reasons behind the expansion of areas with high incidence of bTB breakdowns in Great Britain remain unexplained. By balancing the importance of cattle movements and local transmission on the observed pattern of cattle outbreaks, we identify areas at elevated risk of infection from specific Mycobacterium bovis genotypes. We show that elevated-risk areas (ERAs) were historically more extensive than previously understood, and that cattle movements alone are insufficient for ERA spread, suggesting the involvement of other factors. For all genotypes, we find that, while the absolute risk of infection is higher in ERAs compared to areas with intermittent risk, the statistically significant risk factors are remarkably similar in both, suggesting that these risk factors can be used to identify incipient ERAs before this is indicated by elevated incidence alone. Our findings identify research priorities for understanding bTB dynamics, improving surveillance and guiding management to prevent further ERA expansion.

Mycobacterium bovis shedding patterns from experimentally infected calves and the effect of concurrent infection with bovine viral diarrhoea virus.

Concurrent infection of cattle with bovine viral diarrhoea virus (BVDV) and Mycobacterium bovis is considered to be a possible risk factor for onward transmission of bovine tuberculosis (BTB) in infected cattle and is known to compromise diagnostic tests. A comparison is made here of M. bovis shedding (i.e. release) characteristics from 12 calves, six experimentally co-infected with BVDV and six infected with M. bovis alone, using simple models of bacterial replication. These statistical and mathematical models account for the intermittent or episodic nature of shedding, the dynamics of within-host bacterial proliferation and the sampling distribution from a given shedding episode. We show that while there are distinct differences among the shedding patterns of calves given the same infecting dose, there is no statistically significant difference between the two groups of calves. Such differences as there are, can be explained solely in terms of the shedding frequency, but with all calves potentially excreting the same amount of bacteria in a given shedding episode post-infection. The model can be thought of as a process of the bacteria becoming established in a number of discrete foci of colonization, rather than as a more generalized infection of the respiratory tract. In this case, the variability in the shedding patterns of the infected calves can be explained solely by differences in the number of foci established and shedding being from individual foci over time. Should maximum exposure on a particular occasion be a critical consideration for cattle-to-cattle transmission of BTB, cattle that shed only intermittently may still make an important contribution to the spread and persistence of the disease.

Data quality of the Cattle Tracing System in Great Britain.

The Cattle Tracing System (cts) of Great Britain was examined to investigate the quality of its data in terms of known errors and omissions, and their distribution. The proportions of erroneous or missing data have decreased steadily over time, with a marked improvement in the quality of the data since 2001, when recording became mandatory. There is little variation between regions in the quality of the data, but there are potentially important variations between the types of agricultural premises that cattle move to and from, and in other factors correlated with the type of premises, such as the age of the animals and the number of animal movements associated with the premises.

Modelling the initial spread of foot-and-mouth disease through animal movements.

Livestock movements in Great Britain (GB) are well recorded and are a unique record of the network of connections among livestock-holding locations. These connections can be critical for disease spread, as in the 2001 epidemic of foot-and-mouth disease (FMD) in the UK. Here, the movement data are used to construct an individual-farm-based model of the initial spread of FMD in GB and determine the susceptibility of the GB livestock industry to future outbreaks under the current legislative requirements. Transmission through movements is modelled, with additional local spread unrelated to the known movements. Simulations show that movements can result in a large nationwide epidemic, but only if cattle are heavily involved, or the epidemic occurs in late summer or early autumn. Inclusion of random local spread can considerably increase epidemic size, but has only a small impact on the spatial extent of the disease. There is a geographical bias in the epidemic size reached, with larger epidemics originating in Scotland and the north of England than elsewhere.

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.

A model of bovine tuberculosis control in domesticated cattle herds.

A typical strategy for disease control in domesticated animals involves regular field tests and quarantine of infected herds. This prevents disease spread beyond the herd, while slaughter of diseased animals removes the infection from within the herd. A model of bovine tuberculosis (Tb) control in cattle is examined, which includes 'test and slaughter' combined with herd isolation and vaccination. Herd status is represented by an integral equation expressing the duration of herd isolation. The current Tb situation in New Zealand is used as an example, and vaccination strategy discussed. Extrapolation of existing management strategies indicate that a vaccine of efficacy greater than 96% would be required, reaching 95% of target Tb levels within six years. These results suggest that a complementary strategy of vaccination and vector control may be more promising than vaccination alone.

The dynamics of an infectious disease in a population with birth pulses.

In most models of population dynamics increases in population due to births are assumed to be time-independent, but many species of wild animal give birth only during a single period of the year. We propose a model for the dynamics of a fatal infectious disease in a wild animal population for which births occur in a single pulse once per time period. Periodic solutions are found and criteria for their stability determined. A simple example applied to tuberculosis in the possum is used to illustrate the effect of the birth pulse on critical population parameters.

Modelling the national scrapie eradication programme in the UK.

In accordance with a policy to eliminate all transmissible spongiform encephalopathies from the food chain, a national untargeted ram breeding programme to eliminate scrapie in the UK is in the final stages of planning. Here we formulate a model of flock-to-flock scrapie transmission, in order to consider the effect of a targeted breeding programme which is in the early stages of consideration. We estimate the size of the susceptible flock population, and discuss implications for potential control programmes. Targeting all rams and ewes in highly susceptible flocks rather than rams in all flocks will eradicate scrapie more quickly, and so is likely to be beneficial as long as suitable penalties or incentives are available to facilitate their identification. A more restricted programme aimed only at highly affected flocks would be much easier to implement and crucially will eradicate scrapie just as quickly. This will leave behind a residue population of susceptible sheep, which could then be gradually removed by a more general breeding programme.