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Author(s): D. T. Haydon (corresponding author) [1]; D. A. Randall [2, 3]; L. Matthews [4]; D. L. Knobel [3, 4]; L. A. Tallents [2, 3]; M. B. Gravenor [5]; S. [...]

The study of biological systems commonly depends on inferring the state of a 'hidden' variable, such as an underlying genotype, from that of an 'observed' variable, such as an expressed phenotype. However, this cannot be achieved using traditional quantitative methods when more than one genetic mechanism exists for a single observable phenotype. Using a novel latent class Bayesian model, it is possible to infer the prevalence of different genetic elements in a population given a sample of phenotypes. As an exemplar, data comprising phenotypic resistance to six antimicrobials obtained from passive surveillance of Salmonella Typhimurium DT104 are analysed to infer the prevalence of individual resistance genes, as well as the prevalence of a genomic island known as SGI1 and its variants. Three competing models are fitted to the data and distinguished between using posterior predictive p-values to assess their ability to predict the observed number of unique phenotypes. The results suggest that several SGI1 variants circulate in a few fixed forms through the population from which our data were derived. The methods presented could be applied to other types of phenotypic data, and represent a useful and generic mechanism of inferring the genetic population structure of organisms. [ABSTRACT FROM AUTHOR]

The article describes the molecular characterization of South African Territories (SAT)-2 foot-and-mouth disease (FMD) virus isolates obtained from cattle during a four-month period in 2001 in Limpopo Province, South Africa. FMD is an acute, highly contagious viral infection of domestic and wild cloven-hoofed animals. The FMD virus is a single-stranded ribonucleic acid (RNA) virus that has a high rate of nucleotide mutation and amino acid substitution. According to authors, the SAT 1-3 serotypes of FMD virus are found by large numbers in African buffaloes, which provided a potential source of infection for domestic livestock and wild animals in southern Africa.

There was a major epidemic of the foot-and-mouth-disease virus among cattle herds in the UK in 1967–68 which showed a very rapid early spread, a much slower later spread, and eventually infected 12% of herds in the core epidemic area. A simple discrete-time version of a susceptible-latent-infectious-removed epidemiological model is used to generate a set of estimates of the transmission rate. This parameter has high values over the first few days, then the values are lower and they subsequently decline. The early high values are consistent with the view that unusual meteorological conditions produced exceptionally good conditions for wind-borne spread of the virus over the first few days. The corresponding basic reproduction number, R0, is estimated as 38.4. Subsequent low values of the transmission rate correspond to a value of R0 of 2.0; this is within the range of estimates made from the observed ratio of secondary to primary outbreaks for 25 other epidemics. Prophylactic control measures, such as vaccination, would have to be extremely effective to prevent epidemics with the higher R0 value. [ABSTRACT FROM PUBLISHER]

Emerging zoonoses with pandemic potential are a stated priority for the global health security agenda, but endemic zoonoses also have a major societal impact in low-resource settings. Although many endemic zoonoses can be treated, timely diagnosis and appropriate clinical management of human cases is often challenging. Preventive 'One Health' interventions, e.g. interventions in animal populations that generate human health benefits, may provide a useful approach to overcoming some of these challenges. Effective strategies, such as animal vaccination, already exist for the prevention, control and elimination of many endemic zoonoses, including rabies, and several livestock zoonoses (e.g. brucellosis, leptospirosis, Q fever) that are important causes of human febrile illness and livestock productivity losses in low- and middle-income countries. We make the case that, for these diseases, One Health interventions have the potential to be more effective and generate more equitable benefits for human health and livelihoods, particularly in rural areas, than approaches that rely exclusively on treatment of human cases. We hypothesize that applying One Health interventions to tackle these health challenges will help to build trust, community engagement and cross-sectoral collaboration, which will in turn strengthen the capacity of fragile health systems to respond to the threat of emerging zoonoses and other future health challenges. One Health interventions thus have the potential to align the ongoing needs of disadvantaged communities with the concerns of the broader global community, providing a pragmatic and equitable approach to meeting the global goals for sustainable development and supporting the global health security agenda.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'., (© 2017 The Authors.)

The study of biological systems commonly depends on inferring the state of a 'hidden' variable, such as an underlying genotype, from that of an 'observed' variable, such as an expressed phenotype. However, this cannot be achieved using traditional quantitative methods when more than one genetic mechanism exists for a single observable phenotype. Using a novel latent class Bayesian model, it is possible to infer the prevalence of different genetic elements in a population given a sample of phenotypes. As an exemplar, data comprising phenotypic resistance to six antimicrobials obtained from passive surveillance of Salmonella Typhimurium DT104 are analysed to infer the prevalence of individual resistance genes, as well as the prevalence of a genomic island known as SGI1 and its variants. Three competing models are fitted to the data and distinguished between using posterior predictive p-values to assess their ability to predict the observed number of unique phenotypes. The results suggest that several SGI1 variants circulate in a few fixed forms through the population from which our data were derived. The methods presented could be applied to other types of phenotypic data, and represent a useful and generic mechanism of inferring the genetic population structure of organisms.

Understanding the transmission dynamics of generalist pathogens that infect multiple host species is essential for their effective control. Only by identifying those host populations that are critical to the permanent maintenance of the pathogen, as opposed to populations in which outbreaks are the result of 'spillover' infections, can control measures be appropriately directed. Rabies virus is capable of infecting a wide range of host species, but in many ecosystems, particular variants circulate among only a limited range of potential host populations. The Serengeti ecosystem (in northwestern Tanzania) supports a complex community of wild carnivores that are threatened by generalist pathogens that also circulate in domestic dog populations surrounding the park boundaries. While the combined assemblage of host species appears capable of permanently maintaining rabies in the ecosystem, little is known about the patterns of circulation within and between these host populations. Here we use molecular phylogenetics to test whether distinct virus-host associations occur in this species-rich carnivore community. Our analysis identifies a single major variant belonging to the group of southern Africa canid-associated viruses (Africa 1b) to be circulating within this ecosystem, and no evidence for species-specific grouping. A statistical parsimony analysis of nucleoprotein and glycoprotein gene sequence data is consistent with both within- and between-species transmission events. While likely differential sampling effort between host species precludes a definitive inference, the results are most consistent with dogs comprising the reservoir of rabies and emphasize the importance of applying control efforts in dog populations.

African buffalo (Syncerus caffer) play an important role in the maintenance of the SAT types of foot-and-mouth disease (FMD) in southern Africa. These long-term carriers mostly become sub-clinically infected, maintaining the disease and posing a threat to other susceptible wildlife and domestic species. During an unrelated bovine tuberculosis experiment using captive buffalo in the Kruger National Park (KNP), an outbreak of SAT-1 occurred and was further investigated. The clinical signs were recorded and all animals demonstrated significant weight loss and lymphopenia that lasted 100 days. In addition, the mean cell volume and mean cell haemoglobin values were significantly higher than before the outbreak started. Virus was isolated from several buffalo over a period of 167 days post infection and the molecular clock estimated to be 3 x 10(-5) nucleotide substitutions per site per day. Seven amino acid changes occurred of which four occurred in hypervariable regions previously described for SAT-1. The genetic relationship of the outbreak virus was compared to buffalo viruses previously obtained from the KNP but the phylogeny was largely unresolved, therefore the relationship of this outbreak strain to others isolated from the KNP remains unclear.

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.

Explaining synchronization of cyclical or fluctuating populations over geographical regions presents ecologists with novel analytical challenges. We have developed a method to measure synchrony within spatial-temporal datasets of population densities applicable to both periodic and irregularly fluctuating populations. The dynamics of each constituent population is represented by a discrete Markov model. The state of a population trajectory at each time-point is classified as one of 'increase', 'decrease', 'peak' or 'trough'. The set of populations at any time-point is characterized by the frequency distribution of these different states, and the time-evolution of this frequency distribution used to test the hypothesis that the dynamics of each population proceeds independently of the others. The analysis identifies years in which population coupling results in synchronous states and onto which states the system converges, and identifies those years in which synchrony remains high but is accounted for by coupling observed in previous years. It also enables identification of which pairs of sites show the highest levels of coupling. Applying these methods to populations of the grey-sided vole on Hokkaido reveals them to be fluctuating in greater synchrony than would be expected from independent dynamics, and that this level of synchrony is maintained through intermittent coupling acting in ca. 1 year in four or five. High synchrony occurs between sites with similar vegetation and of similar altitude indicating that coupling may be mediated through shared environmental stimuli. When coupling is indicated, convergence is equally likely to occur on a peak state as a trough, indicating that synchronization may be brought about by the response of populations to a combination of different stimuli rather than by the action of any single process.

The case-reproduction ratio for the spread of an infectious disease is a critically important concept for understanding dynamics of epidemics and for evaluating impact of control measures on spread of infection. Reliable estimation of this ratio is a problem central to epidemiology and is most often accomplished by fitting dynamic models to data and estimating combinations of parameters that equate to the case-reproduction ratio. Here, we develop a novel parameter-free method that permits direct estimation of the history of transmission events recoverable from detailed observation of a particular epidemic. From these reconstructed 'epidemic trees', case-reproduction ratios can be estimated directly. We develop a bootstrap algorithm that generates percentile intervals for these estimates that shows the procedure to be both precise and robust to possible uncertainties in the historical reconstruction. Identifying and 'pruning' branches from these trees whose occurrence might have been prevented by implementation of more stringent control measures permits estimation of the possible efficacy of these alternative measures. Examination of the cladistic structure of these trees as a function of the distance of each case from its infection source reveals useful insights about the relationship between long-distance transmission events and epidemic size. We demonstrate the utility of these methods by applying them to data from the 2001 foot-and-mouth disease outbreak in the UK.

Foot-and-mouth is one of the world's most economically important livestock diseases. We developed an individual farm-based stochastic model of the current UK epidemic. The fine grain of the epidemiological data reveals the infection dynamics at an unusually high spatiotemporal resolution. We show that the spatial distribution, size, and species composition of farms all influence the observed pattern and regional variability of outbreaks. The other key dynamical component is long-tailed stochastic dispersal of infection, combining frequent local movements with occasional long jumps. We assess the history and possible duration of the epidemic, the performance of control strategies, and general implications for disease dynamics in space and time.

The majority of pathogens, including many of medical and veterinary importance, can infect more than one species of host. Population biology has yet to explain why perceived evolutionary advantages of pathogen specialization are, in practice, outweighed by those of generalization. Factors that predispose pathogens to generalism include high levels of genetic diversity and abundant opportunities for cross-species transmission, and the taxonomic distributions of generalists and specialists appear to reflect these factors. Generalism also has consequences for the evolution of virulence and for pathogen epidemiology, making both much less predictable. The evolutionary advantages and disadvantages of generalism are so finely balanced that even closely related pathogens can have very different host range sizes.

Sodalis glossinidius is a maternally transmitted secondary endosymbiont residing intracellularly in tissues of the tsetse flies, Glossina spp. In this study, we have used Tn5 mutagenesis and a negative selection procedure to derive a S. glossinidius mutant that is incapable of invading insect cells in vitro and is aposymbiotic when microinjected into tsetse. This mutant strain harbors Tn5 integrated into a chromosomal gene sharing high sequence identity with a type III secretion system invasion gene (invC) previously identified in Salmonella enterica. With the use of degenerate PCR, we have amplified a further six Sodalis inv/spa genes sharing high sequence identity with type III secretion system genes encoded by Salmonella pathogenicity island 1. Phylogenetic reconstructions based on the inv/spa genes of Sodalis and other members of the family Enterobacteriaceae have consistently identified a well-supported clade containing Sodalis and the enteric pathogens Shigella and Salmonella. These results suggest that Sodalis may have evolved from an ancestor with a parasitic intracellular lifestyle, possibly a latter-day entomopathogen. These observations lend credence to a hypothesis suggesting that vertically transmitted mutualistic endosymbionts evolve from horizontally transmitted parasites through a parasitism-mutualism continuum.

The apparent persistence of scrapie in British sheep for more than 250 years is difficult to explain. Susceptibility to scrapie is associated with particular alleles at a single locus, the PrP gene. As the only known effect of these alleles is to confer susceptibility to a fatal disease, natural selection is expected to reduce their frequency, as has been observed in practice during scrapie outbreaks in single sheep flocks. Susceptibility alleles, and hence scrapie itself, are therefore expected to become rare, yet the disease remains widespread. We suggest that the paradox of scrapie's persistence can be explained by the exceptionally long time-scales inherent in the epidemiology of the disease. It is proposed that scrapie should be regarded as epidemic in British sheep but, unlike more familiar epidemics, which have time-scales of months or years, the scrapie epidemic has a time-scale of centuries. This interpretation implies that scrapie should eventually disappear from the sheep population.

The nature of selection on capsid genes of foot-and-mouth disease virus (FMDV) was characterized by examining the ratio of nonsynonymous to synonymous substitutions in 11 data sets of sequences obtained from six different serotypes of FMDV. Using a method of analysis that assigns each codon position to one of a number of estimated values of nonsynonymous to synonymous ratio, significant evidence of positive selection was identified in 5 data sets, operating at 1-7% of codon positions. Evidence of positive selection was identified in complete capsid sequences of serotypes A and C and in VP1 sequences of serotypes SAT 1 and 2. Sequences of serotype SAT-2 recovered from a persistently infected African buffalo also revealed evidence for positive selection. Locations of codons under positive selection coincide closely with those of antigenic sites previously identified with the use of monoclonal antibody escape mutants. The vast majority of codons are under mild to strong purifying selection. However, these results suggest that arising antigenic variants benefit from a selective advantage in their interaction with the immune system, either during the course of an infection or in transmission to individuals with previous exposure to antigen. Analysis of amino acid usage at sites under positive selection indicates that this selective advantage can be conferred by amino acid substitutions that share physicochemically similar properties.

We use a dynamic random field to model a spatial collection of coupled oscillators with discrete time stochastic dynamics. At each time step the phase of each cyclic local population is subject to random noise, incremented by a common dynamic, and pulled by a coupling force in the direction of some collective mean phase. We define asynchrony and derive expressions for its measurement in this model. We describe robust methods for phase estimation of cyclic population time series, for estimating strength of coupling between local populations, and for measuring variance of locally acting noise from field data. Proposed methods allow intermittently acting phase synchronizing events operating over large spatial scales to be distinguished from more continuous and possibly locally acting coupling, both of which could result in elevated levels of phase synchronization. We demonstrate the utility of this approach by applying it to classical spatial time series data of Canadian lynx. Analysis confirms findings of previous studies and reveals evidence to suggest that interpopulation coupling was weaker over the 20th century than for the 1800s. Analysis supports the notion that synchrony in these populations is maintained by a continuous and locally acting coupling between adjacent regions with large phase adjustments occurring only infrequently. When this coupling is absent, asynchrony develops between populations.

The number of red grouse (Lagopus lagopus scoticus) shot in the UK has declined by 50% during the 20th century This decline has coincided with reductions in the area of suitable habitat and recoveries in the populations of some avian predators. Here we use long-term records of shooting bags and a large-scale manipulation of raptor density to disentangle the effects of habitat loss and raptor predation on grouse populations. The numbers of grouse harvested on the Eskdale half of Langholm Moor in southern Scotland declined significantly during 1913-1990 and grouse bags from the whole moor from 1950 to 1990 exhibited an almost identical but non-significant trend. Hen harriers (Circus cyaneus) and peregrine falcons (Falco peregrinus) were absent or bred at low densities on this moor throughout this period but heather-dominant vegetation declined by 48% between 1948 and 1988. Harrier and peregrine breeding numbers on Langholm Moor increased to high levels following protection in 1990 whilst grouse density and grouse bags declined year after year until shooting was abandoned in 1998. The prediction of a peak in grouse bags on Langholm Moor in 1996 based on the patterns of bags during 1950-1990 was supported by the observed peaks in 1997 on two nearby moors with few raptors which formerly cycled in synchrony with Langholm Moor. This study demonstrates that, whilst long-term declines in grouse bags were most probably due to habitat loss, high levels of raptor predation subsequently limited the grouse population and suppressed a cycle. This study thus offers support to theoretical models which predict that generalist predators may suppress cycles in prey populations.

Highly exposed and protruding amino acid sites on the surface of viral capsids are subject to fewer residue interactions and packing constraints than those buried within protein interiors. Consequently they often experience higher rates of non-synonymous substitution and exhibit greater genetic variability than buried interior sites. However such protrusive surface structures often induce host immune responses and are likely to constitute B cell epitopes. Genetic variation at these surface sites is therefore likely to correspond to antigenic variation. This may be of adaptive value to the virus for two quite different reasons. The first is that antigenic variation arising over the course of a viraemia may result in greater net viral replication, and increased opportunities for viral transmission. The second is that antigenic variation generated rapidly over a single infection or incrementally over several sequential infections may give rise to variants that are sufficiently immunologically distinct that they can reinfect host individuals with previous infection experience of related virus. This would lead to an extension of the susceptible host pool with consequent increase in transmission opportunities. The surface architecture of viral capsid proteins is therefore conceivably subject to two opposing selection pressures: one to minimize the surface area accessible to interaction with elements of the immune system, the other to increase the potential access to antigenic variation by adoption of exposed and unconstrained protein conformations. Therefore, there exists a possible trade-off between the fitness benefits deriving from potential ability to generate antigenic variation, and the increased immunogenicity with which such potential may be associated. We propose that the existence of this trade-off would lead to a continuum of different strategies by which a virus might combat an immune response. We explore this strategy space with simple mathematical models, and show that peak loads of infectious virus particles are proportional to levels of antigenic diversity, and inversely proportional to immunogenicity, thereby creating the potential for a trade-off by which fitness might be maintained with a continuum of strategies. This may remain possible even if the antigenic variants are not transmissible between hosts, so long as immune resources are sufficiently dispersed between antigenic variants. The diversity of possible strategies is discussed with reference to the Picornavirus family.

The optimal design of a veterinary vaccination programme depends on both the characteristics of the vaccine and the epidemiology of the pathogen or parasite. Relevant vaccine characteristics are the proportion of those vaccinated that are initially protected, the duration of protection and the coverage achieved by the vaccination programme. The most important epidemiological parameter is the basic reproduction number, R0. Mathematical theory can integrate this information to address such questions as: whether it is possible to eliminate an infection; what proportion of hosts must be vaccinated to achieve this: what age should hosts first be vaccinated; and at what interval should hosts be revaccinated? Examples of rabies in foxes and foot-and-mouth disease in cattle suggest that theory can be used to guide the design of vaccination programmes.

The deduction of biogeographic process from the study of its history is complicated by the fact that history is a singular thing. This singularity allows no estimation of the degree of determinism surrounding the realization of biogeographic processes, and consequently we know almost nothing about the generality of such deductions. Here we discuss a new approach, called 'experimental biogeography', that exploits computers to model faunal build-up repeatedly against a fixed vicariant background over ecological and evolutionary time scales. This new approach enables a biogeographer to be omniscient - to know both vicariant history and actual phylogeny. Moreover, history can be replayed repeatedly to accumulate a sample of multiple phylogenies and to estimate probability density functions for biogeographic variables. Roles of stochastic, historical and ecological processes in adaptive radiations can also be assessed. Experimental biogeography allows examination of the reliability of various methods of recovering historical patterns., (Copyright © 1994. Published by Elsevier Ltd.)