Feedback between coevolution and epidemiology can help or hinder the maintenance of genetic variation in host-parasite models.

Antagonistic coevolution has long been suggested to help maintain host genetic variation. Although ecological and epidemiological feedbacks are known to have important consequences on coevolutionary allele-frequency dynamics, their effects on the maintenance of genetic variation remains poorly understood. Here, we extend previous work on the maintenance of genetic variation in a classic matching alleles coevolutionary model by exploring the effects of ecological and epidemiological feedbacks, where both allele frequencies and population sizes are allowed to vary over time.

Coevolution fails to maintain genetic variation in a host-parasite model with constant finite population size.

Coevolutionary negative frequency-dependent selection has been hypothesized to maintain genetic variation in host and parasites. Despite the extensive literature pertaining to host-parasite coevolution, the temporal dynamics of genetic variation have not been examined in a matching-alleles model (MAM) with a finite population size relative to the expectation under neutral genetic drift alone. The dynamics of the MA coevolution in an infinite population, in fact, suggests that genetic variation in these coevolving populations behaves neutrally.

Reducing respiratory syncytial virus (RSV) hospitalization in a lower-income country by vaccinating mothers-to-be and their households.

Respiratory syncytial virus is the leading cause of lower respiratory tract infection among infants. RSV is a priority for vaccine development. In this study, we investigate the potential effectiveness of a two-vaccine strategy aimed at mothers-to-be, thereby boosting maternally acquired antibodies of infants, and their household cohabitants, further cocooning infants against infection.

Disease transmission promotes evolution of host spatial patterns.

Ecological dynamics can produce a variety of striking patterns. On ecological time scales, pattern formation has been hypothesized to be due to the interaction between a species and its local environment. On longer time scales, evolutionary factors must be taken into account.

Rapid simulation of spatial epidemics: a spectral method.

Spatial structure and hence the spatial position of host populations plays a vital role in the spread of infection. In the majority of situations, it is only possible to predict the spatial spread of infection using simulation models, which can be computationally demanding especially for large population sizes. Here we develop an approximation method that vastly reduces this computational burden.

Mutation detection in formalin-fixed prostate cancer biopsies taken at the time of diagnosis using next-generation DNA sequencing.

Aims: Assessing whether next-generation DNA sequencing (NGS) can be used to screen prostate cancer for multiple gene alterations in men routinely diagnosed with this disease and/or who are entered into clinical trials. Previous studies are limited and have reported only low success rates.

Methods: We marked areas of cancer on H&E-stained sections from formalin-fixed needle biopsies, and used these as templates to dissect cancer-rich tissue from adjacent unstained sections.

Testing the hypothesis of preferential attachment in social network formation.

The hypothesis of preferential attachment (PA) - whereby better connected individuals make more connections - is hotly debated, particularly in the context of epidemiological networks. The simplest models of PA, for example, are incompatible with the eradication of any disease through population-level control measures such as random vaccination. Typically, evidence has been sought for the presence or absence of preferential attachment via asymptotic power-law behaviour.

Strategies for controlling non-transmissible infection outbreaks using a large human movement data set.

Prediction and control of the spread of infectious disease in human populations benefits greatly from our growing capacity to quantify human movement behavior. Here we develop a mathematical model for non-transmissible infections contracted from a localized environmental source, informed by a detailed description of movement patterns of the population of Great Britain. The model is applied to outbreaks of Legionnaires' disease, a potentially life-threatening form of pneumonia caused by the bacteria Legionella pneumophilia.

Digital templating facilitates accurate leg length correction in total hip arthroplasty.

Digital templating of pre-operative radiographs is increasingly utilised by surgeons before total hip arthroplasty (THA) as part of an adequate preoperative preparation to minimise complications. Templating can accurately predict the required implant sizes but its use in facilitating correction of leg length discrepancy (LLD) has been underreported in the literature. We performed a retrospective analysis of a cohort of consecutive patients undergoing primary THA.

An inter-laboratory validation of a real time PCR assay to measure host excretion of bacterial pathogens, particularly of Mycobacterium bovis.

Advances in the diagnosis of Mycobacterium bovis infection in wildlife hosts may benefit the development of sustainable approaches to the management of bovine tuberculosis in cattle. In the present study, three laboratories from two different countries participated in a validation trial to evaluate the reliability and reproducibility of a real time PCR assay in the detection and quantification of M. bovis from environmental samples.

INFERENCE FOR INDIVIDUAL-LEVEL MODELS OF INFECTIOUS DISEASES IN LARGE POPULATIONS.

Individual Level Models (ILMs), a new class of models, are being applied to infectious epidemic data to aid in the understanding of the spatio-temporal dynamics of infectious diseases. These models are highly flexible and intuitive, and can be parameterised under a Bayesian framework via Markov chain Monte Carlo (MCMC) methods. Unfortunately, this parameterisation can be difficult to implement due to intense computational requirements when calculating the full posterior for large, or even moderately large, susceptible populations, or when missing data are present.

Resolving the impact of waiting time distributions on the persistence of measles.

Measles epidemics in human populations exhibit what is perhaps the best empirically characterized, and certainly the most studied, stochastic persistence threshold in population biology. A critical community size (CCS) of around 250,000-500,000 separates populations where measles is predominantly persistent from smaller communities where there are frequent extinctions of measles between major epidemics. The fundamental mechanisms contributing to this pattern of persistence, which are long-lasting immunity to re-infection, recruitment of susceptibles, seasonality in transmission, age dependence of transmission and the spatial coupling between communities, have all been quantified and, to a greater or lesser level of success, captured by theoretical models.

The interplay between determinism and stochasticity in childhood diseases.

An important issue in the history of ecology has been the study of the relative importance of deterministic forces and processes noise in shaping the dynamics of ecological populations. We address this question by exploring the temporal dynamics of two childhood infections, measles and whooping cough, in England and Wales. We demonstrate that epidemics of whooping cough are strongly influenced by stochasticity; fully deterministic approaches cannot achieve even a qualitative fit to the observed data.

Effect of data quality on estimates of farm infectiousness trends in the UK 2001 foot-and-mouth disease epidemic.

Most of the mathematical models that were developed to study the UK 2001 foot-and-mouth disease epidemic assumed that the infectiousness of infected premises was constant over their infectious periods. However, there is some controversy over whether this assumption is appropriate. Uncertainty about which farm infected which in 2001 means that the only method to determine if there were trends in farm infectiousness is the fitting of mechanistic mathematical models to the epidemic data.

Silent spread of H5N1 in vaccinated poultry.

International debate on the merits of vaccinating poultry against the H5N1 influenza A virus has raised concerns about the possibility of an increased risk of between-flock transmission before outbreaks are detected. Here we show that this 'silent spread' can occur because of incomplete protection at the flock level, even if a vaccine is effective in individual birds. The use of unvaccinated sentinels can mitigate, although not completely eliminate, the problem.

Topographic determinants of foot and mouth disease transmission in the UK 2001 epidemic.

Background: A key challenge for modelling infectious disease dynamics is to understand the spatial spread of infection in real landscapes. This ideally requires a parallel record of spatial epidemic spread and a detailed map of susceptible host density along with relevant transport links and geographical features.

Results: Here we analyse the most detailed such data to date arising from the UK 2001 foot and mouth epidemic.

Modelling the many-wrongs principle: the navigational advantages of aggregation in nomadic foragers.

We develop a simple individual-based model to gain an understanding of the drivers of aggregation behaviour in nomadic foragers. The model incorporates two key elements influencing nomadic foragers in variable environments: uncertainty regarding the location of food sources and variability in the spatio-temporal distribution of ephemeral food sources. A genetic algorithm is used to evolve parameters describing an individual's movement and aggregation strategy.