oalib

Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99

Submit

Any time

2019 ( 464 )

2018 ( 705 )

2017 ( 697 )

2016 ( 967 )

Custom range...

Search Results: 1 - 10 of 401677 matches for " M Ferguson "
All listed articles are free for downloading (OA Articles)
Page 1 /401677
Display every page Item
Knee injuries in football: Knee injuries are particularly common in football.
M Ferguson, R Collins
Continuing Medical Education , 2010,
Abstract:
Evaluating the Adequacy of Gravity Models as a Description of Human Mobility for Epidemic Modelling
James Truscott ,Neil M. Ferguson
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002699
Abstract: Gravity models have a long history of use in describing and forecasting the movements of people as well as goods and services, making them a natural basis for disease transmission rates over distance. In agent-based micro-simulations, gravity models can be directly used to represent movement of individuals and hence disease. In this paper, we consider a range of gravity models as fits to movement data from the UK and the US. We examine the ability of synthetic networks generated from fitted models to match those from the data in terms of epidemic behaviour; in particular, times to first infection. For both datasets, best fits are obtained with a two-piece ‘matched’ power law distance distribution. Epidemics on synthetic UK networks match well those on data networks across all but the smallest nodes for a range of aggregation levels. We derive an expression for time to infection between nodes in terms of epidemiological and network parameters which illuminates the influence of network clustering in spread across networks and suggests an approximate relationship between the log-likelihood deviance of model fit and the match times to infection between synthetic and data networks. On synthetic US networks, the match in epidemic behaviour is initially poor and sensitive to the initially infected node. Analysis of times to infection indicates a failure of models to capture infrequent long-range contact between large nodes. An assortative model based on node population size captures this heterogeneity, considerably improving the epidemiological match between synthetic and data networks.
Antigenic Diversity, Transmission Mechanisms, and the Evolution of Pathogens
Alexander Lange ,Neil M. Ferguson
PLOS Computational Biology , 2009, DOI: 10.1371/journal.pcbi.1000536
Abstract: Pathogens have evolved diverse strategies to maximize their transmission fitness. Here we investigate these strategies for directly transmitted pathogens using mathematical models of disease pathogenesis and transmission, modeling fitness as a function of within- and between-host pathogen dynamics. The within-host model includes realistic constraints on pathogen replication via resource depletion and cross-immunity between pathogen strains. We find three distinct types of infection emerge as maxima in the fitness landscape, each characterized by particular within-host dynamics, host population contact network structure, and transmission mode. These three infection types are associated with distinct non-overlapping ranges of levels of antigenic diversity, and well-defined patterns of within-host dynamics and between-host transmissibility. Fitness, quantified by the basic reproduction number, also falls within distinct ranges for each infection type. Every type is optimal for certain contact structures over a range of contact rates. Sexually transmitted infections and childhood diseases are identified as exemplar types for low and high contact rates, respectively. This work generates a plausible mechanistic hypothesis for the observed tradeoff between pathogen transmissibility and antigenic diversity, and shows how different classes of pathogens arise evolutionarily as fitness optima for different contact network structures and host contact rates.
Feature Selection Methods for Identifying Genetic Determinants of Host Species in RNA Viruses
Ricardo Aguas ,Neil M. Ferguson
PLOS Computational Biology , 2013, DOI: 10.1371/journal.pcbi.1003254
Abstract: Despite environmental, social and ecological dependencies, emergence of zoonotic viruses in human populations is clearly also affected by genetic factors which determine cross-species transmission potential. RNA viruses pose an interesting case study given their mutation rates are orders of magnitude higher than any other pathogen – as reflected by the recent emergence of SARS and Influenza for example. Here, we show how feature selection techniques can be used to reliably classify viral sequences by host species, and to identify the crucial minority of host-specific sites in pathogen genomic data. The variability in alleles at those sites can be translated into prediction probabilities that a particular pathogen isolate is adapted to a given host. We illustrate the power of these methods by: 1) identifying the sites explaining SARS coronavirus differences between human, bat and palm civet samples; 2) showing how cross species jumps of rabies virus among bat populations can be readily identified; and 3) de novo identification of likely functional influenza host discriminant markers.
A Many-Body Field Theory Approach to Stochastic Models in Population Biology
Peter J. Dodd, Neil M. Ferguson
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0006855
Abstract: Background Many models used in theoretical ecology, or mathematical epidemiology are stochastic, and may also be spatially-explicit. Techniques from quantum field theory have been used before in reaction-diffusion systems, principally to investigate their critical behavior. Here we argue that they make many calculations easier and are a possible starting point for new approximations. Methodology We review the many-body field formalism for Markov processes and illustrate how to apply it to a ‘Brownian bug’ population model, and to an epidemic model. We show how the master equation and the moment hierarchy can both be written in particularly compact forms. The introduction of functional methods allows the systematic computation of the effective action, which gives the dynamics of mean quantities. We obtain the 1-loop approximation to the effective action for general (space-) translation invariant systems, and thus approximations to the non-equilibrium dynamics of the mean fields. Conclusions The master equations for spatial stochastic systems normally take a neater form in the many-body field formalism. One can write down the dynamics for generating functional of physically-relevant moments, equivalent to the whole moment hierarchy. The 1-loop dynamics of the mean fields are the same as those of a particular moment-closure.
Transmission Parameters of the 2001 Foot and Mouth Epidemic in Great Britain
Irina Chis Ster, Neil M. Ferguson
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000502
Abstract: Despite intensive ongoing research, key aspects of the spatial-temporal evolution of the 2001 foot and mouth disease (FMD) epidemic in Great Britain (GB) remain unexplained. Here we develop a Markov Chain Monte Carlo (MCMC) method for estimating epidemiological parameters of the 2001 outbreak for a range of simple transmission models. We make the simplifying assumption that infectious farms were completely observed in 2001, equivalent to assuming that farms that were proactively culled but not diagnosed with FMD were not infectious, even if some were infected. We estimate how transmission parameters varied through time, highlighting the impact of the control measures on the progression of the epidemic. We demonstrate statistically significant evidence for assortative contact patterns between animals of the same species. Predictive risk maps of the transmission potential in different geographic areas of GB are presented for the fitted models.
Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model
John B. Hopkins, Jake M. Ferguson
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0028478
Abstract: Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs.
Is it time to increase the frequency of use of high-frequency oscillatory ventilation?
Jeffrey M Singh, Niall D Ferguson
Critical Care , 2005, DOI: 10.1186/cc3761
Abstract: Recognition of the impact of ventilator-induced lung injury on morbidity and mortality in patients with acute respiratory distress syndrome (ARDS) has led to an ongoing search for ventilation strategies that limit further damage to the already injured lung. In this issue of Critical Care, Bollen and colleagues [1] present the results of a multicentre randomised controlled trial, comparing high-frequency oscillatory ventilation (HFOV) with conventional ventilation as the primary ventilation mode for adults with ARDS.HFOV applies a continuous distending pressure to the lung around which pressure oscillations are generated. These pressure swings are attenuated by the time they reach the alveolar level, resulting in very small delivered tidal volumes. HFOV is theoretically ideal for lung protection, as this minimal tidal variation in alveolar volume may allow clinicians to recruit the lung, minimising atelectrauma and oxygen toxicity, while still avoiding volutrauma from tidal overdistension. However, potential drawbacks to HFOV also exist, most notably the fact that the majority of adults must have their spontaneous respiratory efforts suppressed since their inspiratory flow demands are often greater than the constant flow of gas in the circuit. This need for heavy sedation (and frequently neuromuscular blockade) means that HFOV may not be an appropriate therapy for patients with mild forms of acute lung injury.An extensively studied and accepted therapy in neonates [2], HFOV is still an emerging ventilator mode in adults. Previous work in this area has shown that HFOV is safe and effective in improving oxygenation in ARDS patients who are failing conventional ventilation [3-5]. However, when HFOV is considered as a primary ventilatory mode to prevent ventilator-induced lung injury, only one clinical trial has been previously published [6]. Mortality was not the primary outcome of this study and the control group arguably did not receive what would today be considered
Mosquito appetite for blood is stimulated by Plasmodium chabaudi infections in themselves and their vertebrate hosts
Heather M Ferguson, Andrew F Read
Malaria Journal , 2004, DOI: 10.1186/1475-2875-3-12
Abstract: Using a rodent malaria model system, behavioural avoidance of super-infection was tested by examining whether already-infected Anopheles stephensi mosquitoes were less responsive to new vertebrate hosts if they were infected. Additionally, a second dose of parasites was given to malaria-infected mosquitoes on a biologically realistic time scale to test whether it impeded the development of a first infection.No effect of a second infected blood meal on either the prevalence or parasite burden arising from a first was found. Furthermore, it was found that not only were infected mosquitoes more likely to take a second blood meal than their uninfected counterparts, they were disproportionately drawn to infected hosts.The alterations in mosquito feeding propensity reported here would occur if parasites have been selected to make infected vertebrate hosts more attractive to mosquitoes, and infected mosquitoes are more likely to seek out new blood meals. Although such a strategy might increase the risk of super-infection, this study suggests the cost to parasite development is not high and as such would be unlikely to outweigh the potential benefits of increasing the contact rate between the parasite's two obligate hosts.Many arthropod disease vectors have multiple opportunities to become infected with the same pathogen species during their lifetime (super-infection). The impact of super-infection within vectors to parasite transmission is largely unknown, and may have substantial impacts on epidemiology. For example, in the laboratory, pathogen transmission can be enhanced when different parasite species co-occur in the same individual vector, a phenomenon that has been observed in some [1-4] but not all mosquito species that have been tested [1,4].The aim of this study was to investigate the potential epidemiological consequences of super-infection of mosquitoes by malaria parasites. Super-infection of vectors by successive parasite infections has been examined in a vari
Epidemic and intervention modelling: a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic
Van Kerkhove,Maria D; Ferguson,Neil M;
Bulletin of the World Health Organization , 2012, DOI: 10.1590/S0042-96862012000400015
Abstract: problem: outbreak analysis and mathematical modelling are crucial for planning public health responses to infectious disease outbreaks, epidemics and pandemics. this paper describes the data analysis and mathematical modelling undertaken during and following the 2009 influenza pandemic, especially to inform public health planning and decision-making. approach: soon after a(h1n1)pdm09 emerged in north america in 2009, the world health organization convened an informal mathematical modelling network of public health and academic experts and modelling groups. this network and other modelling groups worked with policy-makers to characterize the dynamics and impact of the pandemic and assess the effectiveness of interventions in different settings. setting: the 2009 a(h1n1) influenza pandemic. relevant changes: modellers provided a quantitative framework for analysing surveillance data and for understanding the dynamics of the epidemic and the impact of interventions. however, what most often informed policy decisions on a day-to-day basis was arguably not sophisticated simulation modelling, but rather, real-time statistical analyses based on mechanistic transmission models relying on available epidemiologic and virologic data. lessons learnt: a key lesson was that modelling cannot substitute for data; it can only make use of available data and highlight what additional data might best inform policy. data gaps in 2009, especially from low-resource countries, made it difficult to evaluate severity, the effects of seasonal variation on transmission and the effectiveness of non-pharmaceutical interventions. better communication between modellers and public health practitioners is needed to manage expectations, facilitate data sharing and interpretation and reduce inconsistency in results.
Page 1 /401677
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.