A Diffusion Approximation for an Epidemic Model

Influenza is one of the most common and severe diseases worldwide. Devastating epidemics actuated by a new subtype of the influenza A virus occur again and again with the most important example given by the Spanish Flu in 1918/19 with more than 27 million deaths. For the development of pandemic plans it is essential to understand the character of the dissemination of the disease. We employ an extended SIR model for a probabilistic analysis of the spatio-temporal spread of influenza in Germany. The inhomogeneous mixing of the population is taken into account by the introduction of a network of subregions, connected according to Germany's commuter and domestic air traffic. The infection dynamics is described by a multivariate diffusion process, the discussion of which is a major part of this report. We furthermore present likelihood-based estimates of the model parameters

Stochastic modelling of the spatial spread of influenza in Germany

In geographical epidemiology, disease counts are typically available in discrete spatial units and at discrete time-points. For example, surveillance data on infectious diseases usually consists of weekly counts of new infections in pre-defined geographical areas. Similarly, but on a different time-scale, cancer registries typically report yearly incidence or mortality counts in administrative regions. A major methodological challenge lies in building realistic models for space-time interactions on discrete irregular spatial graphs. In this paper, we will discuss an observation-driven approach, where past observed counts in neighbouring areas enter directly as explanatory variables, in contrast to the parameter-driven approach through latent Gaussian Markov random fields (Rue and Held, 2005) with spatio-temporal structure. The main focus will lie on the demonstration of the spread of influenza in Germany, obtained through the design and simulation of a spatial extension of the classical SIR model (Hufnagel et al., 2004)

Stochastic modelling of the spatial spread of influenza in Germany

In geographical epidemiology, disease counts are typically available in discrete spatial units and at discrete time-points. For example, surveillance data on infectious diseases usually consists of weekly counts of new infections in pre-defined geographical areas. Similarly, but on a different time-scale, cancer registries typically report yearly incidence or mortality counts in administrative regions. A major methodological challenge lies in building realistic models for space-time interactions on discrete irregular spatial graphs. In this paper, we will discuss an observation-driven approach, where past observed counts in neighbouring areas enter directly as explanatory variables, in contrast to the parameter-driven approach through latent Gaussian Markov random fields (Rue and Held, 2005) with spatio-temporal structure. The main focus will lie on the demonstration of the spread of influenza in Germany, obtained through the design and simulation of a spatial extension of the classical SIR model (Hufnagel et al., 2004)

Improved compaction of ZnO nano-powder triggered by the presence of acetate and its effect on sintering

The retention of nanocrystallinity in dense ceramic materials is still a challenge, even with the application of external pressure during sintering. The compaction behavior of high purity and acetate enriched zinc oxide (ZnO) nano-powders was investigated. It was found that acetate in combination with water plays a key role during the compaction into green bodies at moderate temperatures. Application of constant pressure resulted in a homogeneous green body with superior packing density (86% of theoretical value) at moderate temperature (85 °C) in the presence of water. In contrast, no improvement in density could be achieved if pure ZnO powder was used. This compaction behavior offers superior packing of the particles, resulting in a high relative density of the consolidated compact with negligible coarsening. Dissolution accompanying creep diffusion based matter transport is suggested to strongly support reorientation of ZnO particles towards densities beyond the theoretical limit for packing of ideal monosized spheres. Finally, the sintering trajectory reveals that grain growth is retarded compared to conventional processing up to 90% of theoretical density. Moreover, nearly no radial shrinkage was observed after sinter-forging for bodies performed with this advanced processing method

Bayesian Inference for Diffusion Processes with Applications in Life Sciences

Diffusion processes are a promising instrument to realistically model the time-continuous evolution of natural phenomena in life sciences. However, approximation of a given system is often carried out heuristically, leading to diffusions that do not correctly reflect the true dynamics of the original process. Moreover, statistical inference for diffusions proves to be challenging in practice as the likelihood function is typically intractable. This thesis contributes to stochastic modelling and statistical estimation of real problems in life sciences by means of diffusion processes. In particular, it creates a framework from existing and novel techniques for the correct approximation of pure Markov jump processes by diffusions. Concerning statistical inference, the thesis reviews existing practices and analyses and further develops a well-known Bayesian approach which introduces auxiliary observations by means of Markov chain Monte Carlo (MCMC) techniques. This procedure originally suffers from convergence problems which stem from a deterministic link between the model parameters and the quadratic variation of a continuously observed diffusion path. This thesis formulates a neat modification of the above approach for general multi-dimensional diffusions and provides the mathematical and empirical proof that the so-constructed MCMC scheme converges. The potential of the newly developed modelling and estimation methods is demonstrated in two real-data application studies: the spatial spread of human influenza in Germany and the in vivo binding behaviour of proteins in cell nuclei

Isolation and Culture of Pulmonary Endothelial Cells from Neonatal Mice

Endothelial cells provide a useful research model in many areas of vascular biology. Since its first isolation 1, human umbilical vein endothelial cells (HUVECs) have shown to be convenient, easy to obtain and culture, and thus are the most widely studied endothelial cells. However, for research focused on processes like angiogenesis, permeability or many others, microvascular endothelial cells (ECs) are a much more physiologically relevant model to study 2. Furthermore, ECs isolated from knockout mice provide a useful tool for analysis of protein function ex vivo. Several approaches to isolate and culture microvascular ECs of different origin have been reported to date 3-7, but consistent isolation and culture of pure ECs is still a major technical problem in many laboratories. Here, we provide a step-by-step protocol on a reliable and relatively simple method of isolating and culturing mouse lung endothelial cells (MLECs). In this approach, lung tissue obtained from 6- to 8-day old pups is first cut into pieces, digested with collagenase/dispase (C/D) solution and dispersed mechanically into single-cell suspension. MLECS are purified from cell suspension using positive selection with anti-PECAM-1 antibody conjugated to Dynabeads using a Magnetic Particle Concentrator (MPC). Such purified cells are cultured on gelatin-coated tissue culture (TC) dishes until they become confluent. At that point, cells are further purified using Dynabeads coupled to anti-ICAM-2 antibody. MLECs obtained with this protocol exhibit a cobblestone phenotype, as visualized by phase-contrast light microscopy, and their endothelial phenotype has been confirmed using FACS analysis with anti-VE-cadherin 8 and anti-VEGFR2 9 antibodies and immunofluorescent staining of VE-cadherin. In our hands, this two-step isolation procedure consistently and reliably yields a pure population of MLECs, which can be further cultured. This method will enable researchers to take advantage of the growing number of knockout and transgenic mice to directly correlate in vivo studies with results of in vitro experiments performed on isolated MLECs and thus help to reveal molecular mechanisms of vascular phenotypes observed in vivo

Developing best practice guidelines on equine colic

Sarah Freeman and Laila Curtis describe an ongoing project that is aiming to develop evidence-based, best practice guidelines to help owners and veterinary surgeons recognise the signs of colic in horses. They also report on the first of two multidisciplinary workshops during which the evidence was discussed by a range of different stakeholders

Die Prävalenz von Pneumocystis jirovecii bei zahnärztlichem Personal und zahnärztlichen Patienten

Peumocystis jirovecii (P. jirovecii) ist ein Pilz, der ubiquitär vorkommt. Sowohl Gesunde als auch immunsupprimierte Personen können mit P. jirovecii besiedelt sein. P. jirovecii kann bei Immunsupprimierten eine Pneumocystis Pneumonie (PCP) verursachen, selten auch Infektionen anderer Organe. Die Übertragung von P. jirovecii erfolgt durch Schmierinfektion und aerogen durch Tröpfcheninfektion, was eine erhöhte Inzidenz von P. jirovecii bei Personen mit beruflicher Exposition zu menschlichen Aerosolen vermuten lässt. Ziel dieser Studie war es, zu untersuchen, ob Zahnärzte und zahnärztliches Personal im Vergleich zu zahnärztlichen Patienten vermehrt mit P. jirovecii besiedelt sind. Dabei wurde auch evaluiert, inwieweit das Tragen von Mundschutz und Handschuhen in einer Zahnarztpraxis sowie Tierkontakte, Nikotin- und Alkoholkonsum eine Besiedelung mit P. jirovecii beeinflussen

Frequency of shedding of respiratory pathogens in horses recently imported to the United States.

BackgroundImported horses that have undergone recent long distance transport might represent a serious risk for spreading infectious respiratory pathogens into populations of horses.ObjectiveTo investigate the frequency of shedding of respiratory pathogens in recently imported horses.AnimalsAll imported horses with signed owner consent (n = 167) entering a USDA quarantine for contagious equine metritis from October 2014 to June 2016 were enrolled in the study.MethodsProspective observational study. Enrolled horses had a physical examination performed and nasal secretions collected at the time of entry and subsequently if any horse developed signs of respiratory disease during quarantine. Samples were assayed for equine influenza virus (EIV), equine herpesvirus type-1, -2, -4, and -5 (EHV-1, -2, -4, -5), equine rhinitis virus A (ERAV), and B (ERBV) and Streptococcus equi subspecies equi (S. equi) using quantitative PCR (qPCR).ResultsEquine herpesviruses were detected by qPCR in 52% of the study horses including EHV-2 (28.7%), EHV-5 (40.7%), EHV-1 (1.2%), and EHV-4 (3.0%). Clinical signs were not correlated with being qPCR-positive for EHV-4, EHV-2, or EHV-5. None of the samples were qPCR-positive for EIV, ERAV, ERBV, and S. equi. The qPCR assay failed quality control for RNA viruses in 25% (46/167) of samples.Conclusions and clinical importanceClinical signs of respiratory disease were poorly correlated with qPCR positive status for EHV-2, -4, and -5. The importance of γ-herpesviruses (EHV-2 and 5) in respiratory disease is poorly understood. Equine herpesvirus type-1 or 4 (EHV-1 or EHV-4) were detected in 4.2% of horses, which could have serious consequences if shedding animals entered a population of susceptible horses. Biosecurity measures are important when introducing recently imported horses into resident US populations of horses

Antimicrobial resistance patterns of Campylobacter from feedlot cattle

Aims: This study examined 448 Campylobacter strains isolated in 1999 and 2000 from US feedlot cattle for resistance to 12 antimicrobials. Methods and Results: Isolates were tested for antimicrobial susceptibility using the E-test method. Approximately 60% (n = 267) were resistant to one or more antimicrobials, and 19·6% (n = 88) were resistant to two or more antimicrobials. Of the Campylobacter jejuni isolates, 49·1% (n = 187) were resistant to tetracycline, 10·2% (n = 39) were resistant to nalidixic acid, 8·4% were resistant to trimethoprim/sulfamethoxazole, and 1·8% (n = 7) were resistant to ciprofloxacin. Resistance to any of the other eight antimicrobials was 1·3% or less, but 14·4% (n = 55) were resistant to two or more antimicrobials. In the Campylobacter coli group, 65·7% (n = 44) were resistant to tetracycline, 52·2% (n = 35) were resistant to trimethoprim/sulfamethoxazole, 22·4% (n = 15) were resistant to nalidixic acid, and 9·0% (n = 6) were resistant to ciprofloxacin. Resistance to any of the remaining eight antimicrobials was 3·0% or less, although 49·3% (n = 33) were resistant to two or more antimicrobials. Conclusions: Although antimicrobials are widely used in US feedlot cattle production, our results demonstrate generally low levels of resistance to a broad range of commonly used antimicrobials relative to other recent studies. Significance and Impact of the Study: Resistance data on Campylobacter isolated from this major US livestock commodity is lacking. This overview enhances current knowledge and provides a basis for further studies