A Generalist Predator Regulating Spread of a Wildlife Disease: Exploring Two Infection Transmission Scenarios

Ecoepidemiology is a well-developed branch of theoretical ecology, which explores interplay between the trophic interactions and the disease spread. In most ecoepidemiological models, however, the authors assume the predator to be a specialist, which consumes only a single prey species. In few existing papers, in which the predator was suggested to be a generalist, the alternative food supply was always considered to be constant. This is obviously a simplification of reality, since predators can often choose between a number of different prey. Consumption of these alternative prey can dramatically change their densities and strongly influence the model predictions. In this paper, we try to bridge the gap and explore a generic ecoepidemiological system with a generalist predator, where the densities of all prey are dynamical variables. The model consists of two prey species, one of which is subject to an infectious disease, and a predator, which consumes both prey species. We investigate two main scenarios of infection transmission mode: (i) the disease transmission rate is predator independent and (ii) the transmission rate is a function of predator density. For both scenarios we fulfil an extensive bifurcation analysis. We show that including a second dynamical prey in the system can drastically change the dynamics of the single prey case. In particular, the presence of a second prey impedes disease spread by decreasing the basic reproduction number and can result in a substantial drop of the disease prevalence. We demonstrate that with efficient consumption of the second prey species by the predator, the predator-dependent disease transmission can not destabilize interactions, as in the case with a specialist predator. Interestingly, even if the population of the second prey eventually vanishes and only one prey species finally remains, the system with two prey species may exhibit different properties to those of the single prey system.

A dynamic view of the spread and intracellular distribution of Salmonella enterica.

The events that determine the dynamics of proliferation, spread and distribution of microbial pathogens within their hosts are surprisingly heterogeneous and poorly understood. We contend that understanding these phenomena at a sophisticated level with the help of mathematical models is a prerequisite for the development of truly novel, targeted preventative measures and drug regimes. We describe here recent studies of Salmonella enterica infections in mice which suggest that bacteria resist the antimicrobial environment inside host cells and spread to new sites, where infection foci develop, and thus avoid local escalation of the adaptive immune response. We further describe implications for our understanding of the pathogenic mechanism inside the host.

Simulations of oil spread on a water surface

Numerical simulation of an oil slick spreading on still and wavy surfaces is described in this paper. The so-called sigma transformation is used to transform the time-varying physical domain into a fixed calculation domain for the water wave motions and, at the same time, the continuity equation is changed into an advection equation of wave elevation. This evolution equation is discretized by the forward time and central space scheme, and the momentum equations by the projection method. A damping zone is set up in front of the outlet boundary coupled with a Sommerfeld-Orlanski condition at that boundary to minimize the wave reflection. The equations for the oil slick are depth-averaged and coupled with the water motions when solving numerically. As examples, sinusoidal and solitary water waves, the oil spread on a smooth plane and on still and wavy water surfaces are calculated to examine the accuracy of simulating water waves by Navier-Stokes equations, the effect of damping zone on wave reflection and the precise structures of oil spread on waves.

Spread of Salmonella enterica in the body during systemic infection: unravelling host and pathogen determinants.

Salmonella enterica causes a range of life-threatening diseases in humans and animals worldwide. Current treatments for S. enterica infections are not sufficiently effective, and there is a need to develop new vaccines and therapeutics. An understanding of how S. enterica spreads in tissues has very important implications for targeting bacteria with vaccine-induced immune responses and antimicrobial drugs. Development of new control strategies would benefit from a more sophisticated evaluation of bacterial location, spatiotemporal patterns of spread and distribution in the tissues, and sites of microbial persistence. We review here recent studies of S. enterica serovar Typhimurium (S. Typhimurium) infections in mice, an established model of systemic typhoid fever in humans, which suggest that continuous bacterial spread to new infection foci and host phagocytes is an essential trait in the virulence of S. enterica during systemic infections. We further highlight how infections within host tissues are truly heterogeneous processes despite the fact that they are caused by the expansion of a genetically homogeneous microbial population. We conclude by discussing how understanding the within-host quantitative, spatial and temporal dynamics of S. enterica infections might aid the development of novel targeted preventative measures and drug regimens.

Income risk of EU coal-fired power plants after Kyoto

Coal-fired power plants may enjoy a significant advantage relative to gas plants in terms of cheaper fuel cost. Still, this advantage may erode or even turn into disadvantage depending on CO2 emission allowance price. This price will presumably rise in both the Kyoto Protocol commitment period (2008-2012) and the first post-Kyoto years. Thus, in a carbon-constrained environment, coal plants face financial risks arising in their profit margins, which in turn hinge on their so-called "clean dark spread". These risks are further reinforced when the price of the output electricity is determined by natural gas-fired plants' marginal costs, which differ from coal plants' costs. We aim to assess the risks in coal plants' margins. We adopt parameter values estimated from empirical data. These in turn are derived from natural gas and electricity markets alongside the EU ETS market where emission allowances are traded. Monte Carlo simulation allows to compute the expected value and risk profile of coal-based electricity generation. We focus on the clean dark spread in both time periods under different future scenarios in the allowance market. Specifically, bottom 5% and 10% percentiles are derived. According to our results, certain future paths of the allowance price may impose significant risks on the clean dark spread obtained by coal plants.

Does the Term Spread play a role in the FED's reaction function? An Empirical Investigation

Using US data for the period 1967:5-2002:4, this paper empirically investigates the performance of a Fed’s reaction function (FRF) that (i) allows for the presence of switching regimes, (ii) considers the long-short term spread in addition to the typical variables, (iii) uses an alternative monthly indicator of general economic activity suggested by Stock and Watson (1999), and (iv) considers interest rate smoothing. The estimation results show the existence of three switching regimes, two characterized by low volatility and the remaining regime by high volatility. Moreover, the scale of the responses of the Federal funds rate to movements in the rate of inflation and the economic activity index depends on the regime. The estimation results also show robust empirical evidence that the importance of the term spread in the FRF has increased over the sample period and the FRF has been more stable during the term of office of Chairman Greenspan than in the pre-Greenspan period.

Understanding the ex-ante cost of liquidity in the limit order book: A note

This paper estimates a new measure of liquidity costs in a market driven by orders. It represents thecost of simultaneously buying and selling a given amount of shares, and it is given by a single measure of ex-ante liquidity that aggregates all available information in the limit order book for a given number of shares. The cost of liquidity is an increasing function relating bid-ask spreads with the amounts available for trading. This measure completely characterizes the cost of liquidity of any given asset. It does not suffer from the usual ambiguities related to either the bid-ask spread or depth when they are considered separately. On the contrary, with a single measure, we are able to capture all dimensions of liquidity costs on ex-ante basis.

The role of the term spread in an augmented Taylor rule: An empirical investigation

Using US data for the period 1967:5-2002:4, this paper empirically investigates the performance of an augmented version of the Taylor rule (ATR) that (i) allows for the presence of switching regimes, (ii) considers the long-short term spread in addition to the typical variables, (iii) uses an alternative monthly indicator of general economic activity suggested by Stock and Watson (1999), and (iv) considers interest rate smoothing. The estimation results show the existence of switching regimes, one characterized by low volatility and the other by high volatility. Moreover, the scale of the responses of the Federal funds rate to movements in the term spread, inflation and the economic activity index depend on the regime. The estimation results also show robust empirical evidence that the ATR has been more stable during the term of office of Chairman Greenspan than in the pre-Greenspan period. However, a closer look at the Greenspan period shows the existence of two alternative regimes and that the response of the Fed funds rate to inflation has not been significant during this period once the term spread is considered.

El componente de selección adversa de la horquilla de precios cotizada: una revisión de los modelos de estimación

[ES] Una de las principales preocupaciones en el área de la microestructura del mercado ha sido la estimación de los componentes no observables de la horquilla de precios a partir de las series de datos que proporcionan los mercados financieros, despertando quizá un mayor interés el de selección adversa por la implicaciones que supone la existencia del mismo. Esto ha provocado el desarrollo de numerosos modelos empíricos que, basándose en las propiedades estadísticas de las series de precios, proporcionan dichas estimaciones. La mayor disponibilidad de datos existentes en los mercados ha permitido el desarrollo en los últimos años de modelos basados en técnicas estadísticas más complejas como son el método generalizado de momentos o la metodología VAR y cuya base de partida es la dinámica de la formación del precio, y, en concreto, cómo la información privada de las transacciones se recoge en los nuevos precios cotizados. El objetivo de este trabajo es analizar este último grupo de trabajos, es decir, aquellos modelos de estimación de los componentes de la horquilla basados en la dinámica de la formación de precios que, además de permitir la estimación del componente de selección adversa en series temporales, suponen una herramienta fundamental para analizar el proceso de incorporación de la información a los precios cotizados en los distintos mercados.