First-passage times in a critical stochastic model

Average first-passage times for a single-variable stochastic model with a critical fixed point at the origin are computed by exact enumeration. The numerical measurements show excellent agreement with analytical results. The scaling function approaches the predicted asymptotic dependence.     

Dynamical analysis of age-structured pertussis model with covert infection

An age-structured pertussis model with covert infection is proposed to understand the effect of covert infection on the recurrence of pertussis. It is found that vaccination only for young children does not have a decisive effect on whooping cough control. It is shown that although the vaccine coverage rate is relatively high, the model has a backward bifurcation for a larger covert infection rate. In addition, sufficient conditions for the disease-free steady state to be globally asymptotically stable are obtained.     

微量元素与脑卒中(2)

脑卒中是目前中国最重要的公共卫生问题,正以其高发病率、高死亡率对我国造成巨大的社会、经济困难。从脑卒中的流行病学特征、脑卒中发病的危险因素、脑卒中患者的微量元素失衡及微量元素检测的临床意义四个方面阐述了微量元素与脑卒中的关系。     

Site- and event-specific wastewater-based epidemiology: Current status and future perspectives

Wastewater-based epidemiology (WBE) can provide objective and reliable data to monitor spatio‐temporal patterns of licit and illicit drug use. Numerous studies have been published relating to sampling, sample stability, validation of analytical protocols and the back-calculation of drug consumption. The majority of these studies focus on sampling from municipal sewage treatment plants, but an increasing number of studies have used WBE to monitor community-specific substance use and use during special events. This paper presents a systematic review of published WBE studies of drug use trends in educational institutions and prisons, as well as during music festivals, sporting events, and holidays. A discussion on the application and benefits of using wastewater-based epidemiology in these specific cases is presented together with an examination of current challenges and future perspectives.     

Multiblock redundancy analysis: interpretation tools and application in epidemiology

For the purpose of exploring and modeling the relationships between a dataset Y and several datasets () measured on the same individuals, multiblock Partial Least Squares is a regression technique which is widely used, particularly in process monitoring, chemometrics and sensometrics. In the same vein, a new multiblock method, called multiblock Redundancy Analysis, is proposed. It is introduced by maximizing a criterion that reflects the objectives to be addressed. The solution of this maximization problem is directly derived from the eigenanalysis of a matrix. In addition, this method is related to other multiblock methods. Multiblock modeling methods provide to the user a large spectrum of interpretation indices for the investigation of the relationships among variables and among datasets. They are related to the criterion to maximize and therefore directly derived from the maximization problem under consideration. The interest of multiblock Redundancy Analysis and the associated interpretation tools are illustrated using a dataset in the field of veterinary epidemiology. Copyright © 2011 John Wiley & Sons, Ltd.     

An eco‐epidemiological predator–prey model where predators distinguish between susceptible and infected prey

A predator–prey model with disease amongst the prey and ratio‐dependent functional response for both infected and susceptible prey is proposed and its features analysed. This work is based on previous mathematical models to analyse the important ecosystem of the Salton Sea in Southern California and New Mexico where birds (particularly pelicans) prey on fish (particularly tilapia). The dynamics of the system around each of the ecologically meaningful equilibria are presented. Natural disease control is considered before studying the impact of the disease in the absence of predators and the interaction of predators and healthy prey and the disease effects on predators in the absence of healthy prey. Our theoretical results are confirmed by numerical simulation. Copyright © 2016 John Wiley & Sons, Ltd.     

Number of infections suffered by a focal individual in a two‐strain SIS model with partial cross‐immunity

We study a stochastic model for the spread of two pathogen strains—termed type 1 and type 2—among a homogeneously mixing community consisting of a finite number of individuals. In the model, we assume partial cross‐immunity, exogenous streams of infection, and that the degree of severity of a newly infective individual depends on who this infective individual was infected by. The aim is to characterize the joint probability distribution of the numbers M₁ and M₂ of type‐1 and type‐2 infections suffered by a focal individual during an outbreak of the disease. We present iterative procedures for computing the probability mass function of (M₁,M₂) under the assumption that the initial state of the focal individual is known, and a numerical study of the model is performed to investigate the influence of certain key parameters on the spread of resistant bacteria in hospitals.     

On application of asymptotic generalized discrepancy principle to the analysis of epidemiology models

Various implementations of the discrepancy principle (DP) for linear ill-posed problems are given in a large number of papers. In all of these papers, the DP has been justified for special types of regularization strategies. In our paper, a unified approach to the construction of the DP is presented that does not require any special structure of the regularizing operator. In that respect, the new method generalizes all prior results on the DP principle for linear irregular operator equations with noisy data. The efficiency of the proposed scheme is demonstrated for a parameter identification problem in avian influenza. In solving this particular inverse problem, it turned out to be beneficial to use some regularization strategies, for which the earlier (structure-based) discrepancy principles were not applicable. This motivated the development of a novel DP put forth in the current paper.     

Eco-epidemiological model with fatal disease in the prey

We investigate a model consisting of a predator population and both susceptible and infected prey populations. The predator can feed on either prey species but instead of choosing individuals at random the predator feeds preferentially on the most abundant prey species. More specifically we assume that the likelihood of a predator catching a susceptible prey or an infected prey is proportional to the numbers of these two different types of prey species. This phenomenon, involving changing preference from susceptible to infected prey, is called switching. Mukhopadhyay studied a switching model and proposed that the interaction of predators with infected prey is beneficial for the growth of the predator. In this model, we assume that the predator will eventually die as a result of eating infected prey. We find a threshold parameter $R_0$ and showed that the disease will be eradicated from the system if $R_0<1$.