How Bad Can a Crisis Be If It Does Not Top the News?

Sudden onset of front-page news about the U.S. financial crisis, beginning September 6, 2008, may have exacerbated underlying financial problems and facilitated the spread of risk panic to other nations.     

Exact Bayesian Inference and Model Selection for Stochastic Models of Epidemics Among a Community of Households

Abstract.  Much recent methodological progress in the analysis of infectious disease data has been due to Markov chain Monte Carlo (MCMC) methodology. In this paper, it is illustrated that rejection sampling can also be applied to a family of inference problems in the context of epidemic models, avoiding the issues of convergence associated with MCMC methods. Specifically, we consider models for epidemic data arising from a population divided into households. The models allow individuals to be potentially infected both from outside and from within the household. We develop methodology for selection between competing models via the computation of Bayes factors. We also demonstrate how an initial sample can be used to adjust the algorithm and improve efficiency. The data are assumed to consist of the final numbers ultimately infected within a sample of households in some community. The methods are applied to data taken from outbreaks of influenza.     

The performance of several statistical tests for seasonality in monthly data

The type I and II error rates of several statistical tests for seasonality in monthly data were investigated through a computer simulation study at two nominal significance levels, α=1% and α=5%. Three models were used for the variation: annual sinusoidal; semi—annual sinusoidal; and a curve which is constant in all but three consecutive months of the year, when it exhibits a constant increase (a “one—pulse” model). The statistical tests are compared in terms of the simulation results. These results may be applied to calculate either the sample size required to detect seasonal variation of fixed amplitude or the probability of detecting seasonal variation of variable amplitude with a fixed sample size. A numerical case study is given     

A Quantitative Assessment of the Risk for Highly Pathogenic Avian Influenza Introduction into Spain via Legal Trade of Live Poultry

Highly pathogenic avian influenza (HPAI) is considered one of the most important diseases of poultry. During the last 9 years, HPAI epidemics have been reported in Asia, the Americas, Africa, and in 18 countries of the European Union (EU). For that reason, it is possible that the risk for HPAI virus (HPAIV) introduction into Spain may have recently increased. Because of the EU free‐trade policy and because legal trade of live poultry was considered an important route for HPAI spread in certain regions of the world, there are fears that Spain may become HPAIV‐infected as a consequence of the legal introduction of live poultry. However, no quantitative assessment of the risk for HPAIV introduction into Spain or into any other EU member state via the trade of poultry has been published in the peer‐reviewed literature. This article presents the results of the first quantitative assessment of the risk for HPAIV introduction into a free country via legal trade of live poultry, along with estimates of the geographical variation of the risk and of the relative contribution of exporting countries and susceptible poultry species to the risk. The annual mean risk for HPAI introduction into Spain was estimated to be as low as 1.36 × 10⁻³, suggesting that under prevailing conditions, introduction of HPAIV into Spain through the trade of live poultry is unlikely to occur. Moreover, these results support the hypothesis that legal trade of live poultry does not impose a significant risk for the spread of HPAI into EU member states.     

Efficient method for identification of cyclic trends in incidence

Various methods for estimating the parameters of the simple harmonic curve and corresponding statistics for testing the significance of the sinusoidal trend are investigated. The locally reasonable method is almost fully efficient when the size of the trend is very small; however, the maximum likelihood method is preferred generally, especially when the trend is not very small. The log likelihood ratio test is more powerful than the R test which is based on locally reasonable estimates. The efficient method and the log likelihood ratio or equivalent tests are the best statistical techniques for identifying the cyclical trend. Thus they are the methods of choice when adequate computing facilities are available.     

长江滨带植被的垂直地带性分布初探

本文介绍了长江滨带的垂直地带生物群系，并对植被垂直分布的原因及意义进行了分析讨论     

Spatio‐temporal modelling of disease mapping of rates

This paper studies generalized linear mixed models (GLMMs) for the analysis of geographic and temporal variability of disease rates. This class of models adopts spatially correlated random effects and random temporal components. Spatio‐temporal models that use conditional autoregressive smoothing across the spatial dimension and autoregressive smoothing over the temporal dimension are developed. The model also accommodates the interaction between space and time. However, the effect of seasonal factors has not been previously addressed and in some applications (e.g., health conditions), these effects may not be negligible. The authors incorporate the seasonal effects of month and possibly year as part of the proposed model and estimate model parameters through generalized estimating equations. The model provides smoothed maps of disease risk and eliminates the instability of estimates in low‐population areas while maintaining geographic resolution. They illustrate the approach using a monthly data set of the number of asthma presentations made by children to Emergency Departments (EDs) in the province of Alberta, Canada, during the period 2001–2004. The Canadian Journal of Statistics 38: 698–715; 2010 © 2010 Statistical Society of Canada     

Growth Curves with Explanatory Variables and Estimation of the Effect of Tagging

The von Bertalanffy growth model is extended to incorporate explanatory variables. The generalized model includes the switched growth model and the seasonal growth model as special cases, and can also be used to assess the tagging effect on growth. Distribution-free and consistent estimating functions are constructed for estimation of growth parameters from tag-recapture data in which age at release is unknown. This generalizes the work of James (1991, Biometrics 47 1519–1530) who considered the classical model and allowed for individual variability in growth. A real dataset from barramundi ( Lates calcarifer ) is analysed to estimate the growth parameters and possible effect of tagging on growth.     

关于季节指数约束条件和极大似然估计的研究——基于三种加法和乘法模型

使用科学的方法观测并计算某种社会经济现象的季节性变动,对于把握其真实的环比变动具有重要的现实意义。使用经典方法计算季节指数以反映现象的季节性变动,因其结果不够严谨和完备,是一个至今尚未获得完满解决的问题。为了提高计算季节指数结果的科学性、严谨性、完备性,基于符合三种加法和乘法模型的社会经济现象,解析其中各季节指数之间存在的约束条件,运用数理统计中极大似然估计理论与方法,推导出与经典方法算式相近的季节指数的约束极大似然估计算式,给出季节指数的区间估计,并举例对获得的结果做了计算和对比验证。     

大流感爆发对中国经济的影响预测

当前,人类面临新一次大流感的威胁正在不断升级,分析与评估其可能带来的经济影响是制定应对大流感战略的重要基础。根据历史经验将大流感的爆发区分为温和与严重两种情况,在一系列假定的基础上对其经济影响进行估算。如果大流感爆发,不管是两种情况的哪一种,后果都是严重的,对中国经济的影响程度大体相当于2003年SARS(非典)情况的1—6倍。在温和情形下,大概会造成当年GDP下降0.9%,略大于2003年SARS给中国带来的影响,相当于2007年中国GDP减少2.1千亿元。在严重情形下,将可能降低中国当年GDP约5.1%,相当于2003年SARS的情况的6倍,相当于2007年GDP减少1.2万亿元。应充分认识到大流感的危害性,尽快完善应对大流感的国家战略;制定明确的财政支持计划,估计全国需要专项准备经费120亿元人民币以上;在危机应对预案中要有明确的经济工作预案。