Estimation of cyclic long-memory parameters

This paper studies cyclic long-memory processes with Gegenbauer-type spectral densities. For a semiparametric statistical model, new simultaneous estimates for singularity location and long-memory parameters are proposed. This generalized filtered method-of-moments approach is based on general filter transforms that include wavelet transformations as a particular case. It is proved that the estimates are almost surely convergent to the true values of parameters. Solutions of the estimation equations are studied, and adjusted statistics are proposed. Monte-Carlo study results are presented to confirm the theoretical findings.     

Block bootstrap for periodic characteristics of periodically correlated time series

This research is dedicated to the study of periodic characteristics of periodically correlated time series such as seasonal means, seasonal variances and autocovariance functions. Two bootstrap methods are used: the extension of the usual Moving Block Bootstrap (EMBB) and the Generalised Seasonal Block Bootstrap (GSBB). The first approach is proposed, because the usual Moving Block Bootstrap does not preserve the periodic structure contained in the data and cannot be applied for the considered problems. For the aforementioned periodic characteristics the bootstrap estimators are introduced and consistency of the EMBB in all cases is obtained. Moreover, the GSBB consistency results for seasonal variances and autocovariance function are presented. Additionally, the bootstrap consistency of both considered techniques for smooth functions of the parameters of interest is obtained. Finally, the simultaneous bootstrap confidence intervals are constructed. A simulation study to compare their actual coverage probabilities is provided. A real data example is presented.     

Modeling exotic highly pathogenic avian influenza virus entrance risk through air passenger violations

The highly pathogenic avian influenza virus (HPAIV) is able to survive in poultry products and could be carried into a country by air travelers. An assessment model was constructed to estimate the probability of the exotic viable HPAIV entering Taiwan from two neighboring areas through poultry products carried illegally by air passengers at Taiwan's main airports. The entrance risk was evaluated based on HPAIV-related factors (the prevalence and the incubation period of HPAIV; the manufacturing process of poultry products; and the distribution-storage-transportation factor event) and the passenger event. Distribution functions were adopted to simulate the probabilities of each HPAIV factor. The odds of passengers being intercepted with illegal poultry products were estimated by logistic regression. The Monte Carlo simulation established that the risk caused by HPAIV-related factors from area A was lower than area B, whereas the entrance risk by the passenger event from area A was similar to area B. Sensitivity analysis showed that the incubation period of HPAIV and the interception of passenger violations were major determinants. Although the result showed viable HPAIV was unlikely to enter Taiwan through meat illegally carried by air passengers, this low probability could be caused by incomplete animal disease data and modeling uncertainties. Considering the negative socioeconomic impacts of HPAIV outbreaks, strengthening airport quarantine measures is still necessary. This assessment provides a profile of HPAIV entrance risk through air travelers arriving from endemic areas and a feasible direction for quarantine and public health measures.     

Risk Communication,Values Clarification,and Vaccination Decisions

Many health‐related decisions require choosing between two options, each with risks and benefits. When presented with such tradeoffs, people often make choices that fail to align with scientific evidence or with their own values. This study tested whether risk communication and values clarification methods could help parents and guardians make evidence‐based, values‐congruent decisions about children's influenza vaccinations. In 2013–2014 we conducted an online 2×2 factorial experiment in which a diverse sample of U.S. parents and guardians (n = 407) were randomly assigned to view either standard information about influenza vaccines or risk communication using absolute and incremental risk formats. Participants were then either presented or not presented with an interactive values clarification interface with constrained sliders and dynamic visual feedback. Participants randomized to the risk communication condition combined with the values clarification interface were more likely to indicate intentions to vaccinate (β = 2.10, t(399) = 2.63, p < 0.01). The effect was particularly notable among participants who had previously demonstrated less interest in having their children vaccinated against influenza (β = –2.14, t(399) = –2.06, p < 0.05). When assessing vaccination status reported by participants who agreed to participate in a follow‐up study six months later (n = 116), vaccination intentions significantly predicted vaccination status (OR = 1.66, 95%CI (1.13, 2.44), p < 0.05) and rates of informed choice (OR = 1.51, 95%CI (1.07, 2.13), p < 0.012), although there were no direct effects of experimental factors on vaccination rates. Qualitative analysis suggested that logistical barriers impeded immunization rates. Risk communication and values clarification methods may contribute to increased vaccination intentions, which may, in turn, predict vaccination status if logistical barriers are also addressed.     

Quantitative Links Between Arsenic Exposure and Influenza A (H1N1) Infection‐Associated Lung Function Exacerbations Risk

The objective of this study was to link arsenic exposure and influenza A (H1N1) infection‐induced respiratory effects to assess the impact of arsenic‐contaminated drinking water on exacerbation risk of A (H1N1)‐associated lung function. The homogeneous Poisson process was used to approximate the related processes between arsenic exposure and influenza‐associated lung function exacerbation risk. We found that (i) estimated arsenic‐induced forced expiratory volume in 1 second (FEV₁) reducing rates ranged from 0.116 to 0.179 mL/μg for age 15–85 years, (ii) estimated arsenic‐induced A (H1N1) viral load increasing rate was 0.5 mL/μg, (iii) estimated A (H1N1) virus‐induced FEV₁ reducing rate was 0.10 mL/logTCID50, and (iv) the relationship between arsenic exposure and A (H1N1)‐associated respiratory symptoms scores (RSS) can be described by a Hill model. Here we showed that maximum RSS at day 2 postinfection for Taiwan, West Bengal (India), and the United States were estimated to be in the severe range of 0.83, 0.89, and 0.81, respectively, indicating that chronic arsenic exposure and A (H1N1) infection together are most likely to pose potential exacerbations risk of lung function, although a 50% probability of lung function exacerbations risk induced by arsenic and influenza infection was within the mild and moderate ranges of RSS at day 1 and 2 postinfection. We concluded that avoidance of drinking arsenic‐containing water could significantly reduce influenza respiratory illness and that need will become increasingly urgent as the novel H1N1 pandemic influenza virus infects people worldwide.     

A simulation study of l1:estimation of a seasonal moving average time series model

A detailed simulation study is reported on the application of l₁:estimations to a seasonal moving average model. It is found that the asymptotic normal distribution is a nonapproximation to the finite sample distribution. However, the expected benefits of l₁:estimation relative to l₂:are partially realised for nonnormal innovative distributions.     

Use of generalized estimating equations in a trial in influenza to explore treatment effects over time

For trials with repeated measurements of outcome, analyses often focus on univariate outcomes, such as analysis of summary measures or of the last on‐treatment observation. Methods which model the whole data set provide a rich source of approaches to analysis. For continuous data, mixed‐effect modelling is increasingly used. For binary and categorical data, models based on use of generalized estimating equations account for intra‐subject correlation and allow exploration of the time course of response, as well as providing a useful way to account for missing data, when such data can be maintained as missing in the analysis. The utility of this approach is illustrated by an example from a trial in influenza. Copyright © 2004 John Wiley & Sons Ltd.     

一次华南前汛期暴雨分析及减灾启示

该文通过对2004年5月我国华南地区一次前汛期暴雨的分析,以及我国大水年汛期多雨时段大型低空环流特征的分析,初步认定:我国暴雨及特大暴雨的发生,均与“半球间宏观系统”活动有关。这一发现,不仅对我国特大暴雨及洪涝灾害的预测与监测有着指导意义,也为防灾、减灾工作开辟了一个新的研究思路与途径。     

Mad Cows and Sick Birds: Financing International Responses to Animal Disease in Developing Countries

Because many animal diseases have strong transboundary attributes, their control can be reasonably characterised as an international public good. The potential for reservoirs of transboundary diseases to persist in developing countries that lack the capacity or incentives to control them implies a need for international financial transfers to fund control. However, the costs of control can be large compared with development assistance budgets, and the benefits small compared with the global benefits of control and the local benefits of other priority investments. This article outlines a framework for setting priorities for international development assistance for animal disease control based on the incidence of market and non‐market impacts and the context in which outbreaks take place in endemic and susceptible countries.     

Seasonal Adjustment of the Monetary Aggregates: Summary of the Federal Reserve's Committee Report

The Committee of Experts on Seasonal Adjustment Techniques was formed by the Federal Reserve Board to examine and make recommendations concerning the Board's procedures for seasonally adjusting the money supply and related series. This article summarizes the report of that committee.