An Infection Control Program for a 2009 Influenza A H1N1 Outbreak in a University-Based Summer Camp

Abstract

Objectives: Describe two 2009-H1N1 influenza outbreaks in university-based summer camps and the implementation of an infection control program. Participants: 7,906 campers across 73 residential camps from May 21–August 2, 2009. Methods: Influenza-like-illness (ILI) was defined as fever with cough and/or sore throat. Influenza A was identified using PCR or rapid-antigen testing. We implemented an infection control program consisting of education, hand hygiene, disinfection, symptom screening, and ILI case management. Results: An initial ILI cluster involved 60 cases across 3 camps from June 17–July 2. Academic Camp-1 had the most cases (n = 45, 14.9% attack rate); influenza A was identified in 84% of those tested. Despite implementation of an infection control program, a second ILI cluster began on July 12 in Academic Camp-2 (n = 47, 15.0% attack rate). Conclusions: ILI can spread rapidly in a university-based residential camp. Infection control is an important aspect of the medical response but is challenging to implement.     

Influenza-Like Illness Among University Students: Symptom Severity and Duration Due to Influenza Virus Infection Compared to Other Etiologies

Abstract

Objective: University students with influenza-like illness (ILI) were assessed to determine whether symptom severity, duration, or missed days of school or work varied according to etiology. Participants: Sixty persons presenting to a university health clinic with ILI symptoms during 3 consecutive influenza seasons completed baseline survey and viral testing; 51 (85%) completed follow-up. Methods: Influenza viral culture and polymerase chain reaction and respiratory virus immunofluorescence assay testing were performed. Information collected at baseline and follow-up included symptom occurrence, severity, duration, and numbers of days of work and school missed. Results: Influenza virus was confirmed in 63% of participants. Influenza-positive individuals were no more likely to report any symptom or miss more days of school or work. Self-reported severity and durations of symptoms were similar between groups. Conclusions: Students with influenza-associated ILI were similar to those with noninfluenza ILI with respect to severity, duration, and numbers of days of school and work missed.     

The effect of World War I and the 1918 influenza pandemic on cohort life expectancy of South Australian males born in 1881–1900

Cohort lifetime distribution functions have been estimated for the twenty separate calendar year cohorts of South Australian males born in 1881–1900. A cohort life expectancy at birth was calculated from each of these distribution functions, and a composite assessment made of the reduction in cohort life expectancy at birth due to both World War I 1914–1918 and the 1918 Influenza Pandemic. By partitioning each cohort, the cohort life expectancy at birth of the subgroup that had overseas military service is estimated to be 85 to 90 per cent of the cohort life expectancy at birth of the subgroup that remained in South Australia.     

论近代粤丝出口的市场规律和特征

由于亚热带季风气候的影响 ,以蚕丝生产为基础的粤丝出口在量与质等方面都呈现出明显的季节变化 :一般 4、5月份第一造新丝上市 ,但质、量欠佳 ,对出口贸易影响不大 ;6月份第四造生丝质、量最优 ,形成出口交易高潮 ;前后多造蚕丝相继上市 ,使交易旺期持续到 10月份。同时在近代社会背景下 ,粤丝价格深受国际市场的支配和影响 ,并被欧美列强恣意操纵 ;其变化在宏观上形成由涨到落的趋势 ,微观上则呈现出波动频繁等特点     

Measures of Variability for Model-Based Seasonal Adjustment Procedures

An algorithm is derived that develops measures of variability for the estimates of the nonseasonal component computed from a model-based seasonal adjustment procedure. The measures of variability are developed from signal extraction theory. Properties of components of the variance are developed, and the behavior of the variance is investigated for one popular time series model. The results are illustrated by using real data.     

福建省社会消费品零售总额的预测

以2004年1月至2010年12月福建省社会消费品零售总额月度数据为样本,建立了时间序列季节模型和单整自回归移动平均(ARIMA)模型,并分别应用它们对2011年各月的指标值进行了预测。在此基础上进行组合预测,得出了2011年1-12月福建省社会消费品零售总额的预测值。预测结果对更好地引导消费具有重要作用,模型建立的过程和方法能为相关研究提供借鉴。     

Assessing the Exacerbations Risk of Influenza‐Associated Chronic Occupational Asthma

The purpose of this article was to conduct a risk‐based study based on a linkage of experimental human influenza infections and fluctuation analysis of airway function to assess whether influenza viral infection was risk factor for exacerbations of chronic occupational asthma. Here we provided a comprehensive probabilistic analysis aimed at quantifying influenza‐associated exacerbations risk for occupational asthmatics, based on a combination of published distributions of viral shedding and symptoms scores and lung respiratory system properties characterized by long‐range peak expiratory flow (PEF) dynamics. Using a coupled detrended fluctuation analysis‐experimental human influenza approach, we estimated the conditional probability of moderate or severe lung airway obstruction and hence the exacerbations risk of influenza‐associated occupational asthma in individuals. The long‐range correlation exponent (α) was used as a predictor of future exacerbations risk of influenza‐associated asthma. For our illustrative distribution of PEF fluctuations and influenza‐induced asthma exacerbations risk relations, we found that the probability of exacerbations risk can be limited to below 50% by keeping α to below 0.53. This study also found that limiting wheeze scores to 0.56 yields a 75% probability of influenza‐associated asthma exacerbations risk and a limit of 0.34 yields a 50% probability that may give a representative estimate of the distribution of chronic respiratory system properties. This study implicates that influenza viral infection is an important risk factor for exacerbations of chronic occupational asthma.     

季节性数据特征驱动的电子废弃物回收规模分解集成预测建模研究

电子废弃物回收规模预测是政府制定循环经济发展规划和有关补贴政策、企业进行资源回收价值评估和产能优化的基础。本文考虑电子废弃物回收规模季度数据的季节性数据特征可能导致传统单模型预测误差偏大、预测结果不稳定等问题，基于“分解-集成”的思想提出了季节性数据特征驱动的电子废弃物回收规模预测CH-X12/STL-X框架。首先，基于Canova-Hansen(CH)检验对电子废弃物回收规模时间序列的季节性数据特征进行识别，继而对适于进行季节性分解的时间序列采用X12乘法模型或时间序列季节性分解(Seasonal-trend Decomposition Procedure Based on Loess，STL)模型实现季节性分量提取。然后，采用Holt-Winters模型对获得的季节性分量进行预测，并以支持向量回归模型(Support Vector Regression，SVR)预测分解获得的其他分量。最后，通过对各个分量预测结果的线性求和以得到最终的预测结果。实证结果表明，提出CH-X12/STL-X预测框架能够较好地满足不同季节性数据特征驱动的时间序列预测建模需求，且较传统单模型(Holt-Winters模型、季节性差分自回归滑动平均模型、SVR模型)在预测性能上表现良好且稳定。