Hand-arm vibration syndrome (HAVS) and musculoskeletal symptoms in the neck and the upper limbs in professional drivers of terrain vehicles--a cross sectional study

This study compares the prevalence of symptoms of Hand-arm vibration syndrome (HAVS) and musculoskeletal symptoms in the neck and the upper limbs, between professional drivers of terrain vehicles and a referent group. 769 male professional drivers of forest machines, snowmobiles, snowgroomers and reindeer herders and 296 randomly selected male referents completed a questionnaire about symptoms of HAVS and musculoskeletal symptoms in the neck and the upper limbs. They also gave information about their lifetime exposure duration driving terrain vehicles and their nicotine use. Prevalence odds ratios (POR) were determined and adjusted for age and nicotine use. Results show that there is a relation between exposure to driving terrain vehicles and some of the symptoms of HAVS (POR: 1.2–6.1). Increased odds of musculoskeletal symptoms in neck, shoulders and wrists were also found (POR 1.2–6.4), and it seemed to be related to the cumulative exposure time.     

Effective Vaccination Policies

We present a framework for modeling the spread of pathogens throughout a population and generating policies that minimize the impact of those pathogens on the population. This framework is used to study the spread of human viruses between cities via airplane travel. It combines agent-based simulation, mathematical analysis, and an Evolutionary Algorithm (EA) optimizer. The goal of this study is to develop tools that determine the optimal distribution of a vaccine supply in the model. Using plausible benchmark vaccine allocation policies of uniform and proportional distribution, we compared their effectiveness to policies found by the EA. We then designed and tested a new, more effective policy which increased the importance of vaccinating smaller cities that are flown to more often. This “importance factor” was validated using US influenza data from the last four years.     

东营市农村居民食物中毒回顾性调查

为调查东营市农村居民食物中毒发生的现情况,采用多级整群随机抽样方法,对山东省东营市20个村庄的15276名农村居民在2002年3月1日至2003年2月28日期间的食物中毒情况进行回顾性问卷调查;数据统计采用SASv8软件分析;按2000年山东省人口普查资料进行率的标化。该期间食物中毒36人,粗发生率235．66／10万,标化发生率225．27／10万,其中男性22人,女性14人,男：女=1．57：1,死亡1人。发病年龄16～68岁,多数在20～59岁。轻度中毒27人,占75．00％,中度中毒6人,占16．67％,重度中毒2人,占5．56％,死亡1人,占2．78％。医疗费用5790元,人均160．83元,其它费用2350元,人均65．28元。该地区农村居民食物中毒发生率较高,给农民群众的健康造成较大威胁,预防和控制农民食物中毒已迫在眉睫。     

德阳地区晒烟病毒种类及发生规律研究

病毒病在德阳晒烟上每隔1-2年大发生一次,造成重大经济损失。1989-1991年,采用ELISA等手段,鉴定了该地区晒烟病毒标样722个。结果表明,烟草普通花叶病毒(TMV)、黄瓜花叶病毒(CMV)、马铃薯病毒Y(PVY)是晒烟上的3种主要病毒。在不同年份或同一年份的不同时期,这3种病毒发生的比例各不相同。重病年以蚜传的CMV、PVY为主。烟草病毒病流行与否与2、3月的气温及雨日关系密切。调查了该地区的毒源植物,提出了以治蚜避蚜、提高烟株抗病力为中心的综合防治措施,取得了明显的防治效果。      

人李斯特菌病监测和预防策略研究

目的通过分析比较李斯特菌病的流行特征、各国的监测方法及预防控制措施,为我国制定李斯特菌病的监测和防控策略提供依据。方法文献比较研究和分析。结果欧美多国已经将李斯特菌病列入法定报告疾病管理,李斯特菌病在欧洲呈上升趋势,在美国有所下降。暴发的发现依赖于病例报告和病人分离菌株的分型和比对。通过暴发调查可以获得危险食品、传播途径等流行病学资料。结论只有将李斯特菌病纳入法定报告疾病管理,将医院分离的病人菌株提交到公共卫生实验室,对实验室确诊病例进行流行病学调查,才能获得李斯特菌病流行规律的资料,采取针对性的防控措施。     

A concise cost analysis of Internet malware

In this paper we present a cost model to analyze impacts of Internet malware in order to estimate the cost of incidents and risk caused by them. The model is useful in determining parameters needed to estimate recovery efficiency, probabilistic risk distributions, and cost of malware incidents. Many users tend to underestimate the cost of curiosity coming with stealth malware such as email-attachments, freeware/shareware, spyware (including keyloggers, password thieves, phishing-ware, network sniffers, stealth backdoors, and rootkits), popups, and peer-to-peer fileshares. We define two sets of functions to describe evolution of attacks and potential loss caused by malware, where the evolution functions analyze infection patterns, while the loss functions provide risk-impact analysis of failed systems. Due to a wide range of applications, such analyses have drawn the attention of many engineers and researchers. Analysis of malware propagation itself has little to contribute unless tied to analysis of system performance, economic loss, and risks.     

Haloacetic acids in drinking water in the United Kingdom

We measured concentrations of haloacetic acids (HAAs) in the water supply in regions covered by three water companies in the UK Approximately 30 samples in each region were obtained for analysis of both THMs and HAAs to assess the levels of HAAs and the relationship between HAAs and THMs, temperature, pH, free and total chlorine. We have found that there is a range of HAA levels in drinking water with the means ranging from 35-95mug/l and a maximum concentration of 244mug/l. In two out of the three regions there was a high correlation between total THMs and total HAAs, but whereas the HAA and THM levels in one of these companies were approximately equal, in another company the HAA levels were 3-4 times higher than the THM levels. In the third region there was no correlation between total THMs and total HAAs even though the average levels were approximately equal. The ratio of total THM and total HAAs levels was significantly correlated with temperature, pH, free and total chlorine. Overall total THM levels are therefore not considered to be a good indicator of HAA levels. Epidemiological studies using total THM levels should be taking this into account in the interpretation of their results, and regulatory authorities when setting water guidelines.     

A modeling framework to accelerate food-borne outbreak investigations

Food safety procedures are critical to reducing pathogen caused food-borne disease (FBD). However there is no way to completely eliminate the risk of consuming contaminated products. When prevention efforts fail, rapid identification of the contaminated product is essential. The medical and economic losses incurred grow with the duration of the outbreak. In this paper we show that before an outbreak occurs, analysis of food sales data, as a proactive intervention, can provide useful product intelligence that we can exploit during an outbreak investigation to accelerate the identification process. Using real grocery retail sales data from Germany, we have implemented a likelihood-based approach to study how such data can be used to accelerate the investigation during the early stages of an outbreak.