Modelling air pollution for epidemiologic research — Part I: A novel approach combining land use regression and air dispersion

A common limitation of epidemiological studies on health effects of air pollution is the quality of exposure data available for study participants. Exposure data derived from urban monitoring networks is usually not adequately representative of the spatial variation of pollutants, while personal monitoring campaigns are often not feasible, due to time and cost restrictions. Therefore, many studies now rely on empirical modelling techniques, such as land use regression (LUR), to estimate pollution exposure. However, LUR still requires a quantity of specifically measured data to develop a model, which is usually derived from a dedicated monitoring campaign. A dedicated air dispersion modelling exercise is also possible but is similarly resource and data intensive.This study adopted a novel approach to LUR, which utilised existing data from an air dispersion model rather than monitored data. There are several advantages to such an approach such as a larger number of sites to develop the LUR model compared to monitored data. Furthermore, through this approach the LUR model can be adapted to predict temporal variation as well as spatial variation. The aim of this study was to develop two LUR models for an epidemiologic study based in Greater Manchester by using modelled NO₂ and PM₁₀ concentrations as dependent variables, and traffic intensity, emissions, land use and physical geography as potential predictor variables. The LUR models were validated through a set aside “validation” dataset and data from monitoring stations.The final models for PM₁₀ and NO₂ comprised nine and eight predictor variables respectively and had determination coefficients (R²) of 0.71 (PM₁₀: Adj. R² = 0.70, F = 54.89, p < 0.001, NO₂: Adj. R² = 0.70, F = 62.04, p < 0.001). Validation of the models using the validation data and measured data showed that the R² decreases compared to the final models, except for NO₂ validation in the measured data (validation data: PM₁₀: R² = 0.33, NO₂: R² = 0.62; measured data: PM₁₀: R² = 0.56, NO₂: R² = 0.86). The validation further showed low mean prediction errors and root mean squared errors for both models.     

Effect of maternal manganese blood levels on erythrocyte calcium-pump activity in newborns

Manganese (Mn) is widely distributed in the biosphere but occurs in only trace amounts in animal tissues. Although Mn deficiency and toxicity both have pathological consequences, the underlying biochemical lesions have not been well defined. In vitro studies suggest that transport proteins are affected by Mn, lead (Pb), and selenium (Se). Among these transport proteins, the calmodulin-regulated calcium pump (Ca(2+)Mg(2+)ATPase) could be inhibited by Mn. In order to understand Mn biochemical pathways, we examined the relationships between Mn blood levels and red blood cell Ca-pump activity among 248 mothers and newborns, environmentally exposed to Mn, Pb, and Se. POPULATION AND METHODS: 248 mother-newborn pairs were recruited at Robert Debré University Hospital (Paris). Blood Mn and Pb concentrations were measured by absorption spectrophotometry. Se was measured by fluorometric method. Red blood cell membrane suspensions were obtained for Ca-pump activity measurements. Linear and quadratic regression models and Pearson correlation were performed. RESULTS: A non-linear parabolic relationship between maternal Mn blood levels and newborn Ca-pump activity was discovered from the analysis of the observed data. The peak level of maternal Mn that corresponded to a maximal activity of the newborn Ca-pump was estimated at 23.9 microg/l with a 95% confidence interval of 17.6 to 32.4 microg/l. An inhibition of this enzyme was observed at low and high levels of maternal Mn. The relationships between the newborn Ca-pump activity and maternal Se and Pb levels became non-significant after adjustment on all the co-factors included in the final model. CONCLUSION: Maternal environmental exposure to Mn, as reflected by maternal blood levels of this metal, is associated with a reduced activity of newborn erythrocyte Ca-pump in a non-linear pattern. Mn levels between 17.6 and 32.4 microg/l in maternal blood probably correspond to the optimal physiological concentration for the metabolism of this enzyme in newborns.     

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。     

广州市1997-2007年食物中毒流行病学特征分析

目的分析广州市食物中毒事件流行病学特征,为预防和控制食物中毒的发生提供依据。方法收集1997-2007年的食物中毒档案资料,建立数据库,归类统计分析。结果1997-2007年广州市共发生食物中毒事件520起,中毒人数10103人,死亡41人,发病率为12.82/10万,平均中毒规模为19.43人/起;中毒起数和发病率总体呈阶段性上升趋势,但中毒规模呈下降趋势;中毒高发时间在5-10月份;中毒食物以动物类食品为主(52.69%);42.31%的中毒场所发生在集体食堂;致病因素以微生物污染为主(52.31%);中毒发生原因主要为生熟食品交叉污染以及原料污染或变质;引起中毒死亡主要原因为毒蘑菇和假酒中毒。结论广州市食物中毒预防与控制重点是集体食堂熟肉食品微生物性中毒;加强预防食物中毒宣教工作将有效控制误食有毒食物中毒死亡事件的发生。     

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。     

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.     

Epidemiologic Evolution Platform Using Integrated Modeling and Geographic Information System

At the international level, a major effort is being made to optimize the flow of data and information for health systems management. The studies show that medical and economic efficiency is strongly influenced by the level of development and complexity of implementing an integrated system of epidemiological monitoring and modeling. The solution proposed and described in this paper is addressed to all public and private institutions involved in the fight against the COVID-19 pandemic, using recognized methods and standards in this field. The Green-Epidemio is a platform adaptable to the specific features of any public institution for disease management, based on open-source software, allowing the adaptation, customization, and further development of “open-source” applications, according to the specificities of the public institution, the changes in the economic and social environment and its legal framework. The platform has a mathematical model for the spread of COVID-19 infection depending on the location of the outbreaks so that the allocation of resources and the geographical limitation of certain areas can be parameterized according to the number and location of the real-time identified outbreaks. The social impact of the proposed solution is due to the planned applications of information flow management, which is a first step in improving significantly the response time and efficiency of people-operated response services. Moreover, institutional interoperability influences strategic societal factors.     

2004～2011年黑龙江省流行性腮腺炎流行特征分析

目的了解黑龙江省流行性腮腺炎(简称流腮)的发病水平,并分析其流行病学特征,为制定流腮防治策略、加速控制流腮流行提供科学依据。方法对黑龙江省2004～2011年中国疾病预防控制信息系统报告资料进行流行病学特征分析。结果 2004～2011年黑龙江省共报告流腮病例39 236例,年平均发病率为16.10/10万;全年均有发病,但存在两个发病高峰期,分别为4～7月和11月～次年1月,12月和6月是发病最多的月份;13个地市均有流腮病例发生;该省流腮病例主要集中在20岁以下人群,2岁以下儿童发病较少,5～9岁组发病最多,且主要集中在中小学生和托幼儿童。结论进一步了解了黑龙江省流行性腮腺炎的流行特征,并提出了加强流行性腮腺炎疫情的防控措施。     

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.     

The involvement of drugs in drivers of motor vehicles killed in Australian road traffic crashes

A multi-center case-control study was conducted on 3398 fatally-injured drivers to assess the effect of alcohol and drug use on the likelihood of them being culpable. Crashes investigated were from three Australian states (Victoria, New South Wales and Western Australia). The control group of drug- and alcohol-free drivers comprised 50.1% of the study population. A previously validated method of responsibility analysis was used to classify drivers as either culpable or non-culpable. Cases in which the driver "contributed" to the crash (n=188) were excluded. Logistic regression was used to examine the association of key attributes such as age, gender, type of crash and drug use on the likelihood of culpability. Drivers positive to psychotropic drugs were significantly more likely to be culpable than drug-free drivers. Drivers with Delta(9)-tetrahydrocannabinol (THC) in their blood had a significantly higher likelihood of being culpable than drug-free drivers (odds ratio (OR) 2.7, 95% CI 1.02-7.0). For drivers with blood THC concentrations of 5 ng/ml or higher the odds ratio was greater and more statistically significant (OR 6.6, 95% CI 1.5-28.0). The estimated odds ratio is greater than that for drivers with a blood alcohol concentration (BAC) of 0.10-0.15% (OR 3.7, 95% CI 1.5-9.1). A significantly stronger positive association with culpability was seen with drivers positive to THC and with BAC > or =0.05% compared with BAC > or =0.05 alone (OR 2.9, 95% CI 1.1-7.7). Strong associations were also seen for stimulants, particularly in truck drivers. There were non-significant, weakly positive associations of opiates and benzodiazepines with culpability. Drivers positive to any psychoactive drug were significantly more likely to be culpable (OR 1.8, 95% CI 1.3-2.4). Gender differences were not significant, but differences were apparent with age. Drivers showing the highest culpability rates were in the under 25 and over 65 age groups.