Community epidemiology and environmental health risk from dioxin contamination in Paritutu

This article explores community-awareness perspectives and actions towards dioxin-related health exposure in Paritutu Community, New Plymouth, New Zealand. The actions are analysed through media reports, covering a 10-year period from 1998 to 2008. Since 1964, Paritutu Community residents have expressed concern about increased morbidity associated with dioxin contamination from a nearby agrichemical plant. Upon investigation, official agencies were at first unable to verify a causal link between dioxin and morbidity, precipitating community activism and increasing public pressure on relevant authorities. Residents played a major role in alleviating further damage to their community by analysing and evaluating data and providing information that ultimately resulted in both official recognition of their environmental health risk and preventative strategies to alleviate their morbidity. This article backgrounds the Paritutu Community Epidemiology approach and evaluates stages in how the Paritutu Community overcame indifference and lack of precaution and exerted influence leading to the removal of the source of contamination and positive policy changes in public health including the setting up of ameliorative health services for affected people. The findings of this research support theories of popular, lay, community and worker epidemiology.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

This study aimed at understanding how landscape heterogeneity influences outbreaks of contagious diseases in southern Africa. Landscape attributes influence patterns of movement and behaviour of animal hosts, virus spread and survival, as well as land use practices. A multi-agent simulation was developed to represent the spatial and temporal dynamics of pathogens between human-livestock and wildlife interfaces at the fringe of large wildlife conservation areas. The model represents the three main elements associated with epidemics - populations, space, and time - to simulate direct contacts between wildlife and livestock. The dynamics of these populations emerge from interactions between agents and the landscape. The model was calibrated to represent the transmission of foot-and-mouth disease through direct contact at the border of the Kruger National Park in South Africa. In the region, African buffaloes (Syncerus caffer) act as reservoirs of the virus and spread the infection to domestic cattle bordering the park. We tested the sensitivity of various factors influencing contact rate between buffaloes and cattle, and thus the risk of foot-and-mouth disease transmission. Results show that cattle-buffalo contacts mostly depend on the range of displacements of cattle and buffaloes, as influenced by the landscape configuration, and on the number of fence breakages multiplied by the time between breakage and repair. Contacts take place not only close to water-points but also in grazing areas, within an area up to 6 km from the fence.     

以污水流行病学监测广西某市12个污水处理厂服务区域精神活性物质的消耗量

精神活性物质滥用和使用量逐年递增正成为社会稳定、环境健康新的关注点。准确地估算某一地区这类化合物的消耗总量是管理这类物质的关键。本研究对中国广西某市12个污水处理厂(wastewater treatment plants,WWTPs)服务区域中的8种精神活性物质消耗量进行了调查。首先,采用固相萃取-液相色谱-串联质谱法测定了广西某市12个WWTPs进水中8种精神活性物质的浓度,检测到在<方法检测(method detection limit,MDL)至170.9 ng·L^-1范围内的5种精神活性物质。然后,依据污水流行病学(wastewater-based epidemiology,WBE)进行消耗量反算。结果表明,氯胺酮(ketamine,KET)、吗啡(morphine,MOR)、冰毒(methamphetamine,METH)、摇头丸(3,4-methylenedioxymethamphetamine,MDMA)是主要检出的精神活性物质,平均消耗量分别为682.4、167.8、44.6、11.3 mg·d^-1·1000inh^-1;而可卡因(cocaine,COC)、苯甲酰爱康宁(benzoylecgonine,BE)、甲卡西酮(methcathinone,MC)没有被检出。对WWTPs进水中精神活性物质的残留进行分析,估算这些物质在特定区域的消耗量,为防控风险提供支持。     

广东某市疫情期间污水中精神药物的分布特征和滥用评价

采用污水流行病学的方法,研究了2020年新冠疫情期间及前后广东省某市生活污水中两种典型精神药物甲基苯丙胺和氯胺酮的赋存特征及其变化情况,并运用手机信令数据分析人口总数、结构特征及其变动规律,进而将两者结合分析了疫情期间及前后两种药物的消费量变化特征.结果表明,疫情期间该市实际人口相对于疫情前下降了约45%,两种药物总消费量相对于疫情前下降了约75%.总消费量的显著下降很大程度是由疫情期间实际人口下降造成的.实际上,疫情期间该市甲基苯丙胺和氯胺酮的人均消费水平相对于疫情前下降不到50%.考虑到疫情期间严格的管控措施,这一下降幅度说明这两种精神类药物滥用极其顽固;而疫情后两种药物的消费量及在环境中的浓度又基本恢复到疫情前的水平,进一步证明了精神类药物滥用的顽固性.     

Evaluation of the validity of the US EPA's cancer risk assessment of arsenic for low-level exposures: a likelihood ratio approach

Skin cancers associated with ingesting of arsenic have been documented since the 19th century. A study in the southwestern coastal area of Taiwan where people drank well water containing arsenic is generally recognised as providing the best data available for quantifying the risk, and the US Environmental Protection Agency (EPA) used these data to conduct a risk assessment of arsenic ingestion. However, the lowest exposure category in the Taiwan study included arsenic levels up to 290 µg L^–1, which is nearly six times higher than the current EPA maximum contaminant level (MCL), 50 µg L^–1. Therefore, the EPA risk assessment model extrapolated data on high-level exposures to generate risk estimates for low-level exposures. To evaluate the validity of this model, we conducted a quantitative review of epidemiological studies observing arsenic exposures below 290 µg L^–1. A ratio of the likelihood of the EPA model being inappropriate to that of it being appropriate was calculated for each study population as a measurement of the validity of the EPA model. Although existing human data on low-level exposures are limited, the review suggested that the EPA model is unlikely to be able to predict the risk of skin cancer accurately when the arsenic exposure level is between 170 and 270 µg L^–1.     

A framework for predicting personal exposures to environmental hazards

This paper presents a general framework for constructing a predictive distribution of the exposure to an environmental hazard sustained by a randomly selected member of a designated population. The individual’s exposure is assumed to arise from random movement through the environment, resulting in a distribution of exposure that can be used for environmental risk analysis. A specialization of the general framework is that of predicting human exposure to air pollution that can be used to develop models for such things as exposure to particulate matter; practical aspects of their construction are considered. These models can help answer questions such as what fraction of the population sustained ‘high’ levels of exposure for say 5 days in a row. The immediate implementation of the above framework takes the form of a computing platform referred to as pCNEM. This provides a facility for simulating exposures to airborne pollutants and is described in detail elsewhere. This paper considers some theoretical aspects underpinning probabilistic exposure models of this type, with the ideas illustrated in developing a model for predicting human exposure to PM ₁₀.     

The Conservation Relevance of Epidemiological Research into Carnivore Viral Diseases in the Serengeti

Abstract:  Recent outbreaks of rabies and canine distemper in wildlife populations of the Serengeti show that infectious disease constitutes a significant cause of mortality that can result in regional extirpation of endangered species even within large, well-protected areas. Nevertheless, effective management of an infectious disease depends critically on understanding the epidemiological dynamics of the causative pathogen. Pathogens with short infection cycles cannot persist in small populations in the absence of a more permanent reservoir of infection. Development of appropriate interventions requires detailed data on transmission pathways between reservoirs and wildlife populations of conservation concern. Relevant data can be derived from long-term population monitoring, epidemic and case-surveillance patterns, genetic analyses of rapidly evolving pathogens, serological surveys, and intervention studies. We examined studies of carnivore diseases in the Serengeti. Epidemiological research contributes to wildlife conservation policy in terms of management of endangered populations and the integration of wildlife conservation with public health interventions. Long-term, integrative, cross-species research is essential for formulation of effective policy for disease control and optimization of ecosystem health.     

Modeling the Effect of Population Dynamics on the Impact of Rabbit Hemorrhagic Disease

Abstract:  The European wild rabbit ( Oryctolagus cuniculus ) is a staple prey species in Mediterranean ecosystems. The arrival and subsequent spread of rabbit hemorrhagic disease throughout southwestern Europe, however, has caused a decline in rabbit numbers, leading to considerable efforts to enhance wild rabbit populations, especially through habitat management. Because rabbit population dynamics depend on habitat suitability and changes in habitat structure and composition subsequent to habitat management, I evaluated the effects of population dynamics on the long-term impact of rabbit hemorrhagic disease on rabbit populations. I used an age-structured model with varying degrees of population productivity and turnover and different habitat carrying capacities, and I assumed the existence of a unique, highly pathogenic virus. My results suggest that disease impact may be highly dependent on habitat carrying capacity and rabbit population dynamics, and the model provided some insight into the current abundance of wild rabbits in different locations in southwestern Europe. The highest disease impact was estimated for populations located in habitats with low to medium carrying capacity. In contrast, disease impact was lower in high-density populations in habitats with high carrying capacity, corresponding to a lower mean age of rabbit infection and a resulting lower mortality from rabbit hemorrhagic disease. The outcomes of the model suggest that management strategies to help rabbit populations recover should be based on improving habitats to their maximum carrying capacity and increasing rabbit population productivity. In contrast, the use of strategies based on temporary increases in rabbit density, including vaccination campaigns, translocations, and temporal habitat improvements at medium carrying capacities, may increase disease impact, resulting in short-term decreases in rabbit population density.     

A new method for spatially moving correlation analysis in geomedicine

A method of correlation analysis within a spatially moving window was applied to two sets of epidemiological/geochemical data in Norway, (1) mortality/disability rates of multiple sclerosis (MS) versus atmospheric fallout of Mg and concentrations of Se in overbank sediment, and (2) incidence rates of malignant melanoma of the skin (MM) versus concentrations of Ca and K in overbank sediment. It appears that n = 17 observation sites within the moving window is a practical compromise between noise in the data at small values of n and a spatial resolution good enough to detect trends in the distribution patterns of the correlation coefficient. For MS versus Mg, MS versus Se and MM versus Ca the correlation coefficients are generally negative and depict systematic distribution patterns with anomalous clusters of sites with good correlation. For MS versus Se the correlation coefficients also form an additional cluster of positive coefficients. Tests with permutated data show that more than 70% of the negative correlation coefficients for MS versus Mg and for MM versus Ca are both significantly different from zero at p<0.05, while less than 15% of those for MS versus Se are significant at the same level. For MM versus K the correlation coefficients are randomly distributed and not significantly different from zero. The described correlations may be effects of confounders and do not per se indicate any causal relationships. However, further research based on these results may well lead to the identification of possible aetiological factors.