HEALTH RISKS ASSOCIATED WITH CONSUMPTION OF UNTREATED WATER FROM HOUSEHOLD ROOF CATCHMENT SYSTEMS1

ABSTRACT: Rainwater harvesting is receiving increased attention worldwide as an alternative source of drinking water. Although collected rainwater is typically consumed without any type of disinfection, the microbial quality of this type of water source can be poor. Around the world, consumers of collected and stored rainwater may be at considerable risk to a variety of infectious diseases. This review presents studies attributing specific risks of diseases to the consumption of contaminated rainwater. Diseases attributed to the consumption of untreated rainwater include bacterial diarrheas due to Salmonella and Campylobacter, bacterial pneumonia due to Legionella, botulism due to Clostridium, tissue helminths, and protozoal diarrheas from Giardia and Cryptosporidium. Simple indicator systems such as fecal coliform measurements may prove to be inadequate for determining microbial risks associated with consumption of water from rainwater catchment systems.     

Exposure to DDT and HCH congeners and associated potential health risks through khat (Catha edulis) consumption among adults in South Wollo,Ethiopia

Environmental Geochemistry and Health - Khat (Catha edulis) chewing is widespread in the region of East Africa. Even low levels of organochlorine pesticides (OCPs) in khat could induce public...     

Wildlife contact analysis: emerging methods, questions, and challenges

Recent technological advances, such as proximity loggers, allow researchers to collect complete interaction histories, day and night, among sampled individuals over several months to years. Social network analyses are an obvious approach to analyzing interaction data because of their flexibility for fitting many different social structures as well as the ability to assess both direct contacts and indirect associations via intermediaries. For many network properties, however, it is not clear whether estimates based upon a sample of the network are reflective of the entire network. In wildlife applications, networks may be poorly sampled and boundary effects will be common. We present an alternative approach that utilizes a hierarchical modeling framework to assess the individual, dyadic, and environmental factors contributing to variation in the interaction rates and allows us to estimate the underlying process variation in each. In a disease control context, this approach will allow managers to focus efforts on those types of individuals and environments that contribute the most toward super-spreading events. We account for the sampling distribution of proximity loggers and the non-independence of contacts among groups by only using contact data within a group during days when the group membership of proximity loggers was known. This allows us to separate the two mechanisms responsible for a pair not contacting one another: they were not in the same group or they were in the same group but did not come within the specified contact distance. We illustrate our approach with an example dataset of female elk from northwestern Wyoming and conclude with a number of important future research directions.     

Beach macro-litter monitoring on southern Baltic beaches: results,experiences and recommendations

Major objectives were to provide a comprehensive dataset on beach macro-litter for parts of the southern Baltic Sea and to analyse if the methodology is fully applicable and a suitable monitoring method in the Baltic. We carried out a regular macro litter beach monitoring (OSPAR methodology, 4 time a year) on 35 beaches along the German and Lithuanian Baltic coast over 2–5 years. Additional experiments addressed the subjectivity of the field surveys and spatio-temporal variability on different scales. We observed no seasonality of the data and a monthly compared to a 3-monthly sampling resulted in 3 times higher annual item numbers. Along the Lithuanian coast, the average number of items per survey varied between 138 and 340 and along the German Baltic coast between 7 and 404, with a median value of 47. All data showed a very high spatio-temporal variability. Using the Matrix Scoring Technique we assessed beach litter sources. With 50% tourism and recreation was the most important source. 3D–transport simulations helped to explain the minor role of shipping as a source and, compared to the North Sea, the low numbers of items on German Baltic beaches. Floating litter had a short duration time in the western Baltic Sea and offshore drift dominated. Further, the common regular beach cleanings reduced the potential for local litter accumulation and translocation. We suggest a monitoring system on 14 Baltic beaches in Germany and 2 in Lithuania and provide cost calculations. The analysis of macro-litter in cormorant nesting material and the search for beached dead animals did not show any result. We can conclude that the macro-litter beach monitoring method is less suitable for Baltic beaches and should only serve as a complementary method in combination with others.     

Comparative survival of bay scallops in eelgrass and the introduced alga, Codium fragile, in a New York estuary

Eelgrass, Zostera marina, is generally regarded as the preferred habitat of bay scallops, but in some cases scallop populations have persisted or increased in areas lacking eelgrass. This suggests that some other substrate(s) may serve important ecological functions for bay scallops. One candidate is Codium fragile, a macroalgal species with which bay scallops are known to associate and in which we commonly find juvenile and adult bay scallops in eastern Long Island, New York. In this study, we examined whether survival of planted bay scallops differed in Codium, eelgrass, and Codium + eelgrass substrates at two sites during August and October of 2 years. Survival of tethered scallops and recoveries of live free-planted individuals varied with scallop size, planting season and year, but no differences were observed between the three substrates for a given scallop size and planting date. Crab (particularly Dyspanopeus sayi) and whelk predation were implicated as important causes of tethered scallop mortalities while emigration and removal by predators likely contributed to scallop losses. Densities of naturally recruited 0+ years scallops recovered by visual and suction dredge sampling were similar in the eelgrass and Codium substrates. While our results suggest that Codium may offer some degree of predation refuge for bay scallops, further work needs to weigh the potential disadvantages of this substrate (such as low DO levels, potential attachment and transport of scallops, and differences in current flow, food availability and sedimentation relative to eelgrass) to determine if Codium may serve as a valuable habitat for bay scallops throughout their lifespan.     

A framework for evaluating regional-scale numerical photochemical modeling systems

This paper discusses the need for critically evaluating regional-scale (~200–2,000 km) three-dimensional numerical photochemical air quality modeling systems to establish a model’s credibility in simulating the spatio-temporal features embedded in the observations. Because of limitations of currently used approaches for evaluating regional air quality models, a framework for model evaluation is introduced here for determining the suitability of a modeling system for a given application, distinguishing the performance between different models through confidence-testing of model results, guiding model development and analyzing the impacts of regulatory policy options. The framework identifies operational, diagnostic, dynamic, and probabilistic types of model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether model estimates are in agreement with the observations in an overall sense. Diagnostic evaluation focuses on process-oriented analyses to determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to simulate changes in air quality stemming from changes in source emissions and/or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the confidence that can be placed in model predictions using techniques such as ensemble modeling and Bayesian model averaging. The advantages of these types of model evaluation approaches are discussed in this paper.