Dataset Information

Estimating the Risk of Domestic Water Source Contamination Following Precipitation Events.

ABSTRACT: Climate change is expected to increase precipitation extremes, threatening water quality. In low resource settings, it is unclear which water sources are most vulnerable to contamination following rainfall events. We evaluated the relationship between rainfall and drinking water quality in southwest Guatemala where heavy rainfall is frequent and access to safe water is limited. We surveyed 59 shallow household wells, measured precipitation, and calculated simple hydrological variables. We compared Escherichia coli concentration at wells where recent rainfall had occurred versus had not occurred, and evaluated variability in the association between rainfall and E. coli concentration under different conditions using interaction models. Rainfall in the past 24 hours was associated with greater E. coli concentrations, with the strongest association between rainfall and fecal contamination at wells where pigs were nearby. Because of the small sample size, these findings should be considered preliminary, but provide a model to evaluate vulnerability to climate change.

SUBMITTER: Eisenhauer IF

PROVIDER: S-EPMC4889765 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Estimating the Risk of Domestic Water Source Contamination Following Precipitation Events.

Eisenhauer Ian F IF Hoover Christopher M CM Remais Justin V JV Monaghan Andrew A Celada Marco M Carlton Elizabeth J EJ

The American journal of tropical medicine and hygiene 20160425 6

Climate change is expected to increase precipitation extremes, threatening water quality. In low resource settings, it is unclear which water sources are most vulnerable to contamination following rainfall events. We evaluated the relationship between rainfall and drinking water quality in southwest Guatemala where heavy rainfall is frequent and access to safe water is limited. We surveyed 59 shallow household wells, measured precipitation, and calculated simple hydrological variables. We compar ...[more]

PMID: 27114298

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Project description:Monitoring of microbial drinking water quality is a key component for ensuring safety and understanding risk, but conventional monitoring strategies are typically based on low sampling frequencies (e.g., quarterly or monthly). This is of concern because many drinking water sources, such as karstic springs are often subject to changes in bacterial concentrations on much shorter time scales (e.g., hours to days), for example after precipitation events. Microbial contamination events are crucial from a risk assessment perspective and should therefore be targeted by monitoring strategies to establish both the frequency of their occurrence and the magnitude of bacterial peak concentrations. In this study we used monitoring data from two specific karstic springs. We assessed the performance of conventional monitoring based on historical records and tested a number of alternative strategies based on a high-resolution data set of bacterial concentrations in spring water collected with online flow cytometry (FCM). We quantified the effect of increasing sampling frequency and found that for the specific case studied, at least bi-weekly sampling would be needed to detect precipitation events with a probability of >90%. We then proposed an optimized monitoring strategy with three targeted samples per event, triggered by precipitation measurements. This approach is more effective and efficient than simply increasing overall sampling frequency. It would enable the water utility to (1) analyze any relevant event and (2) limit median underestimation of peak concentrations to approximately 10%. We conclude with a generalized perspective on sampling optimization and argue that the assessment of short-term dynamics causing microbial peak loads initially requires increased sampling/analysis efforts, but can be optimized subsequently to account for limited resources. This offers water utilities and public health authorities systematic ways to evaluate and optimize their current monitoring strategies.

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Project description:Legionnaires' disease is a potentially fatal pneumonia like infection caused by inhalation or aspiration of water particles contaminated with pathogenic Legionella spp. Household showers have been identified as a potential source of sporadic, community-acquired Legionnaires' disease. This study used qPCR to enumerate Legionella spp. and Legionella pneumophila in water samples collected from domestic showers across metropolitan Adelaide, South Australia. A survey was used to identify risk factors associated with contamination and to examine awareness of Legionella control in the home. The hot water temperature was also measured. A total of 74.6% (50/68) and 64.2% (43/68) showers were positive for Legionella spp. and L. pneumophila, respectively. Statistically significant associations were found between Legionella spp. concentration and maximum hot water temperature (p = 0.000), frequency of shower use (p = 0.000) and age of house (p = 0.037). Lower Legionella spp. concentrations were associated with higher hot water temperatures, showers used at least every week and houses less than 5 years old. However, examination of risk factors associated with L. pneumophila found that there were no statistically significant associations (p > 0.05) with L. pneumophila concentrations and temperature, type of hot water system, age of system, age of house or frequency of use. This study demonstrated that domestic showers were frequently colonized by Legionella spp. and L. pneumophila and should be considered a potential source of sporadic Legionnaires' disease. Increasing hot water temperature and running showers every week to enable water sitting in pipes to be replenished by the municipal water supply were identified as strategies to reduce the risk of Legionella in showers. The lack of public awareness in this study identified the need for public health campaigns to inform vulnerable populations of the steps they can take to reduce the risk of Legionella contamination and exposure.

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Project description:BackgroundAfrican Swine Fever (ASF) is a highly lethal viral disease caused by the African Swine Fever Virus (ASFV), the only virus of the Asfaviridae family, which affects different species of wild and domestic suids, and for which no vaccination or effective medical treatment is currently available. The virus can survive for long periods in the environment, and humans can unintentionally act as vectors through infected fomites, a risk that is linked to the ASF introduction into pig farms. We ran a simulation study, in which we reconstructed the probability process leading to the different forms of human-mediated ASF contamination in ASF endemic areas. We compared the infection risks related to different types of human forest activities and produced estimates of the minimum expected number of human-induced contamination events occurring annually at the scale of some European countries.ResultsWhen analysed on a short temporal scale and in a relatively small spatial context, ASF environmental contamination appeared as a rather unlikely event for most of the simulated forest uses, with contamination probabilities often lower than 0.1%. When scaling up the contamination process to a whole year and to large geographic areas, though, the accumulation of the same forest activities, repeated several times per month within the same patch of forest, produced the expectation that thousands of contamination events would occur each year, with potentially relevant epidemiological consequences. Wild boar supplemental feeding and forest logging emerged as the riskiest activities in terms of contamination probabilities, but risk was highly influenced by the frequency and intensity of the different types of forest use.ConclusionsThe risk of human-mediated ASF environmental contamination should not be disregarded when planning management actions to reduce ASF circulation and prevent its breach into the pig farming system. Supplemental feeding should be strongly reduced or avoided in ASF affected areas. Wild boar hunting, which is often employed as an active management tool in ASF affected areas, should be seen as both a tool for controlling wild boar density and as a potential risk for further contamination. It is essential to implement and enforce strict biosecurity measures for all forest-based human activities in ASF endemic areas.

Dataset Information

Estimating the Risk of Domestic Water Source Contamination Following Precipitation Events.

Publications

Estimating the Risk of Domestic Water Source Contamination Following Precipitation Events.

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