scholarly journals Prevalence and public health implications of mycotoxigenic fungi in treated drinking water systems

2019 ◽  
Vol 17 (4) ◽  
pp. 517-531 ◽  
Author(s):  
Ntombie Thandazile Mhlongo ◽  
Memory Tekere ◽  
Timothy Sibanda

Abstract Insufficient potable water resources and poorly treated drinking water quality are the world's number one cause for preventable morbidity and mortality from water-related pathogenic microorganisms. Pathogenic microorganisms, including mycotoxigenic fungi, have been identified in treated drinking water. This paper presents a review of mycotoxigenic fungi as a health risk to the public as these fungi are responsible for allergies, cancers and opportunistic infections mainly to immunocompromised patients. The exacerbating factors contributing to fungal presence in water distribution systems, factors that lead to fungi being resistant to water treatment and treated drinking water quality legislations are also discussed. This paper provides a review on the prevalence of mycotoxigenic fungi and their implications to public health in treated drinking water, and the need for inclusion in treated drinking water quality regulations.

2017 ◽  
Vol 3 (5) ◽  
pp. 865-874 ◽  
Author(s):  
Zhiheng Xu ◽  
Wangchi Zhou ◽  
Qiuchen Dong ◽  
Yan Li ◽  
Dingyi Cai ◽  
...  

Drinking water quality along distribution systems is critical for public health.


2017 ◽  
Vol 7 (1.1) ◽  
pp. 47 ◽  
Author(s):  
S. Kavi Priya ◽  
G. Shenbagalakshmi ◽  
T. Revathi

Drinking Water Distribution Systems facilitate to carry portable water from water resources such as reservoirs, river, and water tanks to industrial, commercial and residential consumers through complex buried pipe networks. Determining the consequences of a water contamination event is an important concern in the field of water systems security and in drinking water distribution systems. The proposed work is based on the development of low cost fuzzy based water quality monitoring system using wireless sensor networks which is capable of measuring physiochemical parameters of water quality such as pH, temperature, conductivity, oxidation reduction potential and turbidity. Based on selected parameters a sensing unit is developed along with several microsystems for analog signal conditioning, data aggregation, sensor data analysis and logging, and remote representation of data to the consumers. Finally, algorithms for fusing the real time data and decision making using fuzzy logic at local level are developed to assess the water contamination risk. Based on the water contamination level in the distribution pipeline the drinking water quality is classified as acceptable/reject/desirable. When the contamination is detected, the sensing unit with ZigBee sends signals to close the solenoid valve inside the pipeline to prevent the flow of contaminated water supply and it intimates the consumers about drinking water quality through mobile app. Experimental results indicate that this low cost real time water quality monitoring system acts as an ideal early warning system with best detection accuracy. The derived solution can also be applied to different IoT (Internet of Things) scenario such as smart cities, the city transport system etc.


2018 ◽  
Vol 23 (4) ◽  
pp. 301-309 ◽  
Author(s):  
Martin Allen ◽  
Robert Clark ◽  
Joseph A. Cotruvo ◽  
Neil Grigg

The provision of a safe and sustainable drinking water supply is one of the hallmarks of a successful society. Treated drinking water entering distribution systems in virtually all U.S. public drinking water systems meets regulations and is microbiologically safe. However, the opportunity for microbial contamination from decades to century old water distribution systems is increasing with time. Thus, increased health risk to consumers should be a driving factor in accelerating reinvestment in America’s aging water distribution water systems.


2019 ◽  
Vol 17 (5) ◽  
pp. 777-787 ◽  
Author(s):  
Jennifer R. Cope ◽  
Amy M. Kahler ◽  
Jake Causey ◽  
John G. Williams ◽  
Jennifer Kihlken ◽  
...  

Abstract Naegleria fowleri causes the usually fatal disease primary amebic meningoencephalitis (PAM), typically in people who have been swimming in warm, untreated freshwater. Recently, some cases in the United States were associated with exposure to treated drinking water. In 2013, a case of PAM was reported for the first time in association with the exposure to water from a US treated drinking water system colonized with culturable N. fowleri. This system and another were found to have multiple areas with undetectable disinfectant residual levels. In response, the water distribution systems were temporarily converted from chloramine disinfection to chlorine to inactivate N. fowleri and reduced biofilm in the distribution systems. Once >1.0 mg/L free chlorine residual was attained in all systems for 60 days, water testing was performed; N. fowleri was not detected in water samples after the chlorine conversion. This investigation highlights the importance of maintaining adequate residual disinfectant levels in drinking water distribution systems. Water distribution system managers should be knowledgeable about the ecology of their systems, understand potential water quality changes when water temperatures increase, and work to eliminate areas in which biofilm growth may be problematic and affect water quality.


2018 ◽  
Vol 4 (12) ◽  
pp. 2080-2091 ◽  
Author(s):  
Isabel Douterelo ◽  
Carolina Calero-Preciado ◽  
Victor Soria-Carrasco ◽  
Joby B. Boxall

This research highlights the potential of whole metagenome sequencing to help protect drinking water quality and safety.


2012 ◽  
Vol 12 (5) ◽  
pp. 580-587 ◽  
Author(s):  
Stephen Mounce ◽  
John Machell ◽  
Joby Boxall

Safe, clean drinking water is a foundation of society and water quality monitoring can contribute to ensuring this. A case study application of the CANARY software to historic data from a UK drinking water distribution system is described. Sensitivity studies explored appropriate choice of algorithmic parameter settings for a baseline site, performance was evaluated with artificial events and the system then transferred to all sites. Results are presented for analysis of nine water quality sensors measuring six parameters and deployed in three connected district meter areas (DMAs), fed from a single water source (service reservoir), for a 1 year period and evaluated using comprehensive water utility records with 86% of event clusters successfully correlated to causes (spatially limited to DMA level). False negatives, defined by temporal clusters of water quality complaints in the pilot area not corresponding to detections, were only approximately 25%. It was demonstrated that the software could be configured and applied retrospectively (with potential for future near real time application) to detect various water quality event types (with a wider remit than contamination alone) for further interpretation.


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