TORONTO, Sept. 6, 2022 - Waterborne illness is one of the leading causes of infectious disease outbreaks in refugee and internally displaced persons (IDP) settlements, but a team led by 91亚色 has developed a new technique to keep drinking water safe using machine learning, and it could be a game changer.

As drinking water is not piped into homes in most settlements, residents instead collect it from public tap stands using storage containers.

鈥淲hen water is stored in a container in a dwelling it is at high risk of being exposed to contaminants, so it鈥檚 imperative there is enough free residual chlorine to kill any pathogens,鈥� says Lassonde School of Engineering PhD student Michael De Santi, part of 91亚色鈥檚 Dahdaleh Institute for Global Health Research, who led the research.

Recontamination of previously safe drinking water during its collection, transport and storage has been a major factor in outbreaks of cholera, hepatitis E, and shigellosis in refugee and IDP settlements in Kenya, Malawi, Sudan, South Sudan, and Uganda.

鈥淎 variety of factors can affect chlorine decay in stored water. You can have safe water at that collection point, but once you bring it home and store it, sometimes up to 24 hours, you can lose that residual chlorine, pathogens can thrive and illness can spread,鈥� says Lassonde Adjunct Professor Syed Imran Ali, a Research Fellow at 91亚色's Dahdaleh Institute for Global Health Research, who has first-hand experience working in a settlement in South Sudan.

Using machine learning, the research team, including Associate Professor also of Lassonde, has developed a new way to predict the probability that enough chlorine will remain until the last glass is consumed. They used an artificial neural network (ANN) along with ensemble forecasting systems (EFS), something that is not typically done. EFS is a probabilistic model commonly used to predict the probability of precipitation in weather forecasts.

鈥淎NN-EFS can generate forecasts at the time of consumption that take a variety of factors into consideration that affect the level of residual chlorine, unlike the typically used models. This new probabilistic modelling is replacing the currently used universal guideline for chlorine use, which has been shown to be ineffective,鈥� says Ali.

Factors such as local temperature, how the water is stored and handled from home to home, the type and quality of the water pipes, water quality or did a child dipped their hand in the water container, can all play a role in how safe the water is to drink.

鈥淗owever, it鈥檚 really important that these probabilistic models be trained on data at a specific settlement as each one is as unique as a snowflake,鈥� says De Santi. 鈥淭wo people could collect the same water on the same day, both store it for six hours, and one could still have all the chlorine remaining in the water and the other could have almost none of it left. Another 10 people could have varying ranges of chlorine.鈥�

The researchers used routine water quality monitoring data from two refugee settlements in Bangladesh and Tanzania collected through the Safe Water Optimization Tool Project. In Bangladesh, the data was collected from 2,130 samples by M茅decins Sans Fronti猫res from Camp 1 of the Kutupalong-Balukhali Extension Site, Cox鈥檚 Bazaar between June and December 2019 when it hosted 83,000 Rohingya refugees from neighbouring Myanmar.

Determining how to teach the ANN-EFS to come up with realistic probability forecasts with the smallest possible error required out-of-the-box thinking.

鈥淗ow that error is measured is key as it determines how the model behaves in the context of probabilistic modelling,鈥� says De Santi. 鈥淯sing cost-sensitive learning, a tool that morphs the cost function towards a targeted behaviour when using machine learning, we found it could improve probabilistic forecasts and reliability. We are not aware of this being done before in this context.鈥�

For example, this model can say that under certain conditions at the tap with a particular amount of free residual chlorine in the water, there is a 90 per cent chance that the remaining chlorine in the stored water after 15 hours will be below the safety level for drinking.

鈥淭hat鈥檚 the kind of probabilistic determination this modelling can give us,鈥� says De Santi. 鈥淟ike with weather forecasts, if there is a 90 per cent chance of rain, you should bring an umbrella. Instead of an umbrella, we can ask water operators to increase the chlorine concentration so there will be a greater percentage of people with safe drinking water.鈥�

鈥淥ur Safe Water Optimization Tool takes this machine learning work and makes it available to aid workers in the field. The only difference for the water operators is we ask them to sample water in the container at the tap and in that same container at the home after several hours,鈥� says Ali.

鈥淭his work Michael is doing is advancing the state of practice of machine learning models. Not only can this be used to ensure safe drinking water in refugee and IDP settlements, it can also be used in other applications.鈥�

The paper, , will be published in the journal PLOS Water.

De Santi will deliver a seminar on this paper as part of the Dahdaleh Institute Seminar Series on Sept. 7, from 1 to 2 p.m. EST. It is open to the public and registration is free.

-30-

91亚色 is a modern, multi-campus, urban university located in Toronto, Ontario. Backed by a diverse group of students, faculty, staff, alumni and partners, we bring a uniquely global perspective to help solve societal challenges, drive positive change and prepare our students for success. 91亚色's fully bilingual Glendon Campus is home to Southern Ontario's Centre of Excellence for French Language and Bilingual Postsecondary Education. 91亚色鈥檚 campuses in Costa Rica and India offer students exceptional transnational learning opportunities and innovative programs. Together, we can make things right for our communities, our planet, and our future. 

Media Contact:

Sandra McLean, 91亚色 Media Relations, 416-272-6317, sandramc@yorku.ca

The post Researchers develop novel way to prevent waterborne infectious diseases at refugee settlements appeared first on News@91亚色.

TORONTO, November 14, 2016 鈥� Paper strips laced with sugar could be the sweetest solution so far, literally, to kill E. coli in contaminated water. 91亚色 researcher Sushanta Mitra says the 鈥淒ipTreat鈥� discovery will be key to developing a new generation of inexpensive and portable water treatment devices, with human health benefits in Canada and around the world.

DipTreat is the latest innovation by researchers at 91亚色鈥檚 Lassonde School鈥檚 . The group has previously discovered new ways to detect E. coli in contaminated water using a .

鈥淣ow with DipTreat, we have learned it will take less than two hours to fish, trap and kill E. coli in water,鈥� says Professor Mitra in the Lassonde School of Engineering, who heads up the lab. 鈥淲e were able to efficiently remove almost 90 per cent of bacteria by dipping the special paper strip, DipTreat, in contaminated water samples.鈥�

While using porous paper strips to trap the bacterial cells, for killing, the researchers used an antimicrobial agent extracted from the seeds of moringa 鈥� commonly known as drumstick or horseradish tree. As a result, the DipTreat solution for water treatment uses only naturally available antimicrobial substances and sugar, with minimal environmental and health impact.

Currently, popular water treatment systems use silver nanoparticles and clays, whose long term impact on human health is yet to be fully understood, according Mitra. So far, DipTreat is effective for small quantities of water. For example, someone who is hiking can collect a glass of water and then dip the paper strips to purify it before drinking. Researchers believe that the invention could lead to a much greater impact.

鈥淲e expect this new approach to 鈥榝ish鈥�, 鈥榯rap鈥�, and 鈥榢ill鈥� E.coli will seamlessly eliminate the harmful bacteria from water,鈥� says Mitra, explaining the impact it could have on the national and global health scenario, from the far north of Canada to the remote villages of India, and around the world. Recognizing the global importance of water purification technology, UNICEF has invited Mitra to showcase his team鈥檚 work at a in Copenhagen on November 22.

Published as a in the latest issue of the Royal Society of Chemistry journal , the study is co-authored by Mitra, Saumyadeb Dasgupta and Naga Siva Gunda.

is known for championing new ways of thinking that drive teaching and research excellence. Our students receive the education they need to create big ideas that make an impact on the world. Meaningful and sometimes unexpected careers result from cross-discipline programming, innovative course design and diverse experiential learning opportunities. 91亚色 students and graduates push limits, achieve goals and find solutions to the world鈥檚 most pressing social challenges, empowered by a strong community that opens minds. 91亚色 U is an internationally recognized research university 鈥� our 11 faculties and 26 research centres have partnerships with 200+ leading universities worldwide. Located in Toronto, 91亚色 is the third largest university in Canada, with a strong community of 53,000 students, 7,000 faculty and administrative staff, and more than 295,000 alumni.91亚色 U's fully bilingual Glendon campus is home to Southern Ontario's Centre of Excellence for French Language and Bilingual Postsecondary Education.

Media contact:
Gloria Suhasini, Media Relations, 416 736 2100 ext. 22094, suhasini@yorku.ca

The post 91亚色 U researchers find 鈥渟weet鈥� solution to kill E. coli in drinking water appeared first on News@91亚色.