ATLANTA — A new and innovative system developed by researchers at the Georgia Institute of Technology is opening the possibilities for water quality monitoring at the household level, empowering rural community members to play an integral part in strengthening the public health system of their regions. The system involves fast, simple, in-home water purity testing technologies and cellphones.
In conjunction with the London School of Hygiene and Tropical Medicine and the National Environmental Engineering Research Institute (NEERI) of India, Georgia Tech is pioneering a study that allows the members of eight rural Indian communities to test the quality of their household water supply and report the findings to a national database via text messages. Using this point of consumption testing tactic is giving unprecedented insight into the quality and safety of India’s notoriously hazardous rural drinking water supply.
Launching the project in the summer of 2014, researchers distributed test tubes amongst 1,800 families in 8 rural villages around Nagpur, located at the very heart of the Indian subcontinent. Participants from the communities filled the test tubes with water from their household drinking supply, and after allowing the water to incubate overnight, examined the color of the water. Due to the presence of a reactive material within the test tubes, samples of water containing the waterborne pathogen E. coli turned dark purple, while uncontaminated samples turned yellow. Project volunteers subsequently texted in the results to a computer system at NEERI, which then compiled and analyzed the collection of texts in order to assess the overall water quality of each village.
Given the overwhelming size of India’s rural drinking water system – 10 million service points – public health officials have long been perplexed about how to go about ensuring safe and reliable water access to the country’s rural population. This dilemma is a matter of life and death; the World Bank estimates that nearly a quarter of the nation’s communicable diseases are water-related, and these waterborne diarrheal illnesses have been capable of causing upwards of 1,600 deaths each day. An estimated 30-40 percent of these deaths are a result of E. coli.
Crowdsourcing the water quality of rural communities has a variety of advantages. First and foremost, it is extremely cheap; each test kit costs only 53 cents. It is also extremely simple. Participants need only fill the tubes, observe the color, and text a short code from their cellphone. The affordability and ease of this process allows virtually any individual – regardless of income, education level, or social status – to execute what would normally be a rather complicated, laboratory-based procedure right in their own home.
The accessibility of the process has another consequence: empowerment. Rural villagers can now take the health and safety of their families and communities into their own hands in a way never before imaginable. And as more and more households contribute to the database, the more effective this system can prove to be as a public health resource.
Joe Brown assistant professor in Georgia Tech’s School of Civil and Environmental Engineering and lead of the effort says, “The key to this is aggregating many, many samples that each indicate the presence or absence of bacteria. Individually, the tests don’t tell us much, but if you take a thousand of them, you can compute an estimate of what the microbial counts will be in a typical drinking water source.”
The increasing calculation of data points has already proven successful in the effort of cleaning up the water supply. Positive test results in one community near Nagpur led families to identify a broken sewage pipe as the source of contamination of their town’s drinking supply.
Brown and the Georgia Tech team plan to return to India later in 2015 in order to test the product on a larger scale, and they expect to compare the findings generated by their crowdsourcing technique with findings from NEERI, enacted through more traditional water quality monitoring methods.
“We think this may be a scalable model for large-scale environmental monitoring for settings in addition to India. The tests themselves worked well,” shared Brown.
– Brady Mott