Edwin Oh In The News
DRI
Wastewater surveillance became a popular choice among public health officials looking to track rapid virus mutations and spread patterns during the COVID-19 pandemic. But what if there was a way to detect emerging virus pathogens even faster — or to even sniff out new variants possibly before patients even realize they’re ill? A new UNLV-led study is moving that dream one step closer to reality by pairing wastewater sample surveillance with artificial intelligence. The results appear in the latest issue of the journal Nature Communications.
Water & WasteWater Asia
Pairing artificial intelligence (AI) with wastewater surveillance may enable public health authorities to identify emerging viruses earlier than current methods, according to a new study led by the University of Nevada, Las Vegas (UNLV). The findings were published in Nature Communications.
Quantum Zeitgeist
Researchers at the University of Nevada, Las Vegas (UNLV), in collaboration with the Southern Nevada Water Authority and other partners, have developed an artificial intelligence algorithm to accelerate wastewater surveillance for emerging viruses and pathogens. Validated through analysis of nearly 3,700 wastewater samples collected between 2021 and 2023, the system accurately identified unique viral signatures with as few as two to five samples, preceding conventional clinical detection methods. This proactive approach, detailed in a study published on July 8, 2025, aims to enhance public health interventions by detecting outbreaks before patients seek treatment, and is one of over 30 collaborations between the involved organisations.