Groundbreaking global research to combat health problems in East Asia, Australia
A groundbreaking new model that will track the presence of infectious diseases in wastewater across Australia and East Asia is one of two global research projects led by the University of Wollongong (UOW) to have been awarded funding under the National Health and Medical Research Council's (NHMRC) e-ASIA 2024 Joint Research Project scheme.
Announced yesterday (Tuesday 17 December), the three-year project, steered by Associate Professor Guangming Jiang, from UOW's School of Civil, Mining, Environmental and Architectural Engineering and Molecular Horizons, and Professor Martina Sanderson-Smith, from the School of Chemistry and Molecular Bioscience and Molecular Horizons, will use tools such as surveillance data and artificial intelligence to analyse the origins and spread of diseases.
Working with researchers from Monash University, the University of New South Wales, and University of Melbourne, as well as teams based in Japan and Indonesia, the project will help to support decision-making in disease control, particularly in low- and middle-income countries. The researchers have been awarded $731,739 by the NHMRC for the three-year project.
Associate Professor Jiang said the potential of wastewater tracking has not yet been realised.
"Sewers, the urban infrastructure's vital arteries, play a critical role in public health by transporting human waste and excreta. Domestic wastewater contains various pathogenic bacteria, viruses and chemicals excreted by people. Wastewater therefore contains chemical and biological information coming directly out of our bodies and is highly informative with regards to infectious diseases, particularly viruses," Associate Professor Jiang said.
"Wastewater-based epidemiology has emerged as a critical tool in complementing clinical testing to monitor the spread of COVID-19 and other infectious diseases. Despite its widespread adoption, the full potential of wastewater-based epidemiology has yet to be unlocked, primarily due to a significant gap in advanced data analytics capable of guiding public health decisions and policy formulation. We are aiming to overcome these limitations by integrating artificial intelligence into wastewater surveillance."
The second project funded under the e-ASIA scheme will see Distinguished Professor Xu-Feng Huang, from UOW's School of Medical, Indigenous and Health Sciences and Molecular Horizons, examine the role of increased fibre intake in combating metabolic syndrome. The research teams have been awarded $1,093,853 for the three-year project, including $495,547 from the NHMRC in Australia, $237,283 from BRIN in Indonesia, $227,238 from PMU-B in Thailand, and $133,785 from DOST-PCHRD in the Philippines.
Collaborating with researchers from Indonesia, Thailand, and the Philippines, the team of UOW researchers, led by Chief Investigator Professor Huang, an expert in molecular nutrition and obesity, will examine molecular mechanisms underlying metabolic syndrome to inform new personalised nutrition and lifestyle recommendations to control metabolic syndrome in South-East Asia and Australia.
Metabolic syndrome is a global and complex health problem, that comprises several conditions that occur together in people, such as hypertension, dyslipidemia, abdominal obesity and insulin resistance. The rising prevalence of metabolic syndrome in East Asia countries places enormous pressure on their health systems and their economies highlighting an urgent need for a new intervention.
Professor Huang said lack of dietary fibre in modern diets, which rely heavily on highly processed and fast food, is exacerbating the rise of metabolic syndrome worldwide. The project will focus on the use of machine learning, a subset of artificial intelligence that leverages computational algorithms, to develop personalised nutrition programs.
"Conventional dietary guidelines for individuals with metabolic syndrome typically emphasise calorie adjustments," Professor Huang said.
"Nevertheless, following these guidelines strictly does not consistently yield the desired reduction in risk factors. This discrepancy arises from variations in individuals' responses to dietary components. In addition, research has shown that metabolic syndrome is influenced by a multitude of factors including genetics, obesity, lifestyle, diet composition, hormonal imbalances and ethnicity.
"Machine learning offers a ground-breaking approach to combat metabolic syndrome. In this context, personalised nutrition will enable us to tailor dietary interventions to individual needs and guiding them towards behaviours conducive to improved health outcomes."
UOW Interim Deputy Vice-Chancellor and Vice President (Research and Sustainable Futures) Senior Professor Eileen McLaughlin congratulated the researchers on their success.
"These are vital projects that offer a truly innovative approach to global health problems. It is always wonderful to see UOW researchers collaborating with academics throughout the world, and I can't wait to see how these projects develop," she said.
