AI system uses wastewater data to predict COVID hospitalizations

New research demonstrates that it is possible to accurately predict hospital admission numbers due to COVID-19 up to four weeks in advance using an artificial intelligence (AI) based system together with COVID wastewater sampling, according to a press release from the University of Technology Sydney.

The study, published in the journal Nature Communications, used wastewater data from 159 counties in the U.S., covering nearly 100 million Americans, along with U.S. hospital admission records, to develop the prediction model.

The research was led by Qilin Wang and Xuan Li from the University of Technology Sydney together with researchers from UNSW Sydney, Delft University of Technology and Morgan State University.

Li was recently awarded a two-year grant from the Australian Academy of Science WH Gladstones Population and Environment Fund to develop an Australian-based wastewater prediction model.

“COVID-19 still poses a heavy burden on healthcare systems around the world. The number of Australians in hospital with Covid-19 peaked at around 5500 and continues to fluctuate. Rapid increases in patient numbers can stress frontline healthcare capacity and increase fatality rates,” Li said.

“Current prediction methods are based on COVID-19 laboratory testing, or self-testing and reporting, however this does not pick up asymptomatic cases, and many countries are moving away from rigorous testing requirements,” she said.

Wang said the research shows wastewater surveillance combined with AI-based modelling can be a cost-effective early warning system, allowing public health officials to better prepare for and manage pandemic waves, and efficiently allocate limited healthcare resources.

Li hopes to extend her research to include other infectious diseases that can be detected through wastewater-based epidemiology, including food-borne pathogens, such as salmonella and E-coli, and viruses such as flu, norovirus and hepatitis A.

“My PhD focused on sewer design to reduce concrete corrosion, however I graduated right around the time of COVID-19 and saw an opportunity to monitor and study the pandemic,” said Li.