EpiWatch, the AI-driven early warning system for epidemics


The event that inspired the development of EpiWatch, an AI-driven early warning detection system for epidemics, was the West African ebola outbreak of 2014, according to UNSW professor of global biosecurity Raina MacIntyre.

Given this outbreak and subsequent epidemics, Professor MacIntyre said the world was in urgent need of real change in the way outbreaks are detected, paving the way for better epidemic and pandemic preparedness, response and mitigation.

“The West African ebola epidemic was a preventable catastrophe and got us thinking about how early warning signals may prevent epidemics from spreading,” Professor MacIntyre said. “With NHMRC grant funding obtained in 2016, we began developing EpiWatch.”

“There wasn’t a lot of interest, but we persevered and turned it into an automated AI system in 2018. By 2019, we had run out of funding, so as the COVID pandemic started spreading in late 2019, there were no analysts to monitor EpiWatch and to act on early signals. But in hindsight, we could have detected a signal for COVID in mid-November 2019.”

Fast forward to 2021 and epidemiological surveillance systems are now – not surprisingly – in hot demand.

Raina MacIntyre, UNSW Professor of Global Biosecurity

“COVID changed everyone’s opinion on the value of early warning systems, and they began springing up everywhere by 2021. But we had been thinking about it, working on it and improving our system for much longer.”

The UNSW team is a finalist in the 2022 InnovationAus Awards for Excellence for the Digital Health and Health Tech category. It has been working hard to realise its visio to become the centre of epidemic intelligence for global decision-makers and to help prevent the next pandemic.

So, how does EpiWatch work? Essentially, the epidemic intelligence system curates, prioritises, and filters incoming data and provides analytical tools, thereby increasing efficiency while reducing unmanageable data loads for users.

And it’s far-reaching. It was developed as a manual system in 2016 and semi-automated in 2018 and has now been enhanced with search capability covering 42 global languages including almost all major Asian languages.

The main focus areas for the platform includes influenza, COVID-19, pneumococcal disease, herpes zoster, Ebola, MERS CoV, smallpox and measles.

“We research the rapid detection and prevention of these threats through our AI-driven observatory EpiWatch.”

In addition to the early detection observatory, the risk analytic tools can enhance the early warning system capabilities by red flagging urgent events or helping to prioritise responses.

“The COVID-19 pandemic we witnessed – and still experiencing – isn’t the last of its kind. Many more will emerge, threatening our daily lives. On our part, we’re striving to provide an end-to-end solution that’ll help to prevent the next pandemic and ensure health security for all.”

The Covid pandemic proved there are many gaps in the existing systems used for outbreak detection and reporting.

“Our system represents real world value for Australia because early detection, prevention and mitigation of serious epidemics and pandemics saves lives, avoids disruption to families, supply chains and business, and allows us to focus on growth and prosperity as a nation.

Empowering public health innovation
The EpiWatch team is working closely with the government, industry and NGOs to make informed decisions about responses to emerging and existing epidemics and prevent them from becoming pandemics, Professor MacIntyre said.

“EpiWatch is a public health innovation that will enable decision makers to enact life-saving and appropriate public policy and for health care professionals and clinicians to implement.”

Its footprint in the US and UK through its PLuS Alliance university partners should enable further growth of EpiWatch globally, and leverages Australia’s strategic international relationships.

“We will manage background and shared IP during the next five years between the universities and CSIRO, and a range of other partners. These have been addressed with an intellectual property plan that provides incentives for partners and adequate protections for background IP.”

Through use of AI in public health surveillance and gamified tools for decision support, Professor MacIntryre said the innovation would lead the transformation of the public health workforce and disruptive new models of public health epidemic response.

“Our vision is that EpiWatch will be the leading global hub for epidemic detection, prevention, and mitigation, with 24/7 analytics capability to provide advanced, real-time decision support.”

Do you know more? Contact James Riley via Email.

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