Mon, Sep 11|
03-EPIWATCH - Artificial Intelligence for Epidemic Surveillance and Early Warnings
Organizer: EPIWATCH, Biosecurity Program, The Kirby Institute, University of New South Wales
Time & Location
Sep 11, 2023, 8:00 PM – 8:05 PM
Room 4.02, 155 University Ave, Canberra ACT 2601, Australia
About The Event
BACKGROUND AND CONTEXT The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention, has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is not a replacement for traditional surveillance, but an adjunct to trigger earlier investigation, diagnostics and response to serious epidemics. The widespread adoption of digital open-source surveillance and AI technology is needed for the detection of early signals and prevention of serious epidemics. EPIWATCH is an AI epidemic surveillance system, which provides advanced warning of emerging disease outbreaks and disaster events and a range of interconnected capabilities to prepare, mitigate and respond to epidemics and pandemics.
WORKSHOP FORMAT The workshop will be interactive and will compromise a lecture, followed by two interactive disease scenarios where participants will be able to use open-source data to inform on an epidemic. Participants will write a watching brief on an outbreak of interest using open-source data, which may be publishable.
SUPPORT Follow up support will be provided by the EPIWATCH team for participants who are interested in drafting and submitting a Watching Brief manuscript for publication. Details of this will be provided during the workshop, session 4.
The key learning objectives are: 1. Hands on use of the EPIWATCH system. 2. To interpret and analyze EPIWATCH outbreak data. 3. To learn the principles of outbreak investigation using open-source data.
1. Raina MacIntyre is a physician and epidemiologist, and Head of the Biosecurity Program at the Kirby Institute. She leads a research program in control and prevention of epidemics, pandemics and bioterrorism. She has extensive field experience of outbreak investigation. She developed EPIWATCH, an AI-driven epidemic observatory that harnesses open-source data and has proven capability in early detection of epidemics. The suite of EPWATCH tools includes EPIRISK, a real-time risk analysis tool for epidemics. She has over 450 peer reviewed publications and leads a NHMRC Centre for Research Excellence in Airborne Threats to Health. She has received many awards including the Sir Henry Wellcome Medal and Prize from the Association of Military Surgeons of the US for her risk assessment research on bioterrorism and the 2022 Eureka Prize for Leadership & Innovation in Science. She is the author of Dark Winter – an insider’s guide to pandemics and biosecurity (2022).
2. Abrar Chughtai is a medical epidemiologist with more than 20 years’ experience in the health sector with governmental, non-governmental and international health organizations. He has substantial experience of public health programs and infectious diseases research, having worked in the World Health Organization (WHO) for many years. Currently he is working as a Senior Lecturer in the School of Population Health, University of New South Wales Australia. He is also the director of the Master of Infectious Diseases Intelligence (MIDI) Program at School. Dr Chughtai has worked on EPIWATCH since its inception. His research interests include epidemiology and control of infectious diseases, focusing on emerging and re-emerging infections. During 2021, he has been on secondment to NSW Health COVID-19 Emergency Operation Center.
3. Ashley Quigley is a molecular epidemiologist and Senior Research Associate with the Kirby Institute’s Biosecurity Program. She is the Epi Team Lead for EPIWATCH, an open-source intelligence tool which harnesses the power of AI and open-source data to capture early epidemic signals globally and rapid epidemic detection, leading to the prevention of global spread. Her research focuses on using open-source data synthesized in novel ways to develop new insights into the COVID-19 pandemic and other emerging infectious diseases (EID) to advise public health policy.
CONTACT PERSON: Ashley Quigley (firstname.lastname@example.org)
Maximum number: 20-40
Participants will be required to bring their own laptops.