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      Interview: How computer modelling can be used to manage pandemics is "far beyond theorizing," says computer scientist in Australia

      Source: Xinhua| 2019-08-16 16:08:11|Editor: xuxin
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      by Levi J Parsons

      SYDNEY, Aug. 16 (Xinhua) -- As modern cities become more urbanized and interconnected, they also grow more vulnerable to the threat of pandemics. But thanks to groundbreaking research in the field of computer modelling, new technology may allow future generations to track, predict and avert the outbreak of deadly contagious diseases.

      At the forefront in this area of computer science, Ukrainian-born Professor Mikhail Prokopenko, who now resides in Australia, told Xinhua in an interview for the Sydney Science Festival, "it's not just science fiction ... we are definitely far beyond just theorizing."

      As director of the Complex Systems Research Group at the University of Sydney, the world-renowned computer scientist is an expert trying to make sense of complex self-organizing systems.

      Ranging from smart cities, mega-projects, power grids, ecosystems and transport networks, complex systems are comprised of a large number of diverse interacting parts which make them highly susceptible to unexpected and "apparent uncontrolled behaviors".

      "Pandemics, is indeed a good example of a complex self-organizing phenomenon because the actual disease does get transmitted at the local level between carriers," Prokopenko said.

      "However, when the number of infectious people is quite large, and the susceptible population is also quite a large, transmissions can get out of control."

      "And in real time, this is hard to reduce to the individual interactions."

      But with today's modern computing power, all this is beginning to change.

      By mapping artificial populations using Census data, Prokopenko explained that "you can model transmissions of the disease at a higher resolution level ... essentially, at the local level."

      "The level of sophistication is high enough so that we could model the population of Australia in terms of their household composition, mobility between places of residents and their children going to school and back," he said.

      "Once you see an infection, in this artificial population, you could see how fast and what directions it progresses, then you could build some 'what if' scenarios to contrast quarantine with intervention by vaccination, or antiviral prophylactics, to see which of these methods is more efficient, or more effective."

      Seeing advanced computer science as a way to overcome some of the world's most challenging issues, Prokopenko said that people should embrace new technology and keep an open mind when it comes to solving the globes biggest problems.

      "I think it's actually extremely important because we are seeing a revolution here in terms of computational capacity," he said.

      "If people stay with the classical reductionist way of reasoning, we will not really solve these global challenges."

      "To get there. We need to educate people from school age and beyond to understand that some of the phenomena that we're dealing with will not be solved by the classical mindset," Prokopenko said.

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