As the world staggers under the weight of the coronavirus pandemic which shows no signs of slowing down, experts are already working out how to cope with future public health emergencies.
In particular they're concerned about the increasing likelihood of an even more devastating pandemic – the dreaded "Disease X" which was added to the World Health Organisation's list of priority diseases in 2017.
The University of Edinburgh's Prof Mark Woolhouse says the next Disease X – meaning an as-yet unknown pathogen with the power to cause a pandemic – is "absolutely" around the corner.
"You could use the phrase 'it is when, not if'," he told the Evening Standard this week.
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Now a team of engineers and epidemiologists have come up with a novel way of modelling the spread of infectious diseases — using a simulation game very similar to The Sims.
The best-selling computer game, the first iteration of which was released in 2000, requires users to control virtual people called "Sims", fulfilling their basic human needs and creating houses for them to live in.
The team designed a modelling programme with some similarities, creating exact replicas of two different cities: Birmingham, England (population 2.6 million) and Bogotá, Colombia (population 11 million).
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They considered each city's average household size, layout, public transport and age distribution before randomly assigning "particles" (representing residents) to move about the city doing their everyday routines and commutes.
They also allowed for "random walks" to account for unpredictable movement such as an impromptu trip to pick up a coffee.
The researchers then let the city simulations run for several months. Like in The Sims, they were able to choose between real-time and sped-up simulation time to mimic both pre-lockdown and lockdown dynamic, as well as how the virus spread in each city.
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Using supercomputers and high-level chemistry analytic techniques, the researchers were able to accurately model how the lockdowns of the past year flattened the Covid-19 infection curves in both cities.
While their modelling wasn't completely accurate in recreating the actual infection rates of either Birmingham or Bogotá, the researchers did come pretty close by using only "hard" data such as population statistics and estimated movement maps.
They found the model tended to over-estimate the number of new infections after re-openings, as the simulation did not account for residents being "more careful about social distancing" following months of lockdown.
It's hoped the findings, which were published on Tuesday in the journal 'Proceedings of the Royal Society A: Mathematical and Physical Sciences', will help epidemiologists better understand and target coronavirus restrictions in the future and eventually bring infection rates down worldwide to manageable levels.
However it's also hoped the model will provide much more longterm use than the current pandemic, with researchers writing it could "simulate the mobility of the entire human population".
Public health experts have been warning for years that unsustainable agricultural practices, from deforestation to battery farming to unhygienic "wet markets" like those in Wuhan, will lead to more pandemics in future that could be even more destructive than Covid-19.
The data from this new study could help scientists to more accurately model human movement and perhaps prevent the spread of infectious diseases in future.
Humans tend to think of ourselves as individuals with free will to do what we like with our lives, but this paper's finding indicates our behaviour is so predictable we're more like Sims.
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