New mathematical models may help us predict the spread of future epidemics © Getty Images

New mathematical models may help us predict the spread of future epidemics

The new models take into account that a disease moving from animals to humans will have to evolve.

Mathematical predictions may have missed how rapidly the novel coronavirus would develop from threat to world-wide pandemic, but researchers are working hard to find new models that will.

Advertisement

When it comes to something spreading through a population, be it a virus, social media meme or fake news, there are mathematical models that can be used to predict its trajectory. These models rely heavily on data taken at the outset but most assume that whatever is spreading is going to stay the same throughout its lifetime.

In reality, though, things can change rapidly and dramatically. For example, different viruses mutate at varying rates. In an effort to combat this shortcoming, a team of researchers from Carnegie Mellon University and Princeton University have developed a new mathematical model that incorporates this ‘evolution’ of an infectious entity.

Read more about COVID-19:

“If we are to ignore evolution, we underestimate the severity of the epidemic,” the researchers stated in the study, which was funded by the U.S. Army and published in the Proceedings of the National Academy of Sciences.

In the case of viruses, 60 per cent of infectious diseases that have emerged since 1940 have been zoonotic – meaning that they originated in animals, much like the novel coronavirus.

The ability of a zoonotic diseases to go from animal-to-human transmission and to human-to-human transmission depends on the pathogen evolving to a strain that is well-adapted to the human host, the team say.

Read more about maths:

“These evolutionary changes have a huge impact,” said Osman Yağan, corresponding author of the study. “If you don’t consider the potential changes over time, you will be wrong in predicting the number of people that will get sick or the number of people who are exposed to a piece of information.”

Advertisement

The researchers said they have shown that their model works using real-world data, and hope that the theory will help improve, predict and ultimately help contain the spread of future epidemics.

Reader Q&A: Why don’t viruses like the flu die off when no one is ill?

Asked by: Andrew Cirel, via email

Strictly speaking, viruses can’t ‘die off’ as they’re just inanimate strips of genetic material plus other molecules. But the reason that they keep coming back is because they’re always infecting someone somewhere; it’s just that at certain times of the year, they’re less able to infect enough people to trigger a full-blown epidemic.

Many viruses flare up during the winter because people spend more time indoors in poorly-ventilated spaces, breathing in virus-laden air and touching contaminated surfaces. The shorter days also lead to lower levels of vitamin D, and this weakens our disease-fighting immune system. Experiments also suggest that the flu virus in particular remains infectious for longer in low temperatures.

But even when conditions aren’t ideal, viruses will find enough people to infect to ensure their survival, until they can come roaring back in an epidemic.

Read more: