Austrian IST scientists show that small differences in behavior determine the success and complete failure of epidemic control.
What is the relationship of fluid physics to the spread of Corona virus? Whirlpools and pandemics seem quite different things, of course, in terms of comfort. However, the latest data on the spread of the epidemic were obtained from Professor of Physics Björn Hoff and his research group at the Institute of Science and Technology of Austria (IST Austria), which specialize in fluids and turbulent flows. When Björn Hof had to cancel a planned visit to Wuhan, his wife’s hometown, early last year, his focus shifted to the spread of the epidemic.
“My group usually studies turbulent flows in pipes and canals,” he explains. “Over the last 10 years, we have shown that the onset of turbulence is described by statistical models that are equally used to describe forest fires and epidemics.” Given this experience, programming the epidemic model was a simple exercise for Burak Budanur, a group theorist and computing expert.
The epidemic curve is not leveling, it is collapsing
Standard epidemic models assume that the level of mitigation constantly affects the peak height of the epidemic. “The curve is expected to level off in proportion to the level of social distancing,” said David Scarselli, lead author. However, when he first modeled epidemics, given the limitations of testing and contact tracking, the picture was quite different. The maximum number of infected people initially decreased as expected, but then suddenly dropped to almost zero as the level of mitigation reached a certain threshold. At one point, about half of the people became infected during the epidemic. Elsewhere, only three percent picked up the disease. Surprisingly, it was impossible to get a result between these two results: either there is a flash of considerable size, or it is almost non-existent.
Failures give faster than exponential growth
Testing known contacts (not testing as such) is one of the most powerful ways to slow the epidemic. However, the number of cases that can be tracked daily is limited, as is the number of tests that can be performed. Because researchers have found that exceeding these limits at one point during an epidemic has far-reaching consequences. “If this happens,” says Timme, “the disease begins to spread more quickly in untested areas, and this inevitably causes an extremely high rate of infection.” Already, exponential growth is huge. This means doubling the infections every few days. Although superexponential means that even the doubling rate is getting faster and faster.
As long as this acceleration can be avoided, the epidemic curves collapse to a relatively low level of cases. It is interesting that it does not matter whether the contact protection is protected by a small or large margin of safety. The figures remain relatively low. If, on the other hand, the limit exceeds only one case, superexponential growth causes the total number of cases to jump to tenfold.
Marginal differences and disproportionate effects
“Like most countries, Austria did not react early against the second wave. When not all contacts were traced back in September last year, it was easy to predict that the number of cases would soon grow faster than the exponential rate, ”says Scarselli. Although it has become clear over the past year that an early and decisive response is extremely important when faced with exponential growth, the group’s study shows that test limitations make time even more important. The difference between the success and failure of the blockade is insignificant, or, as Budanur puts it: “A policy that would have worked yesterday will not only take much longer, but it may fail completely if it is implemented one day too late. “Hoff adds:” Most European countries only reacted when health restrictions threatened. In fact, politicians should have paid attention to their contact groups and blocked them before the shield collapsed.
More recently, the team has explored optimal strategies where locks are used as a preventive measure rather than as emergency braking. A manuscript is currently underway outlining the optimal strategy that minimizes both the number of infected people and the required blocking time.
Reference: May 10, 2021, Natural communications.
DOI: 10.1038 / s41467-021-22725-9